diff --git a/app/routes/admin.sports-seasons.$id.simulator.tsx b/app/routes/admin.sports-seasons.$id.simulator.tsx
index 578315c..f623c01 100644
--- a/app/routes/admin.sports-seasons.$id.simulator.tsx
+++ b/app/routes/admin.sports-seasons.$id.simulator.tsx
@@ -232,33 +232,48 @@ export async function action({ request, params }: Route.ActionArgs): Promise<Act
     }
   }
 
-  if (intent === "save-input-policy") {
+  if (intent === "save-configuration") {
     const currentConfig = await getSportsSeasonSimulatorConfig(sportsSeasonId);
     if (!currentConfig) return { success: false, message: "Simulator config not found." };
 
-    const currentPolicy = getSimulatorInputPolicy(currentConfig.config);
+    // Start from the current merged config so keys not exposed as structured
+    // fields (e.g. string knobs) are preserved untouched.
+    const next: Record<string, unknown> = { ...currentConfig.config };
+
+    // Engine knobs: every numeric field rendered as `engine.<key>`.
+    for (const [field, value] of formData.entries()) {
+      if (typeof value !== "string" || !field.startsWith("engine.")) continue;
+      const key = field.slice("engine.".length);
+      const parsed = Number(value);
+      if (value.trim() !== "" && Number.isFinite(parsed)) next[key] = parsed;
+    }
+
+    // Input-derivation policy (only when the simulator consumes Elo/ratings).
+    if (formData.get("hasInputPolicy") === "1") {
+      const currentPolicy = getSimulatorInputPolicy(currentConfig.config);
+      next.inputPolicy = {
+        ...currentPolicy,
+        missingEloStrategy: parseMissingEloStrategy(formData.get("missingEloStrategy")),
+        missingRatingStrategy: parseMissingRatingStrategy(formData.get("missingRatingStrategy")),
+        // Stored as-is; getSimulatorInputPolicy clamps to [0,1] on read.
+        oddsWeight: parsePolicyNumber(formData, "oddsWeight", currentPolicy.oddsWeight),
+        fallbackElo: parsePolicyNumber(formData, "fallbackElo", currentPolicy.fallbackElo),
+        fallbackEloDelta: parsePolicyNumber(formData, "fallbackEloDelta", currentPolicy.fallbackEloDelta),
+        eloMin: parsePolicyNumber(formData, "eloMin", currentPolicy.eloMin),
+        eloMax: parsePolicyNumber(formData, "eloMax", currentPolicy.eloMax),
+        fallbackRating: parsePolicyNumber(formData, "fallbackRating", currentPolicy.fallbackRating),
+        fallbackRatingDelta: parsePolicyNumber(formData, "fallbackRatingDelta", currentPolicy.fallbackRatingDelta),
+        ratingMin: parsePolicyNumber(formData, "ratingMin", currentPolicy.ratingMin),
+        ratingMax: parsePolicyNumber(formData, "ratingMax", currentPolicy.ratingMax),
+      };
+    }
+
     await upsertSportsSeasonSimulatorConfig({
       sportsSeasonId,
       simulatorType: currentConfig.simulatorType,
-      config: {
-        ...currentConfig.config,
-        inputPolicy: {
-          missingEloStrategy: parseMissingEloStrategy(formData.get("missingEloStrategy")),
-          missingRatingStrategy: parseMissingRatingStrategy(formData.get("missingRatingStrategy")),
-          // Stored as-is; getSimulatorInputPolicy clamps to [0,1] on read.
-          oddsWeight: parsePolicyNumber(formData, "oddsWeight", currentPolicy.oddsWeight),
-          fallbackElo: parsePolicyNumber(formData, "fallbackElo", currentPolicy.fallbackElo),
-          fallbackEloDelta: parsePolicyNumber(formData, "fallbackEloDelta", currentPolicy.fallbackEloDelta),
-          eloMin: parsePolicyNumber(formData, "eloMin", currentPolicy.eloMin),
-          eloMax: parsePolicyNumber(formData, "eloMax", currentPolicy.eloMax),
-          fallbackRating: parsePolicyNumber(formData, "fallbackRating", currentPolicy.fallbackRating),
-          fallbackRatingDelta: parsePolicyNumber(formData, "fallbackRatingDelta", currentPolicy.fallbackRatingDelta),
-          ratingMin: parsePolicyNumber(formData, "ratingMin", currentPolicy.ratingMin),
-          ratingMax: parsePolicyNumber(formData, "ratingMax", currentPolicy.ratingMax),
-        },
-      },
+      config: next,
     });
-    return { success: true, message: "Simulator input policy saved." };
+    return { success: true, message: "Simulator configuration saved." };
   }
 
   if (intent === "save-inputs") {
@@ -316,6 +331,13 @@ export default function AdminSportsSeasonSimulator({ loaderData }: Route.Compone
   const showsInputPolicy =
     config.profile.requiredInputs.includes("sourceElo") || config.profile.requiredInputs.includes("rating");
 
+  // Structured engine knobs: every top-level numeric config key (inputPolicy is a
+  // nested object edited in its own section). Driving the fields from the merged
+  // config means each simulator shows exactly the knobs it actually reads.
+  const engineEntries = Object.entries(config.config)
+    .filter(([key, value]) => key !== "inputPolicy" && typeof value === "number")
+    .map(([key, value]) => [key, value as unknown as number] as [string, number]);
+
   return (
     <div className="container mx-auto p-6 space-y-6">
       <div className="flex items-center gap-4">
@@ -407,130 +429,164 @@ export default function AdminSportsSeasonSimulator({ loaderData }: Route.Compone
         </CardContent>
       </Card>
 
-      {showsInputPolicy && (
-        <Card>
-          <CardHeader>
-            <CardTitle>Input Policy</CardTitle>
-            <CardDescription>
-              Direct inputs win. This simulator can derive Elo from{" "}
-              {sourceEloAlternatives.length > 0 ? sourceEloAlternatives.join(", ") : "no alternate Elo inputs"}
-              {ratingAlternatives.length > 0 ? ` and ratings from ${ratingAlternatives.join(", ")}` : ""}.
-              Tail fallbacks are explicit so low-impact missing participants do not silently get invented ratings.
-            </CardDescription>
-          </CardHeader>
-          <CardContent>
-            <Form method="post" className="grid gap-4 md:grid-cols-5">
-              <input type="hidden" name="intent" value="save-input-policy" />
-              <div className="space-y-2 md:col-span-5">
-                <Label htmlFor="oddsWeight">Futures vs. Elo — Odds Blend Weight (0–1)</Label>
-                <Input id="oddsWeight" name="oddsWeight" type="number" step="0.05" min="0" max="1" defaultValue={inputPolicy.oddsWeight} />
-                <p className="text-xs text-muted-foreground">
-                  Every source (raw Elo, projections, futures odds) becomes an Elo, then they blend into
-                  the single Elo that feeds the simulator. This is the weight given to futures odds:
-                  <strong> 0</strong> = Elo / projections only, <strong>1</strong> = futures fully override,
-                  in between = blend (e.g. 0.3 = 70% Elo / 30% futures).
-                </p>
-              </div>
-              {config.profile.requiredInputs.includes("sourceElo") && (
-                <>
-                  <div className="space-y-2 md:col-span-2">
-                    <Label htmlFor="missingEloStrategy">Missing Elo Strategy</Label>
-                    <select
-                      id="missingEloStrategy"
-                      name="missingEloStrategy"
-                      className="h-9 w-full rounded-md border bg-background px-3 text-sm"
-                      defaultValue={inputPolicy.missingEloStrategy}
-                    >
-                      <option value="block">Block until complete</option>
-                      <option value="fallbackElo">Use fixed fallback Elo</option>
-                      <option value="averageKnown">Use average known Elo</option>
-                      <option value="worstKnownMinus">Use worst known Elo minus delta</option>
-                    </select>
-                  </div>
-                  <div className="space-y-2">
-                    <Label htmlFor="fallbackElo">Fallback Elo</Label>
-                    <Input id="fallbackElo" name="fallbackElo" type="number" defaultValue={inputPolicy.fallbackElo} />
-                  </div>
-                  <div className="space-y-2">
-                    <Label htmlFor="fallbackEloDelta">Worst Elo Delta</Label>
-                    <Input id="fallbackEloDelta" name="fallbackEloDelta" type="number" defaultValue={inputPolicy.fallbackEloDelta} />
-                  </div>
-                  <div className="space-y-2">
-                    <Label htmlFor="eloMin">Elo Floor</Label>
-                    <Input id="eloMin" name="eloMin" type="number" defaultValue={inputPolicy.eloMin} />
-                  </div>
-                  <div className="space-y-2">
-                    <Label htmlFor="eloMax">Elo Ceiling</Label>
-                    <Input id="eloMax" name="eloMax" type="number" defaultValue={inputPolicy.eloMax} />
-                  </div>
-                </>
-              )}
-              {config.profile.requiredInputs.includes("rating") && (
-                <>
-                  <div className="space-y-2 md:col-span-2">
-                    <Label htmlFor="missingRatingStrategy">Missing Rating Strategy</Label>
-                    <select
-                      id="missingRatingStrategy"
-                      name="missingRatingStrategy"
-                      className="h-9 w-full rounded-md border bg-background px-3 text-sm"
-                      defaultValue={inputPolicy.missingRatingStrategy}
-                    >
-                      <option value="block">Block until complete</option>
-                      <option value="fallbackRating">Use fixed fallback rating</option>
-                      <option value="averageKnown">Use average known rating</option>
-                      <option value="worstKnownMinus">Use worst known rating minus delta</option>
-                    </select>
-                  </div>
-                  <div className="space-y-2">
-                    <Label htmlFor="fallbackRating">Fallback Rating</Label>
-                    <Input id="fallbackRating" name="fallbackRating" type="number" step="0.01" defaultValue={inputPolicy.fallbackRating} />
-                  </div>
-                  <div className="space-y-2">
-                    <Label htmlFor="fallbackRatingDelta">Worst Rating Delta</Label>
-                    <Input id="fallbackRatingDelta" name="fallbackRatingDelta" type="number" step="0.01" defaultValue={inputPolicy.fallbackRatingDelta} />
-                  </div>
-                </>
-              )}
-              <div className="space-y-2">
-                <Label htmlFor="ratingMin">Rating Floor</Label>
-                <Input id="ratingMin" name="ratingMin" type="number" step="0.01" defaultValue={inputPolicy.ratingMin} />
-              </div>
-              <div className="space-y-2">
-                <Label htmlFor="ratingMax">Rating Ceiling</Label>
-                <Input id="ratingMax" name="ratingMax" type="number" step="0.01" defaultValue={inputPolicy.ratingMax} />
-              </div>
-              <div className="md:col-span-5">
-                <Button type="submit" disabled={isSubmitting}>
-                  <Save className="mr-2 h-4 w-4" />
-                  Save Input Policy
-                </Button>
-              </div>
-            </Form>
-          </CardContent>
-        </Card>
-      )}
-
       <Card>
         <CardHeader>
-          <CardTitle>Season Config</CardTitle>
+          <CardTitle>Simulator Configuration</CardTitle>
           <CardDescription>
-            JSON overrides for this specific sports season. Defaults come from the simulator profile.
+            One place for this season's settings. <strong>Engine</strong> controls how the Monte Carlo
+            runs; <strong>Input derivation</strong> controls how raw inputs become the single Elo/rating
+            the engine consumes. Defaults come from the simulator profile; values set here override them
+            for this season only. Both sections write the same stored config.
           </CardDescription>
         </CardHeader>
-        <CardContent>
-          <Form method="post" className="space-y-4">
-            <input type="hidden" name="intent" value="save-config" />
-            <Textarea
-              name="config"
-              rows={10}
-              className="font-mono text-sm"
-              defaultValue={JSON.stringify(config.config, null, 2)}
-            />
+        <CardContent className="space-y-6">
+          <Form method="post" className="space-y-6">
+            <input type="hidden" name="intent" value="save-configuration" />
+            {showsInputPolicy && <input type="hidden" name="hasInputPolicy" value="1" />}
+
+            <section className="space-y-3">
+              <div>
+                <h3 className="text-sm font-semibold">Engine</h3>
+                <p className="text-xs text-muted-foreground">
+                  How the simulation runs. A higher <code>parityFactor</code> flattens the finish-position
+                  distribution (favorites win less often); <code>iterations</code> trades speed for precision.
+                </p>
+              </div>
+              {engineEntries.length > 0 ? (
+                <div className="grid gap-4 md:grid-cols-3">
+                  {engineEntries.map(([key, value]) => (
+                    <div key={key} className="space-y-2">
+                      <Label htmlFor={`engine.${key}`} className="font-mono text-xs">{key}</Label>
+                      <Input id={`engine.${key}`} name={`engine.${key}`} type="number" step="any" defaultValue={value} />
+                    </div>
+                  ))}
+                </div>
+              ) : (
+                <p className="text-xs text-muted-foreground">This simulator exposes no numeric engine knobs.</p>
+              )}
+            </section>
+
+            {showsInputPolicy && (
+              <section className="space-y-3">
+                <div>
+                  <h3 className="text-sm font-semibold">Input derivation</h3>
+                  <p className="text-xs text-muted-foreground">
+                    Direct inputs win. This simulator can derive Elo from{" "}
+                    {sourceEloAlternatives.length > 0 ? sourceEloAlternatives.join(", ") : "no alternate Elo inputs"}
+                    {ratingAlternatives.length > 0 ? ` and ratings from ${ratingAlternatives.join(", ")}` : ""}.
+                    Tail fallbacks are explicit so low-impact missing participants do not silently get invented ratings.
+                  </p>
+                </div>
+                <div className="grid gap-4 md:grid-cols-5">
+                  <div className="space-y-2 md:col-span-5">
+                    <Label htmlFor="oddsWeight">Futures vs. Elo — Odds Blend Weight (0–1)</Label>
+                    <Input id="oddsWeight" name="oddsWeight" type="number" step="0.05" min="0" max="1" defaultValue={inputPolicy.oddsWeight} />
+                    <p className="text-xs text-muted-foreground">
+                      Every source (raw Elo, projections, futures odds) becomes an Elo, then they blend into
+                      the single Elo that feeds the simulator. This is the weight given to futures odds:
+                      <strong> 0</strong> = Elo / projections only, <strong>1</strong> = futures fully override,
+                      in between = blend (e.g. 0.3 = 70% Elo / 30% futures). Odds enter the engine only through
+                      this Elo — they are not blended again per game.
+                    </p>
+                  </div>
+                  {config.profile.requiredInputs.includes("sourceElo") && (
+                    <>
+                      <div className="space-y-2 md:col-span-2">
+                        <Label htmlFor="missingEloStrategy">Missing Elo Strategy</Label>
+                        <select
+                          id="missingEloStrategy"
+                          name="missingEloStrategy"
+                          className="h-9 w-full rounded-md border bg-background px-3 text-sm"
+                          defaultValue={inputPolicy.missingEloStrategy}
+                        >
+                          <option value="block">Block until complete</option>
+                          <option value="fallbackElo">Use fixed fallback Elo</option>
+                          <option value="averageKnown">Use average known Elo</option>
+                          <option value="worstKnownMinus">Use worst known Elo minus delta</option>
+                        </select>
+                      </div>
+                      <div className="space-y-2">
+                        <Label htmlFor="fallbackElo">Fallback Elo</Label>
+                        <Input id="fallbackElo" name="fallbackElo" type="number" defaultValue={inputPolicy.fallbackElo} />
+                      </div>
+                      <div className="space-y-2">
+                        <Label htmlFor="fallbackEloDelta">Worst Elo Delta</Label>
+                        <Input id="fallbackEloDelta" name="fallbackEloDelta" type="number" defaultValue={inputPolicy.fallbackEloDelta} />
+                      </div>
+                      <div className="space-y-2">
+                        <Label htmlFor="eloMin">Elo Floor</Label>
+                        <Input id="eloMin" name="eloMin" type="number" defaultValue={inputPolicy.eloMin} />
+                      </div>
+                      <div className="space-y-2">
+                        <Label htmlFor="eloMax">Elo Ceiling</Label>
+                        <Input id="eloMax" name="eloMax" type="number" defaultValue={inputPolicy.eloMax} />
+                      </div>
+                    </>
+                  )}
+                  {config.profile.requiredInputs.includes("rating") && (
+                    <>
+                      <div className="space-y-2 md:col-span-2">
+                        <Label htmlFor="missingRatingStrategy">Missing Rating Strategy</Label>
+                        <select
+                          id="missingRatingStrategy"
+                          name="missingRatingStrategy"
+                          className="h-9 w-full rounded-md border bg-background px-3 text-sm"
+                          defaultValue={inputPolicy.missingRatingStrategy}
+                        >
+                          <option value="block">Block until complete</option>
+                          <option value="fallbackRating">Use fixed fallback rating</option>
+                          <option value="averageKnown">Use average known rating</option>
+                          <option value="worstKnownMinus">Use worst known rating minus delta</option>
+                        </select>
+                      </div>
+                      <div className="space-y-2">
+                        <Label htmlFor="fallbackRating">Fallback Rating</Label>
+                        <Input id="fallbackRating" name="fallbackRating" type="number" step="0.01" defaultValue={inputPolicy.fallbackRating} />
+                      </div>
+                      <div className="space-y-2">
+                        <Label htmlFor="fallbackRatingDelta">Worst Rating Delta</Label>
+                        <Input id="fallbackRatingDelta" name="fallbackRatingDelta" type="number" step="0.01" defaultValue={inputPolicy.fallbackRatingDelta} />
+                      </div>
+                    </>
+                  )}
+                  <div className="space-y-2">
+                    <Label htmlFor="ratingMin">Rating Floor</Label>
+                    <Input id="ratingMin" name="ratingMin" type="number" step="0.01" defaultValue={inputPolicy.ratingMin} />
+                  </div>
+                  <div className="space-y-2">
+                    <Label htmlFor="ratingMax">Rating Ceiling</Label>
+                    <Input id="ratingMax" name="ratingMax" type="number" step="0.01" defaultValue={inputPolicy.ratingMax} />
+                  </div>
+                </div>
+              </section>
+            )}
+
             <Button type="submit" disabled={isSubmitting}>
               <Save className="mr-2 h-4 w-4" />
-              Save Config
+              Save Configuration
             </Button>
           </Form>
+
+          <details>
+            <summary className="cursor-pointer text-sm font-medium">Advanced: edit raw config JSON</summary>
+            <Form method="post" className="space-y-3 mt-3">
+              <input type="hidden" name="intent" value="save-config" />
+              <Textarea
+                name="config"
+                rows={10}
+                className="font-mono text-sm"
+                defaultValue={JSON.stringify(config.config, null, 2)}
+              />
+              <p className="text-xs text-muted-foreground">
+                Power-user escape hatch for keys not shown above. This is the same stored config the fields
+                edit; saving here writes the whole object.
+              </p>
+              <Button type="submit" variant="outline" disabled={isSubmitting}>
+                <Save className="mr-2 h-4 w-4" />
+                Save Raw JSON
+              </Button>
+            </Form>
+          </details>
         </CardContent>
       </Card>
 
diff --git a/app/services/simulations/__tests__/nhl-simulator.test.ts b/app/services/simulations/__tests__/nhl-simulator.test.ts
index 9e819cf..eecb967 100644
--- a/app/services/simulations/__tests__/nhl-simulator.test.ts
+++ b/app/services/simulations/__tests__/nhl-simulator.test.ts
@@ -119,6 +119,13 @@ describe("eloWinProbability (PARITY_FACTOR = 1000)", () => {
     const p = eloWinProbability(1700, 1500);
     expect(p).toBeCloseTo(0.613, 2);
   });
+
+  it("a higher parity factor flattens the per-game win probability toward 0.5", () => {
+    const standard = eloWinProbability(1700, 1500);        // default parity 1000
+    const flatter = eloWinProbability(1700, 1500, 2500);   // season config override
+    expect(flatter).toBeLessThan(standard);
+    expect(flatter).toBeGreaterThan(0.5);
+  });
 });
 
 // ─── simulateProjectedPoints ──────────────────────────────────────────────────
diff --git a/app/services/simulations/afl-simulator.ts b/app/services/simulations/afl-simulator.ts
index b041bcf..195d394 100644
--- a/app/services/simulations/afl-simulator.ts
+++ b/app/services/simulations/afl-simulator.ts
@@ -69,20 +69,22 @@ import { normalizeTeamName } from "~/lib/normalize-team-name";
 import { logger } from "~/lib/logger";
 import { getRegularSeasonStandings } from "~/models/regular-season-standings";
 import { eloWinProbabilityWithParity } from "~/services/probability-engine";
+import { positiveConfigNumber } from "./config-access";
 
-// ─── Simulation parameters ────────────────────────────────────────────────────
+// ─── Simulation parameters (defaults; overridable via season config) ───────────
 
-const NUM_SIMULATIONS = 10_000;
+const DEFAULT_NUM_SIMULATIONS = 10_000;
 
 /**
  * Elo parity factor for AFL single-game win probability.
  * 450 reflects moderate variance — lower than NHL (1000) to account for
  * AFL's relatively predictable results vs. basketball's coin-flip tendencies.
+ * Overridable via the season config's `parityFactor`.
  */
-const PARITY_FACTOR = 450;
+const DEFAULT_PARITY_FACTOR = 450;
 
 /** Approximate total regular season games per AFL team (2026 season). */
-const AFL_REGULAR_SEASON_GAMES = 23;
+const DEFAULT_REGULAR_SEASON_GAMES = 23;
 
 /** Average opponent Elo used for regular season projections. */
 const AVERAGE_OPPONENT_ELO = 1500;
@@ -161,8 +163,8 @@ export function getTeamData(name: string): AflTeamData | undefined {
  *   P(A) = 1 / (1 + 10^((eloB - eloA) / PARITY_FACTOR))
  * Exported for unit testing.
  */
-export function eloWinProbability(eloA: number, eloB: number): number {
-  return eloWinProbabilityWithParity(eloA, eloB, PARITY_FACTOR);
+export function eloWinProbability(eloA: number, eloB: number, parityFactor = DEFAULT_PARITY_FACTOR): number {
+  return eloWinProbabilityWithParity(eloA, eloB, parityFactor);
 }
 
 // ─── Internal types ───────────────────────────────────────────────────────────
@@ -193,8 +195,11 @@ function simulateProjectedWins(entry: TeamEntry): number {
 // ─── Simulator ────────────────────────────────────────────────────────────────
 
 export class AFLSimulator implements Simulator {
-  async simulate(sportsSeasonId: string): Promise<SimulationResult[]> {
+  async simulate(sportsSeasonId: string, config: Record<string, unknown> = {}): Promise<SimulationResult[]> {
     const db = database();
+    const parityFactor = positiveConfigNumber(config, "parityFactor", DEFAULT_PARITY_FACTOR);
+    const numSimulations = Math.round(positiveConfigNumber(config, "iterations", DEFAULT_NUM_SIMULATIONS));
+    const seasonGames = Math.round(positiveConfigNumber(config, "seasonGames", DEFAULT_REGULAR_SEASON_GAMES));
 
     // 1. Load participants, DB Elo, and standings in parallel.
     const [participantRows, evRows, standings] = await Promise.all([
@@ -260,8 +265,8 @@ export class AFLSimulator implements Simulator {
         name: r.name,
         elo: resolvedElo,
         currentWins: standing?.wins ?? 0,
-        remainingGames: Math.max(0, AFL_REGULAR_SEASON_GAMES - gamesPlayed),
-        winProb: eloWinProbability(resolvedElo, AVERAGE_OPPONENT_ELO),
+        remainingGames: Math.max(0, seasonGames - gamesPlayed),
+        winProb: eloWinProbability(resolvedElo, AVERAGE_OPPONENT_ELO, parityFactor),
       };
     });
 
@@ -269,7 +274,7 @@ export class AFLSimulator implements Simulator {
 
     /** Simulate a single AFL game. Returns the winner. */
     const simGame = (a: TeamEntry, b: TeamEntry): TeamEntry =>
-      Math.random() < eloWinProbability(a.elo, b.elo) ? a : b;
+      Math.random() < eloWinProbability(a.elo, b.elo, parityFactor) ? a : b;
 
     /**
      * Project end-of-season ladder and return the top 10 finalists seeded 1–10.
@@ -364,7 +369,7 @@ export class AFLSimulator implements Simulator {
     const efLoserCounts   = new Map<string, number>(participantIds.map((id) => [id, 0]));
 
     // 4. Monte Carlo simulation loop.
-    for (let s = 0; s < NUM_SIMULATIONS; s++) {
+    for (let s = 0; s < numSimulations; s++) {
       const finalists = buildFinalsList();
       const { gfWinner, gfLoser, pfLosers, sfLosers, efLosers } = simAFLFinals(finalists);
 
@@ -393,7 +398,7 @@ export class AFLSimulator implements Simulator {
     //
     //    Within each pair (3rd/4th, 5th/6th, 7th/8th), both positions receive the
     //    same probability — matching the AFL_10 bracket's averaged point values.
-    const N = NUM_SIMULATIONS;
+    const N = numSimulations;
     const results: SimulationResult[] = participantIds.map((participantId) => {
       const c  = championCounts.get(participantId) ?? 0;
       const f  = finalistCounts.get(participantId) ?? 0;
diff --git a/app/services/simulations/auto-racing-simulator.ts b/app/services/simulations/auto-racing-simulator.ts
index dc8933e..1e5e838 100644
--- a/app/services/simulations/auto-racing-simulator.ts
+++ b/app/services/simulations/auto-racing-simulator.ts
@@ -26,10 +26,11 @@ import * as schema from "~/database/schema";
 import { getAllParticipantEVsForSeason } from "~/models/participant-expected-value";
 import { getSeasonResults } from "~/models/participant-season-result";
 import type { Simulator, SimulationResult } from "./types";
+import { positiveConfigNumber } from "./config-access";
 
 // ─── Simulation parameters (mirrors Python constants) ────────────────────────
 
-const NUM_SIMULATIONS = 10000;
+const DEFAULT_NUM_SIMULATIONS = 10000;
 
 /** Per-race performance variance. 0 = no noise, 1 = fully random each race. */
 const RACE_NOISE = 0.50;
@@ -107,7 +108,8 @@ export class AutoRacingSimulator implements Simulator {
     private readonly source: string,
   ) {}
 
-  async simulate(sportsSeasonId: string): Promise<SimulationResult[]> {
+  async simulate(sportsSeasonId: string, config: Record<string, unknown> = {}): Promise<SimulationResult[]> {
+    const numSimulations = Math.round(positiveConfigNumber(config, "iterations", DEFAULT_NUM_SIMULATIONS));
     const db = database();
 
     // 1. Load all participants for this sports season
@@ -186,7 +188,7 @@ export class AutoRacingSimulator implements Simulator {
       // Pre-season: no races to simulate, derive placement probabilities
       // from sourceOdds via pure weighted draws.
       const weights = ids.map((id) => baseProbs.get(id) ?? fallbackProb);
-      for (let sim = 0; sim < NUM_SIMULATIONS; sim++) {
+      for (let sim = 0; sim < numSimulations; sim++) {
         const finishOrder = weightedDrawWithoutReplacement(ids, weights);
         for (let rank = 0; rank < Math.min(8, finishOrder.length); rank++) {
           const counts = rankCounts.get(finishOrder[rank]);
@@ -225,7 +227,7 @@ export class AutoRacingSimulator implements Simulator {
       // Volatility shrinks as the season progresses — late-season standings are
       // much more predictive than early-season odds.
       const effectiveVolatility = PARTICIPANT_VOLATILITY * (1 - seasonProgress * VOLATILITY_DECAY_FACTOR);
-      for (let sim = 0; sim < NUM_SIMULATIONS; sim++) {
+      for (let sim = 0; sim < numSimulations; sim++) {
         // 7a. Season-long performance multiplier per driver (uses blended strength)
         const seasonWeights = new Map<string, number>();
         for (const id of ids) {
@@ -277,14 +279,14 @@ export class AutoRacingSimulator implements Simulator {
       return {
         participantId: p.id,
         probabilities: {
-          probFirst:   counts[0] / NUM_SIMULATIONS,
-          probSecond:  counts[1] / NUM_SIMULATIONS,
-          probThird:   counts[2] / NUM_SIMULATIONS,
-          probFourth:  counts[3] / NUM_SIMULATIONS,
-          probFifth:   counts[4] / NUM_SIMULATIONS,
-          probSixth:   counts[5] / NUM_SIMULATIONS,
-          probSeventh: counts[6] / NUM_SIMULATIONS,
-          probEighth:  counts[7] / NUM_SIMULATIONS,
+          probFirst:   counts[0] / numSimulations,
+          probSecond:  counts[1] / numSimulations,
+          probThird:   counts[2] / numSimulations,
+          probFourth:  counts[3] / numSimulations,
+          probFifth:   counts[4] / numSimulations,
+          probSixth:   counts[5] / numSimulations,
+          probSeventh: counts[6] / numSimulations,
+          probEighth:  counts[7] / numSimulations,
         },
         source: this.source,
       };
diff --git a/app/services/simulations/college-hockey-simulator.ts b/app/services/simulations/college-hockey-simulator.ts
index 0dd4553..9c3b2b7 100644
--- a/app/services/simulations/college-hockey-simulator.ts
+++ b/app/services/simulations/college-hockey-simulator.ts
@@ -22,8 +22,9 @@ import {
   eloWinProbabilityWithParity,
 } from "~/services/probability-engine";
 import type { Simulator, SimulationResult } from "./types";
+import { positiveConfigNumber } from "./config-access";
 
-const NUM_SIMULATIONS = 50_000;
+const DEFAULT_NUM_SIMULATIONS = 50_000;
 const BRACKET_SIZE = 16;
 const HOCKEY_PARITY_FACTOR = 850;
 const DEFAULT_ELO = 1500;
@@ -156,8 +157,8 @@ export function buildCollegeHockeyTeams(
   return teams;
 }
 
-function simGame(team1: Team, team2: Team): { winner: Team; loser: Team } {
-  const p1Wins = Math.random() < eloWinProbabilityWithParity(team1.elo, team2.elo, HOCKEY_PARITY_FACTOR);
+function simGame(team1: Team, team2: Team, parityFactor = HOCKEY_PARITY_FACTOR): { winner: Team; loser: Team } {
+  const p1Wins = Math.random() < eloWinProbabilityWithParity(team1.elo, team2.elo, parityFactor);
   return p1Wins ? { winner: team1, loser: team2 } : { winner: team2, loser: team1 };
 }
 
@@ -189,26 +190,27 @@ function seedField(teams: Team[]): Team[] {
   return [...teams].toSorted((a, b) => b.seedScore - a.seedScore || b.elo - a.elo);
 }
 
-function simulateSeeded16TeamBracket(teams: Team[], counts: Map<string, PlacementCounts>): void {
+function simulateSeeded16TeamBracket(teams: Team[], counts: Map<string, PlacementCounts>, parityFactor = HOCKEY_PARITY_FACTOR): void {
   const r16Pairs: Array<[number, number]> = [
     [0, 15], [7, 8], [4, 11], [3, 12], [5, 10], [2, 13], [6, 9], [1, 14],
   ];
+  const game = (a: Team, b: Team) => simGame(a, b, parityFactor);
 
-  const r16Winners = r16Pairs.map(([a, b]) => simGame(teams[a], teams[b]).winner);
+  const r16Winners = r16Pairs.map(([a, b]) => game(teams[a], teams[b]).winner);
 
   const qfWinners: Team[] = [];
   for (let i = 0; i < 4; i++) {
-    const result = simGame(r16Winners[i * 2], r16Winners[i * 2 + 1]);
+    const result = game(r16Winners[i * 2], r16Winners[i * 2 + 1]);
     qfWinners.push(result.winner);
     bump(counts, result.loser.participantId, "quarterfinalLoser");
   }
 
-  const sf1 = simGame(qfWinners[0], qfWinners[1]);
-  const sf2 = simGame(qfWinners[2], qfWinners[3]);
+  const sf1 = game(qfWinners[0], qfWinners[1]);
+  const sf2 = game(qfWinners[2], qfWinners[3]);
   bump(counts, sf1.loser.participantId, "semifinalLoser");
   bump(counts, sf2.loser.participantId, "semifinalLoser");
 
-  const final = simGame(sf1.winner, sf2.winner);
+  const final = game(sf1.winner, sf2.winner);
   bump(counts, final.winner.participantId, "champion");
   bump(counts, final.loser.participantId, "finalist");
 }
@@ -236,19 +238,21 @@ function simulateMatchFromIds(
   p1: string,
   p2: string,
   match: PlayoffMatch | undefined,
-  teamById: Map<string, Team>
+  teamById: Map<string, Team>,
+  parityFactor = HOCKEY_PARITY_FACTOR
 ): { winner: Team; loser: Team } {
   if (match?.isComplete && match.winnerId) {
     const loserId = completedLoser(match);
     return { winner: getTeam(teamById, match.winnerId), loser: getTeam(teamById, loserId) };
   }
-  return simGame(getTeam(teamById, p1), getTeam(teamById, p2));
+  return simGame(getTeam(teamById, p1), getTeam(teamById, p2), parityFactor);
 }
 
 function simulateExistingBracket(
   rounds: { r16: PlayoffMatch[]; qf: PlayoffMatch[]; sf: PlayoffMatch[]; final: PlayoffMatch },
   teamById: Map<string, Team>,
-  counts: Map<string, PlacementCounts>
+  counts: Map<string, PlacementCounts>,
+  parityFactor = HOCKEY_PARITY_FACTOR
 ): void {
   const r16Winners: Team[] = [];
   for (let i = 0; i < 8; i++) {
@@ -256,7 +260,7 @@ function simulateExistingBracket(
     if (!match.participant1Id || !match.participant2Id) {
       throw new Error(`${match.round} match ${match.matchNumber} is missing participants.`);
     }
-    r16Winners.push(simulateMatchFromIds(match.participant1Id, match.participant2Id, match, teamById).winner);
+    r16Winners.push(simulateMatchFromIds(match.participant1Id, match.participant2Id, match, teamById, parityFactor).winner);
   }
 
   const qfWinners: Team[] = [];
@@ -265,7 +269,7 @@ function simulateExistingBracket(
     const p1 = r16Winners[i * 2]?.participantId;
     const p2 = r16Winners[i * 2 + 1]?.participantId;
     if (!p1 || !p2) throw new Error(`${match.round} match ${match.matchNumber} cannot resolve participants.`);
-    const result = simulateMatchFromIds(p1, p2, match, teamById);
+    const result = simulateMatchFromIds(p1, p2, match, teamById, parityFactor);
     qfWinners.push(result.winner);
     bump(counts, result.loser.participantId, "quarterfinalLoser");
   }
@@ -276,7 +280,7 @@ function simulateExistingBracket(
     const p1 = qfWinners[i * 2]?.participantId;
     const p2 = qfWinners[i * 2 + 1]?.participantId;
     if (!p1 || !p2) throw new Error(`${match.round} match ${match.matchNumber} cannot resolve participants.`);
-    const result = simulateMatchFromIds(p1, p2, match, teamById);
+    const result = simulateMatchFromIds(p1, p2, match, teamById, parityFactor);
     sfWinners.push(result.winner);
     bump(counts, result.loser.participantId, "semifinalLoser");
   }
@@ -284,21 +288,21 @@ function simulateExistingBracket(
   const p1 = sfWinners[0]?.participantId;
   const p2 = sfWinners[1]?.participantId;
   if (!p1 || !p2) throw new Error(`${rounds.final.round} match ${rounds.final.matchNumber} cannot resolve participants.`);
-  const final = simulateMatchFromIds(p1, p2, rounds.final, teamById);
+  const final = simulateMatchFromIds(p1, p2, rounds.final, teamById, parityFactor);
   bump(counts, final.winner.participantId, "champion");
   bump(counts, final.loser.participantId, "finalist");
 }
 
-function toResults(participantIds: string[], counts: Map<string, PlacementCounts>): SimulationResult[] {
+function toResults(participantIds: string[], counts: Map<string, PlacementCounts>, numSimulations: number): SimulationResult[] {
   const results = participantIds.map((participantId) => {
     const c = counts.get(participantId) ?? { champion: 0, finalist: 0, semifinalLoser: 0, quarterfinalLoser: 0 };
-    const sf = c.semifinalLoser / (2 * NUM_SIMULATIONS);
-    const qf = c.quarterfinalLoser / (4 * NUM_SIMULATIONS);
+    const sf = c.semifinalLoser / (2 * numSimulations);
+    const qf = c.quarterfinalLoser / (4 * numSimulations);
     return {
       participantId,
       probabilities: {
-        probFirst: c.champion / NUM_SIMULATIONS,
-        probSecond: c.finalist / NUM_SIMULATIONS,
+        probFirst: c.champion / numSimulations,
+        probSecond: c.finalist / numSimulations,
         probThird: sf,
         probFourth: sf,
         probFifth: qf,
@@ -325,8 +329,10 @@ function toResults(participantIds: string[], counts: Map<string, PlacementCounts
 }
 
 export class CollegeHockeySimulator implements Simulator {
-  async simulate(sportsSeasonId: string): Promise<SimulationResult[]> {
+  async simulate(sportsSeasonId: string, config: Record<string, unknown> = {}): Promise<SimulationResult[]> {
     const db = database();
+    const parityFactor = positiveConfigNumber(config, "parityFactor", HOCKEY_PARITY_FACTOR);
+    const numSimulations = Math.round(positiveConfigNumber(config, "iterations", DEFAULT_NUM_SIMULATIONS));
 
     const bracketEvent = await db.query.scoringEvents.findFirst({
       where: and(
@@ -373,19 +379,19 @@ export class CollegeHockeySimulator implements Simulator {
     );
 
     if (existingBracket) {
-      for (let i = 0; i < NUM_SIMULATIONS; i++) {
-        simulateExistingBracket(existingBracket, teamById, counts);
+      for (let i = 0; i < numSimulations; i++) {
+        simulateExistingBracket(existingBracket, teamById, counts, parityFactor);
       }
     } else {
       const preBracketMode = participantIds.length > BRACKET_SIZE;
       const deterministicField = preBracketMode ? null : seedField(teams);
-      for (let i = 0; i < NUM_SIMULATIONS; i++) {
+      for (let i = 0; i < numSimulations; i++) {
         const field = preBracketMode ? sampleField(teams, BRACKET_SIZE) : deterministicField ?? [];
-        simulateSeeded16TeamBracket(field, counts);
+        simulateSeeded16TeamBracket(field, counts, parityFactor);
       }
     }
 
-    return toResults(participantIds, counts);
+    return toResults(participantIds, counts, numSimulations);
   }
 
   private getExistingBracketRounds(matches: PlayoffMatch[]): { r16: PlayoffMatch[]; qf: PlayoffMatch[]; sf: PlayoffMatch[]; final: PlayoffMatch } | null {
diff --git a/app/services/simulations/config-access.ts b/app/services/simulations/config-access.ts
new file mode 100644
index 0000000..51c6e7a
--- /dev/null
+++ b/app/services/simulations/config-access.ts
@@ -0,0 +1,43 @@
+/**
+ * Shared accessors for reading numeric knobs out of a merged simulator config
+ * (`sports_season_simulator_configs.config` merged over the profile defaults).
+ *
+ * These were previously duplicated inside individual simulators (EPL, MLS,
+ * NCAA-M). Centralizing them keeps every simulator reading engine knobs the same
+ * way, so values set in the unified config screen reliably drive the math.
+ *
+ * Two zero-handling variants exist deliberately:
+ *   - `configNumber`         accepts 0 (`>= 0`) — for knobs where 0 is meaningful
+ *                            (e.g. a draw decay or blend weight of 0).
+ *   - `positiveConfigNumber` requires `> 0` — for counts/divisors where 0 is
+ *                            nonsensical and should fall back to the default.
+ */
+
+type Config = Record<string, unknown> | undefined;
+
+/** Read a finite, non-negative number from config, else the fallback. */
+export function configNumber(config: Config, key: string, fallback: number): number {
+  const value = config?.[key];
+  return typeof value === "number" && Number.isFinite(value) && value >= 0 ? value : fallback;
+}
+
+/** Read a finite, strictly-positive number from config, else the fallback. */
+export function positiveConfigNumber(config: Config, key: string, fallback: number): number {
+  const value = config?.[key];
+  return typeof value === "number" && Number.isFinite(value) && value > 0 ? value : fallback;
+}
+
+/**
+ * Read a required finite, strictly-positive number from config. Throws when the
+ * key is missing or non-positive — use only for knobs a profile always seeds.
+ */
+export function requiredConfigNumber(config: Config, key: string, label = "simulator"): number {
+  const value = config?.[key];
+  if (typeof value === "number" && Number.isFinite(value) && value > 0) return value;
+  throw new Error(`${label} config is missing positive numeric ${key}.`);
+}
+
+/** Coerce a raw value (already extracted from config) to a positive number. */
+export function optionalPositiveNumber(value: unknown, fallback: number): number {
+  return typeof value === "number" && Number.isFinite(value) && value > 0 ? value : fallback;
+}
diff --git a/app/services/simulations/cs-major-simulator.ts b/app/services/simulations/cs-major-simulator.ts
index 861c704..4217bae 100644
--- a/app/services/simulations/cs-major-simulator.ts
+++ b/app/services/simulations/cs-major-simulator.ts
@@ -59,10 +59,11 @@ import {
   type StructureSource,
 } from "./shared-major";
 import type { Simulator, SimulationResult } from "./types";
+import { positiveConfigNumber } from "./config-access";
 
 // ─── Simulation parameters ────────────────────────────────────────────────────
 
-const NUM_SIMULATIONS = 10_000;
+const DEFAULT_NUM_SIMULATIONS = 10_000;
 
 /** Total field size per CS2 Major. */
 const FIELD_SIZE = 32;
@@ -545,7 +546,8 @@ export function simulateChampionsStage(
 // ─── Simulator ────────────────────────────────────────────────────────────────
 
 export class CSMajorSimulator implements Simulator {
-  async simulate(sportsSeasonId: string): Promise<SimulationResult[]> {
+  async simulate(sportsSeasonId: string, config: Record<string, unknown> = {}): Promise<SimulationResult[]> {
+    const numSimulations = Math.round(positiveConfigNumber(config, "iterations", DEFAULT_NUM_SIMULATIONS));
     const db = database();
 
     // 1. Load all participants for this sports season.
@@ -800,7 +802,7 @@ export class CSMajorSimulator implements Simulator {
     const counts: number[][] = Array.from({ length: participantIds.length }, () => Array(8).fill(0));
     const idToIndex = new Map<string, number>(participantIds.map((id, i) => [id, i]));
 
-    for (let sim = 0; sim < NUM_SIMULATIONS; sim++) {
+    for (let sim = 0; sim < numSimulations; sim++) {
       const simQP = new Map<string, number>(actualQPMap);
 
       for (const event of incompleteEvents) {
@@ -831,14 +833,14 @@ export class CSMajorSimulator implements Simulator {
     return participantIds.map((participantId, i) => ({
       participantId,
       probabilities: {
-        probFirst:   counts[i][0] / NUM_SIMULATIONS,
-        probSecond:  counts[i][1] / NUM_SIMULATIONS,
-        probThird:   counts[i][2] / NUM_SIMULATIONS,
-        probFourth:  counts[i][3] / NUM_SIMULATIONS,
-        probFifth:   counts[i][4] / NUM_SIMULATIONS,
-        probSixth:   counts[i][5] / NUM_SIMULATIONS,
-        probSeventh: counts[i][6] / NUM_SIMULATIONS,
-        probEighth:  counts[i][7] / NUM_SIMULATIONS,
+        probFirst:   counts[i][0] / numSimulations,
+        probSecond:  counts[i][1] / numSimulations,
+        probThird:   counts[i][2] / numSimulations,
+        probFourth:  counts[i][3] / numSimulations,
+        probFifth:   counts[i][4] / numSimulations,
+        probSixth:   counts[i][5] / numSimulations,
+        probSeventh: counts[i][6] / numSimulations,
+        probEighth:  counts[i][7] / numSimulations,
       },
       source: "cs2_major_qualifying_points_monte_carlo",
     }));
diff --git a/app/services/simulations/darts-simulator.ts b/app/services/simulations/darts-simulator.ts
index 1671259..cbd7d36 100644
--- a/app/services/simulations/darts-simulator.ts
+++ b/app/services/simulations/darts-simulator.ts
@@ -48,6 +48,7 @@ import { database } from "~/database/context";
 import { eq, and } from "drizzle-orm";
 import * as schema from "~/database/schema";
 import type { Simulator, SimulationResult } from "./types";
+import { positiveConfigNumber } from "./config-access";
 
 // ─── Simulation parameters ────────────────────────────────────────────────────
 
@@ -204,8 +205,9 @@ export class DartsSimulator implements Simulator {
     this.numSimulations = numSimulations;
   }
 
-  async simulate(sportsSeasonId: string): Promise<SimulationResult[]> {
+  async simulate(sportsSeasonId: string, config: Record<string, unknown> = {}): Promise<SimulationResult[]> {
     const db = database();
+    const numSimulations = Math.round(positiveConfigNumber(config, "iterations", this.numSimulations));
 
     // 1. Find the bracket scoring event (if it exists).
     const bracketEvent = await db.query.scoringEvents.findFirst({
@@ -248,9 +250,9 @@ export class DartsSimulator implements Simulator {
     const bracketPopulated = allMatches.some((m) => m.participant1Id && m.participant2Id);
 
     if (bracketPopulated) {
-      return this.simulateBracket(allMatches, eloMap);
+      return this.simulateBracket(allMatches, eloMap, numSimulations);
     } else {
-      return this.simulatePreBracket(sportsSeasonId, eloMap, rankingMap, db);
+      return this.simulatePreBracket(sportsSeasonId, eloMap, rankingMap, db, numSimulations);
     }
   }
 
@@ -258,7 +260,8 @@ export class DartsSimulator implements Simulator {
 
   private async simulateBracket(
     allMatches: Awaited<ReturnType<ReturnType<typeof database>["query"]["playoffMatches"]["findMany"]>>,
-    eloMap: Map<string, number>
+    eloMap: Map<string, number>,
+    numSimulations: number
   ): Promise<SimulationResult[]> {
     // Group matches by round, sorted by match count descending (R1 first = most matches).
     const byRound = new Map<string, typeof allMatches>();
@@ -331,7 +334,7 @@ export class DartsSimulator implements Simulator {
     const sfLoserCounts   = new Map<string, number>(participantIds.map((id) => [id, 0]));
     const qfLoserCounts   = new Map<string, number>(participantIds.map((id) => [id, 0]));
 
-    for (let s = 0; s < this.numSimulations; s++) {
+    for (let s = 0; s < numSimulations; s++) {
       // R1 (64 matches)
       const r1Winners: string[] = [];
       for (let i = 1; i <= 64; i++) {
@@ -439,7 +442,7 @@ export class DartsSimulator implements Simulator {
       finalistCounts.set(finalist, (finalistCounts.get(finalist) ?? 0) + 1);
     }
 
-    return buildResults(participantIds, this.numSimulations, {
+    return buildResults(participantIds, numSimulations, {
       championCounts,
       finalistCounts,
       sfLoserCounts,
@@ -455,7 +458,8 @@ export class DartsSimulator implements Simulator {
     sportsSeasonId: string,
     eloMap: Map<string, number>,
     rankingMap: Map<string, number>,
-    db: ReturnType<typeof database>
+    db: ReturnType<typeof database>,
+    numSimulations: number
   ): Promise<SimulationResult[]> {
     const allParticipants = await db
       .select({ id: schema.seasonParticipants.id, name: schema.seasonParticipants.name })
@@ -520,7 +524,7 @@ export class DartsSimulator implements Simulator {
       unseededPool.push(`__bye_${unseededPool.length}`);
     }
 
-    for (let s = 0; s < this.numSimulations; s++) {
+    for (let s = 0; s < numSimulations; s++) {
       // Draw: shuffle the unseeded pool — seeded positions are pre-computed.
       const drawnUnseeded = shuffle([...unseededPool]);
 
@@ -588,7 +592,7 @@ export class DartsSimulator implements Simulator {
       finalistCounts.set(finalist, (finalistCounts.get(finalist) ?? 0) + 1);
     }
 
-    return buildResults(allParticipantIds, this.numSimulations, {
+    return buildResults(allParticipantIds, numSimulations, {
       championCounts,
       finalistCounts,
       sfLoserCounts,
diff --git a/app/services/simulations/epl-simulator.ts b/app/services/simulations/epl-simulator.ts
index b0f08d8..d39684d 100644
--- a/app/services/simulations/epl-simulator.ts
+++ b/app/services/simulations/epl-simulator.ts
@@ -18,6 +18,7 @@ import { convertFuturesToElo, eloWinProbabilityWithParity } from "~/services/pro
 import { normalizeSimulationResultColumns } from "./simulation-probabilities";
 import { simulateEloSoccerMatch, simulateSimpleSoccerGoals } from "./soccer-helpers";
 import { getSportsSeasonSimulatorConfig } from "~/models/simulator";
+import { positiveConfigNumber, requiredConfigNumber } from "./config-access";
 
 const DEFAULT_NUM_SIMULATIONS = 10_000;
 const DEFAULT_EPL_REGULAR_SEASON_GAMES = 38;
@@ -44,17 +45,6 @@ interface SimulatedTableRow {
   tiebreaker: number;
 }
 
-function configNumber(config: Record<string, unknown> | undefined, key: string, fallback: number): number {
-  const value = config?.[key];
-  return typeof value === "number" && Number.isFinite(value) && value > 0 ? value : fallback;
-}
-
-function requiredConfigNumber(config: Record<string, unknown> | undefined, key: string): number {
-  const value = config?.[key];
-  if (typeof value === "number" && Number.isFinite(value) && value > 0) return value;
-  throw new Error(`EPL simulator config is missing positive numeric ${key}.`);
-}
-
 /** EPL single-match win probability using the sport-specific parity factor. */
 export function eplWinProbability(
   eloA: number,
@@ -99,13 +89,13 @@ export class EPLSimulator implements Simulator {
     ]);
 
     const config = simulatorConfig?.config;
-    const numSimulations = Math.round(configNumber(config, "iterations", DEFAULT_NUM_SIMULATIONS));
-    const seasonGames = Math.round(configNumber(config, "seasonGames", DEFAULT_EPL_REGULAR_SEASON_GAMES));
-    const averageOpponentElo = configNumber(config, "averageOpponentElo", DEFAULT_AVERAGE_OPPONENT_ELO);
+    const numSimulations = Math.round(positiveConfigNumber(config, "iterations", DEFAULT_NUM_SIMULATIONS));
+    const seasonGames = Math.round(positiveConfigNumber(config, "seasonGames", DEFAULT_EPL_REGULAR_SEASON_GAMES));
+    const averageOpponentElo = positiveConfigNumber(config, "averageOpponentElo", DEFAULT_AVERAGE_OPPONENT_ELO);
     const matchOptions = {
-      baseDrawRate: configNumber(config, "baseDrawRate", DEFAULT_BASE_DRAW_RATE),
-      drawDecay: configNumber(config, "drawDecay", DEFAULT_DRAW_DECAY),
-      matchParityFactor: requiredConfigNumber(config, "matchParityFactor"),
+      baseDrawRate: positiveConfigNumber(config, "baseDrawRate", DEFAULT_BASE_DRAW_RATE),
+      drawDecay: positiveConfigNumber(config, "drawDecay", DEFAULT_DRAW_DECAY),
+      matchParityFactor: requiredConfigNumber(config, "matchParityFactor", "EPL simulator"),
     };
 
     if (participantRows.length === 0) {
diff --git a/app/services/simulations/golf-simulator.ts b/app/services/simulations/golf-simulator.ts
index 673fa58..f0001d8 100644
--- a/app/services/simulations/golf-simulator.ts
+++ b/app/services/simulations/golf-simulator.ts
@@ -38,10 +38,11 @@ import { getGolfSkillsMap, type GolfSkillsRecord } from "~/models/golf-skills";
 import { getQPConfig } from "~/models/qualifying-points";
 import { getExcludedByEventMap } from "~/models/event-result";
 import type { Simulator, SimulationResult } from "./types";
+import { positiveConfigNumber } from "./config-access";
 
 // ─── Simulation parameters ────────────────────────────────────────────────────
 
-const NUM_SIMULATIONS = 10_000;
+const DEFAULT_NUM_SIMULATIONS = 10_000;
 
 /**
  * Simulated field size for each major.
@@ -180,7 +181,8 @@ export function simulateMajor(
 // ─── Simulator ────────────────────────────────────────────────────────────────
 
 export class GolfSimulator implements Simulator {
-  async simulate(sportsSeasonId: string): Promise<SimulationResult[]> {
+  async simulate(sportsSeasonId: string, config: Record<string, unknown> = {}): Promise<SimulationResult[]> {
+    const numSimulations = Math.round(positiveConfigNumber(config, "iterations", DEFAULT_NUM_SIMULATIONS));
     const db = database();
 
     // Load participants, skills, QP config, and scoring events in parallel.
@@ -269,7 +271,7 @@ export class GolfSimulator implements Simulator {
     );
     const idToIndex = new Map<string, number>(participantIds.map((id, i) => [id, i]));
 
-    for (let sim = 0; sim < NUM_SIMULATIONS; sim++) {
+    for (let sim = 0; sim < numSimulations; sim++) {
       const simQP = new Map<string, number>(actualQPMap);
 
       for (const { players, restCount, restStrength } of majorConfigs) {
@@ -292,14 +294,14 @@ export class GolfSimulator implements Simulator {
     return participantIds.map((participantId, i) => ({
       participantId,
       probabilities: {
-        probFirst:   counts[i][0] / NUM_SIMULATIONS,
-        probSecond:  counts[i][1] / NUM_SIMULATIONS,
-        probThird:   counts[i][2] / NUM_SIMULATIONS,
-        probFourth:  counts[i][3] / NUM_SIMULATIONS,
-        probFifth:   counts[i][4] / NUM_SIMULATIONS,
-        probSixth:   counts[i][5] / NUM_SIMULATIONS,
-        probSeventh: counts[i][6] / NUM_SIMULATIONS,
-        probEighth:  counts[i][7] / NUM_SIMULATIONS,
+        probFirst:   counts[i][0] / numSimulations,
+        probSecond:  counts[i][1] / numSimulations,
+        probThird:   counts[i][2] / numSimulations,
+        probFourth:  counts[i][3] / numSimulations,
+        probFifth:   counts[i][4] / numSimulations,
+        probSixth:   counts[i][5] / numSimulations,
+        probSeventh: counts[i][6] / numSimulations,
+        probEighth:  counts[i][7] / numSimulations,
       },
       source: "golf_qualifying_points_monte_carlo",
     }));
diff --git a/app/services/simulations/input-policy.ts b/app/services/simulations/input-policy.ts
index 8e08b89..d230b07 100644
--- a/app/services/simulations/input-policy.ts
+++ b/app/services/simulations/input-policy.ts
@@ -254,7 +254,14 @@ export function resolveSourceElos(
       );
     }
     if (oddsInputs.length >= 2) {
-      for (const [participantId, elo] of convertFuturesToElo(oddsInputs)) {
+      // Map onto the configured Elo band so the policy's floor/ceiling set the
+      // odds-derived *spread* (the real flattening dial), not just a post-hoc clamp.
+      const converted = convertFuturesToElo(oddsInputs, "american", {
+        exponent: 0.33,
+        eloMin: policy.eloMin,
+        eloMax: policy.eloMax,
+      });
+      for (const [participantId, elo] of converted) {
         oddsElo.set(participantId, elo);
       }
     }
diff --git a/app/services/simulations/llws-simulator.ts b/app/services/simulations/llws-simulator.ts
index c633b08..850e6f8 100644
--- a/app/services/simulations/llws-simulator.ts
+++ b/app/services/simulations/llws-simulator.ts
@@ -61,6 +61,7 @@ import { eq } from "drizzle-orm";
 import * as schema from "~/database/schema";
 import { convertAmericanOddsToProbability } from "~/services/probability-engine";
 import type { Simulator, SimulationResult } from "./types";
+import { positiveConfigNumber } from "./config-access";
 
 // ─── Simulation parameters ────────────────────────────────────────────────────
 
@@ -261,7 +262,8 @@ function determineRandomized(sideTeams: Team[], sideName: string): boolean {
 export class LLWSSimulator implements Simulator {
   constructor(private numSimulations = NUM_SIMULATIONS) {}
 
-  async simulate(sportsSeasonId: string): Promise<SimulationResult[]> {
+  async simulate(sportsSeasonId: string, config: Record<string, unknown> = {}): Promise<SimulationResult[]> {
+    const numSimulations = Math.round(positiveConfigNumber(config, "iterations", this.numSimulations));
     const db = database();
 
     // 1. Load all participants.
@@ -347,7 +349,7 @@ export class LLWSSimulator implements Simulator {
     };
 
     // 6. Run Monte Carlo simulations.
-    for (let s = 0; s < this.numSimulations; s++) {
+    for (let s = 0; s < numSimulations; s++) {
       // Assign pools for this simulation.
       const [usPoolA, usPoolB] = assignPools(usTeams, usRandomized);
       const [intlPoolA, intlPoolB] = assignPools(intlTeams, intlRandomized);
@@ -378,7 +380,7 @@ export class LLWSSimulator implements Simulator {
     // 7. Convert counts to probability distributions.
     //    bracketLosers: 4 per sim (2 US + 2 Intl) → split evenly.
     const bracketLosersPerSim = 4;
-    const bracketDivisor = bracketLosersPerSim * this.numSimulations;
+    const bracketDivisor = bracketLosersPerSim * numSimulations;
 
     const zeroCounts: PlacementCounts = { champion: 0, finalist: 0, thirdPlace: 0, fourthPlace: 0, bracketLoser: 0 };
     return allIds.map((id) => {
@@ -387,10 +389,10 @@ export class LLWSSimulator implements Simulator {
       return {
         participantId: id,
         probabilities: {
-          probFirst: c.champion / this.numSimulations,
-          probSecond: c.finalist / this.numSimulations,
-          probThird: c.thirdPlace / this.numSimulations,
-          probFourth: c.fourthPlace / this.numSimulations,
+          probFirst: c.champion / numSimulations,
+          probSecond: c.finalist / numSimulations,
+          probThird: c.thirdPlace / numSimulations,
+          probFourth: c.fourthPlace / numSimulations,
           probFifth: bracketProb,
           probSixth: bracketProb,
           probSeventh: bracketProb,
diff --git a/app/services/simulations/manifest.ts b/app/services/simulations/manifest.ts
index 8d9c862..530e41b 100644
--- a/app/services/simulations/manifest.ts
+++ b/app/services/simulations/manifest.ts
@@ -66,7 +66,7 @@ const PROFILES: Record<SimulatorType, Omit<SimulatorManifestProfile, "simulatorT
     setupSections: ["participants", "futuresOdds", "bracket"],
   },
   ucl_bracket: {
-    defaultConfig: { ...BASE_CONFIG, inputPolicy: { oddsWeight: 0.3 } },
+    defaultConfig: { ...BASE_CONFIG, parityFactor: 400, inputPolicy: { oddsWeight: 0.3 } },
     requiredInputs: ["sourceElo"],
     optionalInputs: ["sourceOdds"],
     derivableInputs: { sourceElo: ["sourceOdds"] },
@@ -150,7 +150,7 @@ const PROFILES: Record<SimulatorType, Omit<SimulatorManifestProfile, "simulatorT
     setupSections: ["participants", "eloRatings", "regularStandings"],
   },
   wnba_bracket: {
-    defaultConfig: { ...BASE_CONFIG, seasonGames: 44, srsEloScale: 30 },
+    defaultConfig: { ...BASE_CONFIG, parityFactor: 400, seasonGames: 44, srsEloScale: 30 },
     requiredInputs: ["sourceElo"],
     optionalInputs: ["sourceOdds", "projectedWins"],
     derivableInputs: { sourceElo: ["projectedWins", "sourceOdds"] },
@@ -176,7 +176,7 @@ const PROFILES: Record<SimulatorType, Omit<SimulatorManifestProfile, "simulatorT
     setupSections: ["participants", "eloRatings", "rankings", "cs2Setup", "events"],
   },
   ncaa_football_bracket: {
-    defaultConfig: { ...BASE_CONFIG, bracketSize: 12, inputPolicy: { oddsWeight: 0.4 } },
+    defaultConfig: { ...BASE_CONFIG, parityFactor: 400, bracketSize: 12, inputPolicy: { oddsWeight: 0.4 } },
     requiredInputs: ["sourceElo"],
     optionalInputs: ["sourceOdds", "worldRanking"],
     derivableInputs: { sourceElo: ["sourceOdds"] },
diff --git a/app/services/simulations/mlb-simulator.ts b/app/services/simulations/mlb-simulator.ts
index 2c53046..86d2d6a 100644
--- a/app/services/simulations/mlb-simulator.ts
+++ b/app/services/simulations/mlb-simulator.ts
@@ -74,12 +74,13 @@ import { database } from "~/database/context";
 import { eq } from "drizzle-orm";
 import * as schema from "~/database/schema";
 import type { Simulator, SimulationResult } from "./types";
+import { positiveConfigNumber } from "./config-access";
 import { logger } from "~/lib/logger";
 import { getRegularSeasonStandings } from "~/models/regular-season-standings";
 
 // ─── Simulation parameters ────────────────────────────────────────────────────
 
-const NUM_SIMULATIONS = 50_000;
+const DEFAULT_NUM_SIMULATIONS = 50_000;
 const TOTAL_SEASON_GAMES = 162;
 
 /**
@@ -440,7 +441,8 @@ function simLeagueBracket(
 // ─── Simulator ────────────────────────────────────────────────────────────────
 
 export class MLBSimulator implements Simulator {
-  async simulate(sportsSeasonId: string): Promise<SimulationResult[]> {
+  async simulate(sportsSeasonId: string, config: Record<string, unknown> = {}): Promise<SimulationResult[]> {
+    const numSimulations = Math.round(positiveConfigNumber(config, "iterations", DEFAULT_NUM_SIMULATIONS));
     const db = database();
 
     // 1. Load all participants for this sports season.
@@ -569,7 +571,7 @@ export class MLBSimulator implements Simulator {
 
     let effectiveN = 0;
 
-    for (let s = 0; s < NUM_SIMULATIONS; s++) {
+    for (let s = 0; s < numSimulations; s++) {
       const alField = drawLeaguePlayoffField(alTeams, seedingWinRate);
       const nlField = drawLeaguePlayoffField(nlTeams, seedingWinRate);
       if (!alField || !nlField) continue; // degenerate draw — skip
diff --git a/app/services/simulations/mls-simulator.ts b/app/services/simulations/mls-simulator.ts
index 19f5fee..7f89786 100644
--- a/app/services/simulations/mls-simulator.ts
+++ b/app/services/simulations/mls-simulator.ts
@@ -50,6 +50,7 @@ import { simulateEloSoccerMatch, simulateSimpleSoccerGoals } from "./soccer-help
 import type { EloSoccerMatchOptions } from "./soccer-helpers";
 import { normalizeSimulationResultColumns } from "./simulation-probabilities";
 import { logger } from "~/lib/logger";
+import { configNumber } from "./config-access";
 
 // ─── Default constants (overridable via season simulator config) ───────────────
 
@@ -62,12 +63,6 @@ const DEFAULT_DRAW_DECAY = 0.002;
 
 const MLS_PLAYOFF_TEAMS_PER_CONF = 9;
 
-// ─── Config helpers ────────────────────────────────────────────────────────────
-
-function configNumber(config: Record<string, unknown> | undefined, key: string, fallback: number): number {
-  const value = config?.[key];
-  return typeof value === "number" && Number.isFinite(value) && value >= 0 ? value : fallback;
-}
 
 /**
  * Infer MLS conference from seasonParticipant.externalId.
diff --git a/app/services/simulations/nba-simulator.ts b/app/services/simulations/nba-simulator.ts
index 59cbd72..5d32a6c 100644
--- a/app/services/simulations/nba-simulator.ts
+++ b/app/services/simulations/nba-simulator.ts
@@ -53,19 +53,21 @@ import * as schema from "~/database/schema";
 import type { Simulator, SimulationResult } from "./types";
 import { normalizeTeamName } from "~/lib/normalize-team-name";
 import { getRegularSeasonStandings } from "~/models/regular-season-standings";
+import { positiveConfigNumber } from "./config-access";
 
-// ─── Simulation parameters ────────────────────────────────────────────────────
+// ─── Simulation parameters (defaults; overridable via season config) ───────────
 
-const NUM_SIMULATIONS = 50_000;
+const DEFAULT_NUM_SIMULATIONS = 50_000;
 
 /**
- * Elo parity factor. NBA uses 400 (standard formula).
+ * Elo parity factor. NBA defaults to 400 (standard formula).
  * A 400-point Elo difference → ~90.9% win probability per game.
+ * Raising it (via the season config's `parityFactor`) flattens the distribution.
  */
-const PARITY_FACTOR = 400;
+const DEFAULT_PARITY_FACTOR = 400;
 
 /** NBA regular season games per team. */
-const NBA_REGULAR_SEASON_GAMES = 82;
+const DEFAULT_REGULAR_SEASON_GAMES = 82;
 
 // ─── Team data (2025-26 season, as of March 2026) ─────────────────────────────
 
@@ -129,8 +131,8 @@ export function getTeamData(name: string): NbaTeamData | undefined {
  * Elo win probability for team A over team B.
  *   P(A) = 1 / (1 + 10^((eloB - eloA) / PARITY_FACTOR))
  */
-export function eloWinProbability(eloA: number, eloB: number): number {
-  return 1 / (1 + Math.pow(10, (eloB - eloA) / PARITY_FACTOR));
+export function eloWinProbability(eloA: number, eloB: number, parityFactor = DEFAULT_PARITY_FACTOR): number {
+  return 1 / (1 + Math.pow(10, (eloB - eloA) / parityFactor));
 }
 
 // ─── Per-position normalization ───────────────────────────────────────────────
@@ -157,90 +159,99 @@ function normalizeColumns(results: SimulationResult[]): void {
 
 type DbMatch = typeof schema.playoffMatches.$inferSelect;
 
-/** Simulate a single-game matchup. Returns winner and loser. */
-function simGame(
-  eloMap: Map<string, number>,
-  a: string,
-  b: string
-): { winner: string; loser: string } {
-  const eloA = eloMap.get(a) ?? 1400;
-  const eloB = eloMap.get(b) ?? 1400;
-  const winner = Math.random() < eloWinProbability(eloA, eloB) ? a : b;
-  return { winner, loser: winner === a ? b : a };
-}
-
-/** Simulate a best-of-7 series. Returns winner and loser. */
-function simSeries(
-  eloMap: Map<string, number>,
-  a: string,
-  b: string
-): { winner: string; loser: string } {
-  const winProb = eloWinProbability(eloMap.get(a) ?? 1400, eloMap.get(b) ?? 1400);
-  let wA = 0;
-  let wB = 0;
-  while (wA < 4 && wB < 4) {
-    if (Math.random() < winProb) wA++; else wB++;
-  }
-  return wA === 4 ? { winner: a, loser: b } : { winner: b, loser: a };
-}
-
 /**
- * Resolve a play-in single game.
- * Uses the real result if the match is complete; otherwise simulates.
- * p1Override / p2Override are used when the DB participant slot is still null
- * (i.e. filled in by the previous round's simulated result).
+ * Build the bracket match helpers bound to a given `parityFactor`. Returning them
+ * from a factory keeps every call site unchanged while letting the season config
+ * tune per-game variance.
  */
-function resolveGame(
-  eloMap: Map<string, number>,
-  match: DbMatch | undefined,
-  p1Override?: string,
-  p2Override?: string
-): { winner: string; loser: string } {
-  if (match?.isComplete && match.winnerId && match.loserId) {
-    return { winner: match.winnerId, loser: match.loserId };
+function makeBracketHelpers(parityFactor: number) {
+  /** Simulate a single-game matchup. Returns winner and loser. */
+  function simGame(
+    eloMap: Map<string, number>,
+    a: string,
+    b: string
+  ): { winner: string; loser: string } {
+    const eloA = eloMap.get(a) ?? 1400;
+    const eloB = eloMap.get(b) ?? 1400;
+    const winner = Math.random() < eloWinProbability(eloA, eloB, parityFactor) ? a : b;
+    return { winner, loser: winner === a ? b : a };
   }
-  const p1 = match?.participant1Id ?? p1Override;
-  const p2 = match?.participant2Id ?? p2Override;
-  if (!p1 || !p2) {
-    throw new Error(
-      `Cannot resolve game: missing participant(s) on match ${match?.id ?? "(undefined)"} ` +
-      `(p1=${p1 ?? "null"}, p2=${p2 ?? "null"}). ` +
-      `Ensure the bracket is fully generated before simulating.`
-    );
-  }
-  return simGame(eloMap, p1, p2);
-}
 
-/**
- * Resolve a playoff series.
- * Uses the real result if the match is complete; otherwise simulates best-of-7.
- * p1Override / p2Override fill null DB participant slots with the simulated seed.
- */
-function resolveSeries(
-  eloMap: Map<string, number>,
-  match: DbMatch | undefined,
-  p1Override?: string,
-  p2Override?: string
-): { winner: string; loser: string } {
-  if (match?.isComplete && match.winnerId && match.loserId) {
-    return { winner: match.winnerId, loser: match.loserId };
+  /** Simulate a best-of-7 series. Returns winner and loser. */
+  function simSeries(
+    eloMap: Map<string, number>,
+    a: string,
+    b: string
+  ): { winner: string; loser: string } {
+    const winProb = eloWinProbability(eloMap.get(a) ?? 1400, eloMap.get(b) ?? 1400, parityFactor);
+    let wA = 0;
+    let wB = 0;
+    while (wA < 4 && wB < 4) {
+      if (Math.random() < winProb) wA++; else wB++;
+    }
+    return wA === 4 ? { winner: a, loser: b } : { winner: b, loser: a };
   }
-  const p1 = match?.participant1Id ?? p1Override;
-  const p2 = match?.participant2Id ?? p2Override;
-  if (!p1 || !p2) {
-    throw new Error(
-      `Cannot resolve series: missing participant(s) on match ${match?.id ?? "(undefined)"} ` +
-      `(p1=${p1 ?? "null"}, p2=${p2 ?? "null"}). ` +
-      `Ensure the bracket is fully generated before simulating.`
-    );
+
+  /**
+   * Resolve a play-in single game.
+   * Uses the real result if the match is complete; otherwise simulates.
+   * p1Override / p2Override are used when the DB participant slot is still null
+   * (i.e. filled in by the previous round's simulated result).
+   */
+  function resolveGame(
+    eloMap: Map<string, number>,
+    match: DbMatch | undefined,
+    p1Override?: string,
+    p2Override?: string
+  ): { winner: string; loser: string } {
+    if (match?.isComplete && match.winnerId && match.loserId) {
+      return { winner: match.winnerId, loser: match.loserId };
+    }
+    const p1 = match?.participant1Id ?? p1Override;
+    const p2 = match?.participant2Id ?? p2Override;
+    if (!p1 || !p2) {
+      throw new Error(
+        `Cannot resolve game: missing participant(s) on match ${match?.id ?? "(undefined)"} ` +
+        `(p1=${p1 ?? "null"}, p2=${p2 ?? "null"}). ` +
+        `Ensure the bracket is fully generated before simulating.`
+      );
+    }
+    return simGame(eloMap, p1, p2);
   }
-  return simSeries(eloMap, p1, p2);
+
+  /**
+   * Resolve a playoff series.
+   * Uses the real result if the match is complete; otherwise simulates best-of-7.
+   * p1Override / p2Override fill null DB participant slots with the simulated seed.
+   */
+  function resolveSeries(
+    eloMap: Map<string, number>,
+    match: DbMatch | undefined,
+    p1Override?: string,
+    p2Override?: string
+  ): { winner: string; loser: string } {
+    if (match?.isComplete && match.winnerId && match.loserId) {
+      return { winner: match.winnerId, loser: match.loserId };
+    }
+    const p1 = match?.participant1Id ?? p1Override;
+    const p2 = match?.participant2Id ?? p2Override;
+    if (!p1 || !p2) {
+      throw new Error(
+        `Cannot resolve series: missing participant(s) on match ${match?.id ?? "(undefined)"} ` +
+        `(p1=${p1 ?? "null"}, p2=${p2 ?? "null"}). ` +
+        `Ensure the bracket is fully generated before simulating.`
+      );
+    }
+    return simSeries(eloMap, p1, p2);
+  }
+
+  return { simGame, simSeries, resolveGame, resolveSeries };
 }
 
 // ─── Simulator ────────────────────────────────────────────────────────────────
 
 export class NBASimulator implements Simulator {
-  async simulate(sportsSeasonId: string): Promise<SimulationResult[]> {
+  async simulate(sportsSeasonId: string, config: Record<string, unknown> = {}): Promise<SimulationResult[]> {
     const db = database();
 
     // ── Mode detection: bracket-aware if a playoff event with matches exists ──
@@ -258,21 +269,25 @@ export class NBASimulator implements Simulator {
       });
 
       if (bracketMatches.length > 0) {
-        return this.simulateBracketAware(sportsSeasonId, bracketMatches);
+        return this.simulateBracketAware(sportsSeasonId, bracketMatches, config);
       }
     }
 
     // ── Fall back to season-projection mode ───────────────────────────────────
-    return this.simulateSeasonProjection(sportsSeasonId);
+    return this.simulateSeasonProjection(sportsSeasonId, config);
   }
 
   // ── Mode 1: Bracket-Aware ──────────────────────────────────────────────────
 
   private async simulateBracketAware(
     sportsSeasonId: string,
-    allMatches: DbMatch[]
+    allMatches: DbMatch[],
+    config: Record<string, unknown> = {}
   ): Promise<SimulationResult[]> {
     const db = database();
+    const parityFactor = positiveConfigNumber(config, "parityFactor", DEFAULT_PARITY_FACTOR);
+    const numSimulations = Math.round(positiveConfigNumber(config, "iterations", DEFAULT_NUM_SIMULATIONS));
+    const { resolveGame, resolveSeries } = makeBracketHelpers(parityFactor);
 
     // Group matches by round.
     const pir1 = allMatches.filter((m) => m.round === "Play-In Round 1")
@@ -355,7 +370,7 @@ export class NBASimulator implements Simulator {
     const csLoserCounts  = new Map(participantIds.map((id) => [id, 0]));
 
     // ── Monte Carlo loop ──────────────────────────────────────────────────────
-    for (let s = 0; s < NUM_SIMULATIONS; s++) {
+    for (let s = 0; s < numSimulations; s++) {
 
       // ── Play-In Round 1 (4 single games) ─────────────────────────────────
       // M1: East 7 vs 8 → winner = E7 seed; loser enters PIR2 as p1
@@ -439,7 +454,7 @@ export class NBASimulator implements Simulator {
     //   probFirst/Second  → N total (1 per sim)
     //   probThird/Fourth  → cfLoserCounts / (2×N) — 2 CF losers per sim
     //   probFifth–Eighth  → csLoserCounts / (4×N) — 4 CS losers per sim
-    const N = NUM_SIMULATIONS;
+    const N = numSimulations;
     const results: SimulationResult[] = participantIds.map((participantId) => {
       const c  = championCounts.get(participantId) ?? 0;
       const f  = finalistCounts.get(participantId) ?? 0;
@@ -467,8 +482,11 @@ export class NBASimulator implements Simulator {
 
   // ── Mode 2: Season Projection ──────────────────────────────────────────────
 
-  private async simulateSeasonProjection(sportsSeasonId: string): Promise<SimulationResult[]> {
+  private async simulateSeasonProjection(sportsSeasonId: string, config: Record<string, unknown> = {}): Promise<SimulationResult[]> {
     const db = database();
+    const parityFactor = positiveConfigNumber(config, "parityFactor", DEFAULT_PARITY_FACTOR);
+    const numSimulations = Math.round(positiveConfigNumber(config, "iterations", DEFAULT_NUM_SIMULATIONS));
+    const seasonGames = Math.round(positiveConfigNumber(config, "seasonGames", DEFAULT_REGULAR_SEASON_GAMES));
 
     const [participantRows, standings, evRows] = await Promise.all([
       db
@@ -529,8 +547,8 @@ export class NBASimulator implements Simulator {
         data,
         conference,
         currentWins: standing?.wins ?? 0,
-        remainingGames: Math.max(0, NBA_REGULAR_SEASON_GAMES - gamesPlayed),
-        winProb: eloWinProbability(resolvedElo, 1500),
+        remainingGames: Math.max(0, seasonGames - gamesPlayed),
+        winProb: eloWinProbability(resolvedElo, 1500, parityFactor),
         resolvedElo,
       };
     });
@@ -546,10 +564,10 @@ export class NBASimulator implements Simulator {
     }
 
     const simTeamGame = (a: TeamEntry, b: TeamEntry): TeamEntry =>
-      Math.random() < eloWinProbability(eloOfEntry(a), eloOfEntry(b)) ? a : b;
+      Math.random() < eloWinProbability(eloOfEntry(a), eloOfEntry(b), parityFactor) ? a : b;
 
     const simTeamSeries = (a: TeamEntry, b: TeamEntry): { winner: TeamEntry; loser: TeamEntry } => {
-      const winProb = eloWinProbability(eloOfEntry(a), eloOfEntry(b));
+      const winProb = eloWinProbability(eloOfEntry(a), eloOfEntry(b), parityFactor);
       let wA = 0;
       let wB = 0;
       while (wA < 4 && wB < 4) {
@@ -597,7 +615,7 @@ export class NBASimulator implements Simulator {
     const confFinalLoserCounts = new Map<string, number>(participantIds.map((id) => [id, 0]));
     const confSemiLoserCounts  = new Map<string, number>(participantIds.map((id) => [id, 0]));
 
-    for (let s = 0; s < NUM_SIMULATIONS; s++) {
+    for (let s = 0; s < numSimulations; s++) {
       const eastBracket = buildConferenceBracket(easternTeams);
       const westBracket = buildConferenceBracket(westernTeams);
 
@@ -618,7 +636,7 @@ export class NBASimulator implements Simulator {
       }
     }
 
-    const N = NUM_SIMULATIONS;
+    const N = numSimulations;
     const results: SimulationResult[] = participantIds.map((participantId) => {
       const c  = championCounts.get(participantId) ?? 0;
       const f  = finalistCounts.get(participantId) ?? 0;
diff --git a/app/services/simulations/ncaa-football-simulator.ts b/app/services/simulations/ncaa-football-simulator.ts
index 6141165..9dd4e80 100644
--- a/app/services/simulations/ncaa-football-simulator.ts
+++ b/app/services/simulations/ncaa-football-simulator.ts
@@ -7,9 +7,9 @@
  *   1. Load all participants for the sports season from DB
  *   2. Load Elo/FPI ratings from participantExpectedValues.sourceElo
  *      (entered via Admin → Elo Ratings page; use FPI, S&P+, or any Elo-scale rating)
- *   3. If sourceOdds (American format) are also stored, build a normalized selection
- *      weight from implied championship probability (used for field selection in step 4)
- *      and blend into per-game win probability (ELO_WEIGHT=0.6 / ODDS_WEIGHT=0.4).
+ *   3. Field-selection weight is a softmax over the resolved Elo. Futures odds are
+ *      not blended into per-game win probability — the input policy already folded
+ *      them into sourceElo, so blending again would double-count them.
  *   4. Per simulation, select 12 teams for the CFP field:
  *      - If the pool has exactly 12 teams: use all of them (post-bracket mode).
  *      - If the pool has >12 teams: weighted sample without replacement using each
@@ -31,8 +31,8 @@
  *     fields, so its champion probability accounts for that.
  *   Post-bracket (exactly 12 participants): deterministic field, bracket-only sim.
  *
- * Win probability (per game): eloWinProbability() from probability-engine (400-divisor).
- * Blended win probability: ELO_WEIGHT * eloProb + ODDS_WEIGHT * oddsProb (when odds present).
+ * Win probability (per game): eloWinProbabilityWithParity(eloA, eloB, parityFactor),
+ * where parityFactor comes from the season config (default 400).
  *
  * Selection weight (pre-bracket mode):
  *   With sourceOdds: normalized implied championship probability (vig removed, sums to 1).
@@ -59,12 +59,15 @@
 import { database } from "~/database/context";
 import { eq } from "drizzle-orm";
 import * as schema from "~/database/schema";
-import { eloWinProbability } from "~/services/probability-engine";
+import { eloWinProbabilityWithParity } from "~/services/probability-engine";
 import type { Simulator, SimulationResult } from "./types";
+import { positiveConfigNumber } from "./config-access";
 
-// ─── Simulation parameters ────────────────────────────────────────────────────
+// ─── Simulation parameters (defaults; overridable via season config) ───────────
 
-const NUM_SIMULATIONS = 50_000;
+const DEFAULT_NUM_SIMULATIONS = 50_000;
+/** Elo parity factor. Defaults to 400 (standard formula). */
+const DEFAULT_PARITY_FACTOR = 400;
 const BRACKET_SIZE = 12;
 
 /**
@@ -87,12 +90,12 @@ interface Team {
 // ─── Helpers ─────────────────────────────────────────────────────────────────
 
 /** Win probability for team1 vs team2 from the single resolved Elo. */
-function gameWinProb(team1: Team, team2: Team): number {
-  return eloWinProbability(team1.elo, team2.elo);
+function gameWinProb(team1: Team, team2: Team, parityFactor = DEFAULT_PARITY_FACTOR): number {
+  return eloWinProbabilityWithParity(team1.elo, team2.elo, parityFactor);
 }
 
-function simGame(team1: Team, team2: Team): { winner: Team; loser: Team } {
-  const p1Wins = Math.random() < gameWinProb(team1, team2);
+function simGame(team1: Team, team2: Team, parityFactor = DEFAULT_PARITY_FACTOR): { winner: Team; loser: Team } {
+  const p1Wins = Math.random() < gameWinProb(team1, team2, parityFactor);
   return p1Wins
     ? { winner: team1, loser: team2 }
     : { winner: team2, loser: team1 };
@@ -141,18 +144,19 @@ interface PlacementCounts {
  *   Semifinals:     qf1w vs qf2w, qf3w vs qf4w
  *   Championship:   sf1w vs sf2w
  */
-function simulateBracket(teams: Team[], counts: Map<string, PlacementCounts>): void {
+function simulateBracket(teams: Team[], counts: Map<string, PlacementCounts>, parityFactor = DEFAULT_PARITY_FACTOR): void {
+  const game = (a: Team, b: Team) => simGame(a, b, parityFactor);
   // ── First Round (seeds 5–12) ───────────────────────────────────────────────
-  const fr1 = simGame(teams[4], teams[11]); // 5 vs 12
-  const fr2 = simGame(teams[5], teams[10]); // 6 vs 11
-  const fr3 = simGame(teams[6], teams[9]);  // 7 vs 10
-  const fr4 = simGame(teams[7], teams[8]);  // 8 vs 9
+  const fr1 = game(teams[4], teams[11]); // 5 vs 12
+  const fr2 = game(teams[5], teams[10]); // 6 vs 11
+  const fr3 = game(teams[6], teams[9]);  // 7 vs 10
+  const fr4 = game(teams[7], teams[8]);  // 8 vs 9
 
   // ── Quarterfinals (seeds 1–4 get byes) ────────────────────────────────────
-  const qf1 = simGame(teams[0], fr4.winner); // 1 vs 8/9 winner
-  const qf2 = simGame(teams[3], fr1.winner); // 4 vs 5/12 winner
-  const qf3 = simGame(teams[2], fr2.winner); // 3 vs 6/11 winner
-  const qf4 = simGame(teams[1], fr3.winner); // 2 vs 7/10 winner
+  const qf1 = game(teams[0], fr4.winner); // 1 vs 8/9 winner
+  const qf2 = game(teams[3], fr1.winner); // 4 vs 5/12 winner
+  const qf3 = game(teams[2], fr2.winner); // 3 vs 6/11 winner
+  const qf4 = game(teams[1], fr3.winner); // 2 vs 7/10 winner
 
   const bump = (id: string, key: keyof PlacementCounts) => {
     const entry = counts.get(id);
@@ -165,14 +169,14 @@ function simulateBracket(teams: Team[], counts: Map<string, PlacementCounts>): v
   bump(qf4.loser.participantId, "qfLoser");
 
   // ── Semifinals ────────────────────────────────────────────────────────────
-  const sf1 = simGame(qf1.winner, qf2.winner);
-  const sf2 = simGame(qf3.winner, qf4.winner);
+  const sf1 = game(qf1.winner, qf2.winner);
+  const sf2 = game(qf3.winner, qf4.winner);
 
   bump(sf1.loser.participantId, "sfLoser");
   bump(sf2.loser.participantId, "sfLoser");
 
   // ── National Championship ─────────────────────────────────────────────────
-  const final = simGame(sf1.winner, sf2.winner);
+  const final = game(sf1.winner, sf2.winner);
 
   bump(final.winner.participantId, "champion");
   bump(final.loser.participantId, "finalist");
@@ -181,8 +185,10 @@ function simulateBracket(teams: Team[], counts: Map<string, PlacementCounts>): v
 // ─── Simulator ────────────────────────────────────────────────────────────────
 
 export class NCAAFootballSimulator implements Simulator {
-  async simulate(sportsSeasonId: string): Promise<SimulationResult[]> {
+  async simulate(sportsSeasonId: string, config: Record<string, unknown> = {}): Promise<SimulationResult[]> {
     const db = database();
+    const parityFactor = positiveConfigNumber(config, "parityFactor", DEFAULT_PARITY_FACTOR);
+    const numSimulations = Math.round(positiveConfigNumber(config, "iterations", DEFAULT_NUM_SIMULATIONS));
     // 1. Load all participants for this sports season.
     const participants = await db
       .select({ id: schema.seasonParticipants.id })
@@ -241,18 +247,18 @@ export class NCAAFootballSimulator implements Simulator {
     );
 
     // 6. Run Monte Carlo simulations.
-    for (let s = 0; s < NUM_SIMULATIONS; s++) {
+    for (let s = 0; s < numSimulations; s++) {
       const field = preBracketMode
         ? sampleBracketField(allTeams, BRACKET_SIZE)
         : (deterministicField ?? []);
-      simulateBracket(field, counts);
+      simulateBracket(field, counts, parityFactor);
     }
 
     // 7. Convert counts to probability distributions.
     //    SF losers: 2 per sim → each team's share = sfLoser / (2 * N).
     //    QF losers: 4 per sim → each team's share = qfLoser / (4 * N).
-    const sfDivisor = 2 * NUM_SIMULATIONS;
-    const qfDivisor = 4 * NUM_SIMULATIONS;
+    const sfDivisor = 2 * numSimulations;
+    const qfDivisor = 4 * numSimulations;
 
     return allParticipantIds.map((id) => {
       const c = counts.get(id) ?? { champion: 0, finalist: 0, sfLoser: 0, qfLoser: 0 };
@@ -261,8 +267,8 @@ export class NCAAFootballSimulator implements Simulator {
       return {
         participantId: id,
         probabilities: {
-          probFirst: c.champion / NUM_SIMULATIONS,
-          probSecond: c.finalist / NUM_SIMULATIONS,
+          probFirst: c.champion / numSimulations,
+          probSecond: c.finalist / numSimulations,
           probThird: sfProb,
           probFourth: sfProb,
           probFifth: qfProb,
diff --git a/app/services/simulations/ncaam-simulator.ts b/app/services/simulations/ncaam-simulator.ts
index 560ad96..68da574 100644
--- a/app/services/simulations/ncaam-simulator.ts
+++ b/app/services/simulations/ncaam-simulator.ts
@@ -1,5 +1,6 @@
 import { NCAABasketballSimulator } from "./ncaa-basketball-simulator";
 import type { Simulator, SimulationResult } from "./types";
+import { optionalPositiveNumber } from "./config-access";
 
 const KENPOM_SCALE_FACTOR = 7.5;
 
@@ -11,10 +12,6 @@ export function kenpomWinProbability(netrtgA: number, netrtgB: number): number {
   return 1 / (1 + Math.exp(-(netrtgA - netrtgB) / KENPOM_SCALE_FACTOR));
 }
 
-function optionalPositiveNumber(value: unknown, fallback: number): number {
-  return typeof value === "number" && Number.isFinite(value) && value > 0 ? value : fallback;
-}
-
 function kenpomWinProbabilityWithScale(scaleFactor: number): (netrtgA: number, netrtgB: number) => number {
   return (netrtgA, netrtgB) => 1 / (1 + Math.exp(-(netrtgA - netrtgB) / scaleFactor));
 }
diff --git a/app/services/simulations/nfl-simulator.ts b/app/services/simulations/nfl-simulator.ts
index e23d4af..c47f321 100644
--- a/app/services/simulations/nfl-simulator.ts
+++ b/app/services/simulations/nfl-simulator.ts
@@ -46,15 +46,19 @@ import { eq } from "drizzle-orm";
 import * as schema from "~/database/schema";
 import type { Simulator, SimulationResult } from "./types";
 import { normalizeTeamName } from "~/lib/normalize-team-name";
-import { eloWinProbability, convertFuturesToElo } from "~/services/probability-engine";
+import { eloWinProbabilityWithParity, convertFuturesToElo } from "~/services/probability-engine";
 import { getRegularSeasonStandings } from "~/models/regular-season-standings";
+import { positiveConfigNumber } from "./config-access";
 
-// ─── Simulation parameters ────────────────────────────────────────────────────
+// ─── Simulation parameters (defaults; overridable via season config) ───────────
 
-const NUM_SIMULATIONS = 50_000;
+const DEFAULT_NUM_SIMULATIONS = 50_000;
+
+/** Elo parity factor. NFL defaults to 400 (standard formula). */
+const DEFAULT_PARITY_FACTOR = 400;
 
 /** NFL regular season games per team. */
-const NFL_REGULAR_SEASON_GAMES = 17;
+const DEFAULT_REGULAR_SEASON_GAMES = 17;
 
 /** Average opponent Elo for regular season game projection. */
 const AVG_OPPONENT_ELO = 1500;
@@ -173,9 +177,10 @@ export function getTeamData(name: string): NflTeamData | undefined {
 function simulateProjectedWins(
   currentWins: number,
   gamesPlayed: number,
-  winProb: number
+  winProb: number,
+  seasonGames = DEFAULT_REGULAR_SEASON_GAMES
 ): number {
-  const remaining = Math.max(0, NFL_REGULAR_SEASON_GAMES - gamesPlayed);
+  const remaining = Math.max(0, seasonGames - gamesPlayed);
   let additional = 0;
   for (let g = 0; g < remaining; g++) {
     if (Math.random() < winProb) additional++;
@@ -231,11 +236,12 @@ export function seedConference(
  * Simulate a playoff game with home-field advantage for the higher seed.
  * The team with the lower seed number (better seed) is the home team.
  */
-function playGame(a: SeededTeam, b: SeededTeam): { winner: SeededTeam; loser: SeededTeam } {
+function playGame(a: SeededTeam, b: SeededTeam, parityFactor = DEFAULT_PARITY_FACTOR): { winner: SeededTeam; loser: SeededTeam } {
   const [home, away] = a.seed < b.seed ? [a, b] : [b, a];
-  const winProbHome = eloWinProbability(
+  const winProbHome = eloWinProbabilityWithParity(
     home.elo + NFL_HOME_FIELD_ELO_ADVANTAGE,
-    away.elo
+    away.elo,
+    parityFactor
   );
   if (Math.random() < winProbHome) return { winner: home, loser: away };
   return { winner: away, loser: home };
@@ -245,8 +251,8 @@ function playGame(a: SeededTeam, b: SeededTeam): { winner: SeededTeam; loser: Se
  * Simulate a game at a neutral site (no home-field adjustment).
  * Used for the Super Bowl.
  */
-function playNeutralGame(a: SeededTeam, b: SeededTeam): { winner: SeededTeam; loser: SeededTeam } {
-  const winProbA = eloWinProbability(a.elo, b.elo);
+function playNeutralGame(a: SeededTeam, b: SeededTeam, parityFactor = DEFAULT_PARITY_FACTOR): { winner: SeededTeam; loser: SeededTeam } {
+  const winProbA = eloWinProbabilityWithParity(a.elo, b.elo, parityFactor);
   if (Math.random() < winProbA) return { winner: a, loser: b };
   return { winner: b, loser: a };
 }
@@ -261,14 +267,15 @@ function playNeutralGame(a: SeededTeam, b: SeededTeam): { winner: SeededTeam; lo
  * Returns the finalist, the conference championship loser, and the two
  * divisional-round losers (for 5th-8th place EV).
  */
-export function simulateConferenceBracket(seeds: SeededTeam[]): ConferenceBracketResult {
+export function simulateConferenceBracket(seeds: SeededTeam[], parityFactor = DEFAULT_PARITY_FACTOR): ConferenceBracketResult {
   const byIndex = new Map(seeds.map((t) => [t.seed, t]));
   const s = (seed: number) => byIndex.get(seed) as SeededTeam;
+  const pg = (a: SeededTeam, b: SeededTeam) => playGame(a, b, parityFactor);
 
   // Wild Card (seed 1 bye; lower seed = home)
-  const wc27 = playGame(s(2), s(7));
-  const wc36 = playGame(s(3), s(6));
-  const wc45 = playGame(s(4), s(5));
+  const wc27 = pg(s(2), s(7));
+  const wc36 = pg(s(3), s(6));
+  const wc45 = pg(s(4), s(5));
 
   // Divisional: sort WC winners by original seed (ascending = better seed = home)
   // Seed 1 hosts the lowest-ranked (highest seed number) WC winner
@@ -276,11 +283,11 @@ export function simulateConferenceBracket(seeds: SeededTeam[]): ConferenceBracke
     (a, b) => a.seed - b.seed
   );
 
-  const div1 = playGame(s(1), wcWinners[wcWinners.length - 1]);
-  const div2 = playGame(wcWinners[0], wcWinners[1]);
+  const div1 = pg(s(1), wcWinners[wcWinners.length - 1]);
+  const div2 = pg(wcWinners[0], wcWinners[1]);
 
   // Conference Championship (higher remaining seed is home)
-  const conf = playGame(div1.winner, div2.winner);
+  const conf = pg(div1.winner, div2.winner);
 
   return {
     finalist: conf.winner,
@@ -292,8 +299,11 @@ export function simulateConferenceBracket(seeds: SeededTeam[]): ConferenceBracke
 // ─── Simulator class ──────────────────────────────────────────────────────────
 
 export class NFLSimulator implements Simulator {
-  async simulate(sportsSeasonId: string): Promise<SimulationResult[]> {
+  async simulate(sportsSeasonId: string, config: Record<string, unknown> = {}): Promise<SimulationResult[]> {
     const db = database();
+    const parityFactor = positiveConfigNumber(config, "parityFactor", DEFAULT_PARITY_FACTOR);
+    const numSimulations = Math.round(positiveConfigNumber(config, "iterations", DEFAULT_NUM_SIMULATIONS));
+    const seasonGames = Math.round(positiveConfigNumber(config, "seasonGames", DEFAULT_REGULAR_SEASON_GAMES));
 
     // Load participants
     const participants = await db.query.seasonParticipants.findMany({
@@ -385,7 +395,7 @@ export class NFLSimulator implements Simulator {
     // Pre-compute per-team win probability vs average opponent (constant across sims)
     const winProbMap = new Map<string, number>();
     for (const t of teams) {
-      winProbMap.set(t.participantId, eloWinProbability(t.elo, AVG_OPPONENT_ELO));
+      winProbMap.set(t.participantId, eloWinProbabilityWithParity(t.elo, AVG_OPPONENT_ELO, parityFactor));
     }
 
     // Placement counters
@@ -396,7 +406,7 @@ export class NFLSimulator implements Simulator {
 
     // ─── Monte Carlo ──────────────────────────────────────────────────────────
 
-    for (let sim = 0; sim < NUM_SIMULATIONS; sim++) {
+    for (let sim = 0; sim < numSimulations; sim++) {
       // Project wins for each team this simulation
       const projected = teams.map((t) => ({
         participantId: t.participantId,
@@ -406,7 +416,8 @@ export class NFLSimulator implements Simulator {
         projectedWins: simulateProjectedWins(
           t.currentWins,
           t.gamesPlayed,
-          winProbMap.get(t.participantId) as number
+          winProbMap.get(t.participantId) as number,
+          seasonGames
         ),
       }));
 
@@ -416,11 +427,11 @@ export class NFLSimulator implements Simulator {
       const nfcSeeds = seedConference(nfcTeams);
 
       // Simulate conference brackets
-      const afcResult = simulateConferenceBracket(afcSeeds);
-      const nfcResult = simulateConferenceBracket(nfcSeeds);
+      const afcResult = simulateConferenceBracket(afcSeeds, parityFactor);
+      const nfcResult = simulateConferenceBracket(nfcSeeds, parityFactor);
 
       // Super Bowl (neutral site)
-      const sb = playNeutralGame(afcResult.finalist, nfcResult.finalist);
+      const sb = playNeutralGame(afcResult.finalist, nfcResult.finalist, parityFactor);
 
       // 1st / 2nd
       counts[sb.winner.participantId][1] += 1;
@@ -445,7 +456,7 @@ export class NFLSimulator implements Simulator {
     // Convert counts to probabilities
     return teams.map((t) => {
       const c = counts[t.participantId];
-      const N = NUM_SIMULATIONS;
+      const N = numSimulations;
       return {
         participantId: t.participantId,
         probabilities: {
diff --git a/app/services/simulations/nhl-simulator.ts b/app/services/simulations/nhl-simulator.ts
index 8e24c30..3bf7b93 100644
--- a/app/services/simulations/nhl-simulator.ts
+++ b/app/services/simulations/nhl-simulator.ts
@@ -64,38 +64,34 @@ import { eq, and } from "drizzle-orm";
 import * as schema from "~/database/schema";
 import type { Simulator, SimulationResult } from "./types";
 import { logger } from "~/lib/logger";
-import {
-  convertAmericanOddsToProbability,
-  normalizeProbabilities,
-} from "~/services/probability-engine";
 import { getRegularSeasonStandings } from "~/models/regular-season-standings";
+import { positiveConfigNumber, configNumber } from "./config-access";
 
-// ─── Simulation parameters ────────────────────────────────────────────────────
+// ─── Simulation parameters (defaults; overridable via season config) ───────────
 
-const NUM_SIMULATIONS = 50_000;
+const DEFAULT_NUM_SIMULATIONS = 50_000;
 
 /** NHL regular season games per team. */
-const NHL_REGULAR_SEASON_GAMES = 82;
+const DEFAULT_REGULAR_SEASON_GAMES = 82;
 
 /**
  * Fraction of NHL games that go to overtime / shootout.
  * The losing team earns 1 point (instead of 0) in these games.
  * Historical average: ~23% of games.
  */
-const NHL_OT_RATE = 0.23;
+const DEFAULT_OT_RATE = 0.23;
 
 /**
- * Elo parity factor. NHL uses 1000 (higher than the standard 400) to reflect
- * the elevated game-to-game variance in hockey.
+ * Elo parity factor. NHL defaults to 1000 (higher than the standard 400) to
+ * reflect the elevated game-to-game variance in hockey. Raising it flattens the
+ * finish-position distribution; the season config's `parityFactor` overrides it.
+ *
+ * Futures odds influence the simulation only through each team's resolved Elo
+ * (odds → Elo happens once, in the central input-policy resolver). The simulator
+ * does not blend raw odds into per-game probabilities — doing so double-counted
+ * the same signal and over-sharpened favorites.
  */
-const PARITY_FACTOR = 1000;
-
-/**
- * Blend weights for Elo vs. Vegas futures odds when sourceOdds are available.
- * Same calibration as the UCL simulator (0.7 / 0.3).
- */
-const ELO_WEIGHT  = 0.7;
-const ODDS_WEIGHT = 1 - ELO_WEIGHT;
+const DEFAULT_PARITY_FACTOR = 1000;
 
 // ─── Team data (2025-26 season) ───────────────────────────────────────────────
 //
@@ -179,11 +175,11 @@ export function getTeamData(name: string): NhlTeamData | undefined {
 
 /**
  * Elo win probability for team A over team B.
- *   P(A) = 1 / (1 + 10^((eloB - eloA) / PARITY_FACTOR))
+ *   P(A) = 1 / (1 + 10^((eloB - eloA) / parityFactor))
  * Exported for unit testing.
  */
-export function eloWinProbability(eloA: number, eloB: number): number {
-  return 1 / (1 + Math.pow(10, (eloB - eloA) / PARITY_FACTOR));
+export function eloWinProbability(eloA: number, eloB: number, parityFactor = DEFAULT_PARITY_FACTOR): number {
+  return 1 / (1 + Math.pow(10, (eloB - eloA) / parityFactor));
 }
 
 // ─── Internal types ───────────────────────────────────────────────────────────
@@ -217,10 +213,10 @@ function elo(entry: TeamEntry): number {
  *   - Regulation loss (0 pts) otherwise
  * Returns projected total points for the season.
  */
-export function simulateProjectedPoints(entry: TeamEntry): number {
+export function simulateProjectedPoints(entry: TeamEntry, otRate = DEFAULT_OT_RATE): number {
   let extra = 0;
   const { winProb, remainingGames } = entry;
-  const otlProb = (1 - winProb) * NHL_OT_RATE;
+  const otlProb = (1 - winProb) * otRate;
   for (let g = 0; g < remainingGames; g++) {
     const r = Math.random();
     if (r < winProb) {
@@ -241,8 +237,8 @@ interface ProjectedTeam {
 }
 
 /** Project one team's end-of-season point total with a random tiebreaker. */
-function projectTeam(t: TeamEntry): ProjectedTeam {
-  return { team: t, pts: simulateProjectedPoints(t), tb: Math.random() };
+function projectTeam(t: TeamEntry, otRate: number): ProjectedTeam {
+  return { team: t, pts: simulateProjectedPoints(t, otRate), tb: Math.random() };
 }
 
 /** Sort projected teams descending by pts, then by random tiebreaker. Mutates arr. */
@@ -253,7 +249,7 @@ function sortProjected(arr: ProjectedTeam[]): ProjectedTeam[] {
 // ─── Simulator ────────────────────────────────────────────────────────────────
 
 export class NHLSimulator implements Simulator {
-  async simulate(sportsSeasonId: string): Promise<SimulationResult[]> {
+  async simulate(sportsSeasonId: string, config: Record<string, unknown> = {}): Promise<SimulationResult[]> {
     const db = database();
 
     // Check for a populated playoff bracket; if found, use bracket-aware simulation.
@@ -271,7 +267,7 @@ export class NHLSimulator implements Simulator {
       });
       const bracketPopulated = allMatches.some((m) => m.participant1Id && m.participant2Id);
       if (bracketPopulated) {
-        return this.simulateBracket(sportsSeasonId, allMatches);
+        return this.simulateBracket(sportsSeasonId, allMatches, config);
       }
     }
 
@@ -286,7 +282,6 @@ export class NHLSimulator implements Simulator {
         .select({
           participantId: schema.seasonParticipantExpectedValues.participantId,
           sourceElo: schema.seasonParticipantExpectedValues.sourceElo,
-          sourceOdds: schema.seasonParticipantExpectedValues.sourceOdds,
         })
         .from(schema.seasonParticipantExpectedValues)
         .where(eq(schema.seasonParticipantExpectedValues.sportsSeasonId, sportsSeasonId)),
@@ -299,6 +294,12 @@ export class NHLSimulator implements Simulator {
       );
     }
 
+    // Engine knobs (admin-overridable via the season config; default to NHL values).
+    const parityFactor = positiveConfigNumber(config, "parityFactor", DEFAULT_PARITY_FACTOR);
+    const numSimulations = Math.round(positiveConfigNumber(config, "iterations", DEFAULT_NUM_SIMULATIONS));
+    const seasonGames = Math.round(positiveConfigNumber(config, "seasonGames", DEFAULT_REGULAR_SEASON_GAMES));
+    const otRate = configNumber(config, "overtimeRate", DEFAULT_OT_RATE);
+
     const participantIds = participantRows.map((r) => r.id);
 
     // 2. Build standings lookup, sourceElo map, and construct team entries.
@@ -336,7 +337,7 @@ export class NHLSimulator implements Simulator {
       const wins = standing?.wins ?? 0;
       const otLosses = standing?.otLosses ?? 0;
       const currentPoints = wins * 2 + otLosses;
-      const remainingGames = Math.max(0, NHL_REGULAR_SEASON_GAMES - gamesPlayed);
+      const remainingGames = Math.max(0, seasonGames - gamesPlayed);
       const resolvedElo = dbEloMap.get(r.id) ?? data?.elo ?? 1400;
 
       return {
@@ -347,7 +348,7 @@ export class NHLSimulator implements Simulator {
         division,
         currentPoints,
         remainingGames,
-        winProb: eloWinProbability(resolvedElo, 1500),
+        winProb: eloWinProbability(resolvedElo, 1500, parityFactor),
         resolvedElo,
       };
     });
@@ -381,40 +382,15 @@ export class NHLSimulator implements Simulator {
       );
     }
 
-    // ─── Futures odds blending ─────────────────────────────────────────────────
-
-    const participantIdSet = new Set(participantIds);
-    const oddsRows = evRows.filter(
-      (r) => r.sourceOdds !== null && participantIdSet.has(r.participantId)
-    );
-    const hasOdds = oddsRows.length > 0;
-
-    const normalizedOddsMap = new Map<string, number>();
-    if (hasOdds) {
-      const rawProbs = oddsRows.map((r) =>
-        convertAmericanOddsToProbability(r.sourceOdds ?? 0)
-      );
-      const normalized = normalizeProbabilities(rawProbs);
-      oddsRows.forEach(({ participantId }, i) => {
-        normalizedOddsMap.set(participantId, normalized[i]);
-      });
-    }
-
     // ─── Helpers (defined once, outside the hot loop) ─────────────────────────
 
     /**
-     * Blended per-game win probability for team A over team B.
-     * When odds are available: 70% Elo + 30% vig-removed futures head-to-head.
+     * Per-game win probability for team A over team B, from resolved Elo.
+     * Futures odds already influenced `elo()` via the central odds→Elo resolver,
+     * so they are not blended in again here.
      */
-    const gameWinProb = (a: TeamEntry, b: TeamEntry): number => {
-      const eloProb = eloWinProbability(elo(a), elo(b));
-      if (!hasOdds) return eloProb;
-
-      const o1 = normalizedOddsMap.get(a.id) ?? 0;
-      const o2 = normalizedOddsMap.get(b.id) ?? 0;
-      const oddsProb = o1 + o2 > 0 ? o1 / (o1 + o2) : 0.5;
-      return ELO_WEIGHT * eloProb + ODDS_WEIGHT * oddsProb;
-    };
+    const gameWinProb = (a: TeamEntry, b: TeamEntry): number =>
+      eloWinProbability(elo(a), elo(b), parityFactor);
 
     /** Simulate a best-of-7 series. Returns winner and loser. */
     const simSeries = (a: TeamEntry, b: TeamEntry): { winner: TeamEntry; loser: TeamEntry } => {
@@ -448,7 +424,7 @@ export class NHLSimulator implements Simulator {
 
       // Project all conference teams exactly once (single simulateProjectedPoints call per team).
       const divASet = new Set(divATeams.map((t) => t.id));
-      const allProjected = sortProjected([...divATeams, ...divBTeams].map(projectTeam));
+      const allProjected = sortProjected([...divATeams, ...divBTeams].map((t) => projectTeam(t, otRate)));
       const divAProjected = allProjected.filter((p) => divASet.has(p.team.id));
       const divBProjected = allProjected.filter((p) => !divASet.has(p.team.id));
 
@@ -487,7 +463,7 @@ export class NHLSimulator implements Simulator {
 
     let effectiveN = 0;
 
-    for (let s = 0; s < NUM_SIMULATIONS; s++) {
+    for (let s = 0; s < numSimulations; s++) {
       const eastBracket = buildConferenceBracket(easternAtlantic, easternMetro);
       const westBracket = buildConferenceBracket(westernCentral, westernPacific);
       if (!eastBracket || !westBracket) continue;
@@ -574,7 +550,8 @@ export class NHLSimulator implements Simulator {
 
   private async simulateBracket(
     sportsSeasonId: string,
-    allMatches: Awaited<ReturnType<ReturnType<typeof database>["query"]["playoffMatches"]["findMany"]>>
+    allMatches: Awaited<ReturnType<ReturnType<typeof database>["query"]["playoffMatches"]["findMany"]>>,
+    config: Record<string, unknown> = {}
   ): Promise<SimulationResult[]> {
     const db = database();
 
@@ -626,13 +603,15 @@ export class NHLSimulator implements Simulator {
       db
         .select({
           participantId: schema.seasonParticipantExpectedValues.participantId,
-          sourceOdds: schema.seasonParticipantExpectedValues.sourceOdds,
           sourceElo: schema.seasonParticipantExpectedValues.sourceElo,
         })
         .from(schema.seasonParticipantExpectedValues)
         .where(eq(schema.seasonParticipantExpectedValues.sportsSeasonId, sportsSeasonId)),
     ]);
 
+    const parityFactor = positiveConfigNumber(config, "parityFactor", DEFAULT_PARITY_FACTOR);
+    const numSimulations = Math.round(positiveConfigNumber(config, "iterations", DEFAULT_NUM_SIMULATIONS));
+
     const allParticipantIds = participantRows.map((r) => r.id);
 
     const dbEloMap = new Map<string, number>();
@@ -648,21 +627,6 @@ export class NHLSimulator implements Simulator {
       eloMap.set(r.id, dbEloMap.get(r.id) ?? getTeamData(r.name)?.elo ?? 1400);
     }
 
-    const participantIdSet = new Set(allParticipantIds);
-    const oddsRows = evRows.filter(
-      (r) => r.sourceOdds !== null && participantIdSet.has(r.participantId)
-    );
-    const hasOdds = oddsRows.length > 0;
-
-    const normalizedOddsMap = new Map<string, number>();
-    if (hasOdds) {
-      const rawProbs = oddsRows.map((r) => convertAmericanOddsToProbability(r.sourceOdds ?? 0));
-      const normalized = normalizeProbabilities(rawProbs);
-      oddsRows.forEach(({ participantId }, i) => {
-        normalizedOddsMap.set(participantId, normalized[i]);
-      });
-    }
-
     // Per-round lookup maps for O(1) access.
     const r1ByNum    = new Map(r1Matches.map((m) => [m.matchNumber, m]));
     const r2ByNum    = new Map(r2Matches.map((m) => [m.matchNumber, m]));
@@ -671,14 +635,10 @@ export class NHLSimulator implements Simulator {
 
     // ── Helpers ──────────────────────────────────────────────────────────────────
 
-    const gameWinProb = (aId: string, bId: string): number => {
-      const eloProb = eloWinProbability(eloMap.get(aId) ?? 1400, eloMap.get(bId) ?? 1400);
-      if (!hasOdds) return eloProb;
-      const o1 = normalizedOddsMap.get(aId) ?? 0;
-      const o2 = normalizedOddsMap.get(bId) ?? 0;
-      const oddsProb = o1 + o2 > 0 ? o1 / (o1 + o2) : 0.5;
-      return ELO_WEIGHT * eloProb + ODDS_WEIGHT * oddsProb;
-    };
+    // Futures odds already shaped each team's resolved Elo via the central
+    // odds→Elo resolver, so per-game probability is pure Elo (no odds re-blend).
+    const gameWinProb = (aId: string, bId: string): number =>
+      eloWinProbability(eloMap.get(aId) ?? 1400, eloMap.get(bId) ?? 1400, parityFactor);
 
     const simSeries = (aId: string, bId: string): { winner: string; loser: string } => {
       const winProb = gameWinProb(aId, bId);
@@ -718,7 +678,7 @@ export class NHLSimulator implements Simulator {
 
     // ── Monte Carlo simulation loop ───────────────────────────────────────────────
 
-    for (let s = 0; s < NUM_SIMULATIONS; s++) {
+    for (let s = 0; s < numSimulations; s++) {
       // Round 1: R1 losers score 0 points — not tracked.
       const r1Winners: string[] = [];
       for (let i = 1; i <= 8; i++) {
@@ -758,7 +718,7 @@ export class NHLSimulator implements Simulator {
 
     // ── Convert counts to probability distributions ───────────────────────────────
 
-    const N = NUM_SIMULATIONS;
+    const N = numSimulations;
     const results: SimulationResult[] = allParticipantIds.map((participantId) => {
       const c  = championCounts.get(participantId) ?? 0;
       const f  = finalistCounts.get(participantId) ?? 0;
diff --git a/app/services/simulations/nll-simulator.ts b/app/services/simulations/nll-simulator.ts
index 47c134f..c4c3102 100644
--- a/app/services/simulations/nll-simulator.ts
+++ b/app/services/simulations/nll-simulator.ts
@@ -43,10 +43,11 @@ import { eloWinProbabilityWithParity } from "~/services/probability-engine";
 import { getRegularSeasonStandings } from "~/models/regular-season-standings";
 import { getParticipantSimulatorInputs } from "~/models/simulator";
 import { logger } from "~/lib/logger";
+import { positiveConfigNumber } from "./config-access";
 
-// ─── Simulation parameters ────────────────────────────────────────────────────
+// ─── Simulation parameters (defaults; overridable via season config) ───────────
 
-const NUM_SIMULATIONS = 50_000;
+const DEFAULT_NUM_SIMULATIONS = 50_000;
 const NLL_REGULAR_SEASON_GAMES = 18;
 const NLL_PLAYOFF_TEAMS = 8;
 const PARITY_FACTOR = 400;
@@ -216,7 +217,8 @@ export function simulateNllPlayoffs(
  */
 export function resolveQfMatch(
   match: MatchSnapshot | undefined,
-  eloMap: Map<string, number>
+  eloMap: Map<string, number>,
+  parityFactor = PARITY_FACTOR
 ): { winner: string; loser: string } {
   if (match?.isComplete && match.winnerId && match.loserId) {
     return { winner: match.winnerId, loser: match.loserId };
@@ -231,7 +233,8 @@ export function resolveQfMatch(
   }
   const result = simulateNllGame(
     { participantId: p1, elo: eloMap.get(p1) ?? FALLBACK_ELO },
-    { participantId: p2, elo: eloMap.get(p2) ?? FALLBACK_ELO }
+    { participantId: p2, elo: eloMap.get(p2) ?? FALLBACK_ELO },
+    parityFactor
   );
   return { winner: result.winner.participantId, loser: result.loser.participantId };
 }
@@ -249,7 +252,8 @@ export function resolveBo3Match(
   games: GameSnapshot[],
   eloMap: Map<string, number>,
   p1Override?: string,
-  p2Override?: string
+  p2Override?: string,
+  parityFactor = PARITY_FACTOR
 ): { winner: string; loser: string } {
   if (match?.isComplete && match.winnerId && match.loserId) {
     return { winner: match.winnerId, loser: match.loserId };
@@ -278,7 +282,7 @@ export function resolveBo3Match(
   const { winner, loser } = simulateBestOfThree(
     { participantId: p1, elo: eloMap.get(p1) ?? FALLBACK_ELO },
     { participantId: p2, elo: eloMap.get(p2) ?? FALLBACK_ELO },
-    PARITY_FACTOR,
+    parityFactor,
     { winsA: winsP1, winsB: winsP2 }
   );
   return { winner: winner.participantId, loser: loser.participantId };
@@ -354,8 +358,10 @@ export function simulateRegularSeasonSeeds(
 // ─── Simulator class ──────────────────────────────────────────────────────────
 
 export class NLLSimulator implements Simulator {
-  async simulate(sportsSeasonId: string): Promise<SimulationResult[]> {
+  async simulate(sportsSeasonId: string, config: Record<string, unknown> = {}): Promise<SimulationResult[]> {
     const db = database();
+    const parityFactor = positiveConfigNumber(config, "parityFactor", PARITY_FACTOR);
+    const numSimulations = Math.round(positiveConfigNumber(config, "iterations", DEFAULT_NUM_SIMULATIONS));
 
     // ── Load participants ─────────────────────────────────────────────────────
     const participants = await db.query.seasonParticipants.findMany({
@@ -421,7 +427,7 @@ export class NLLSimulator implements Simulator {
       });
 
       if (bracketMatches.length > 0) {
-        return this.simulateBracketAware(allIds, eloMap, bracketMatches);
+        return this.simulateBracketAware(allIds, eloMap, bracketMatches, parityFactor, numSimulations);
       }
     }
 
@@ -439,7 +445,7 @@ export class NLLSimulator implements Simulator {
       knownSeeds.length === NLL_PLAYOFF_TEAMS &&
       new Set(knownSeeds.map((s) => s.seed)).size === NLL_PLAYOFF_TEAMS
     ) {
-      return this.simulateKnownSeeds(allIds, knownSeeds);
+      return this.simulateKnownSeeds(allIds, knownSeeds, parityFactor, numSimulations);
     }
 
     // Mode 3: regular-season projection (default, including preseason).
@@ -466,7 +472,7 @@ export class NLLSimulator implements Simulator {
       );
     }
 
-    return this.simulateRegularSeason(allIds, teams);
+    return this.simulateRegularSeason(allIds, teams, parityFactor, numSimulations);
   }
 
   // ── Mode 1: Bracket-Aware ─────────────────────────────────────────────────
@@ -474,7 +480,9 @@ export class NLLSimulator implements Simulator {
   private async simulateBracketAware(
     allIds: string[],
     eloMap: Map<string, number>,
-    allMatches: typeof schema.playoffMatches.$inferSelect[]
+    allMatches: typeof schema.playoffMatches.$inferSelect[],
+    parityFactor = PARITY_FACTOR,
+    numSimulations = DEFAULT_NUM_SIMULATIONS
   ): Promise<SimulationResult[]> {
     const db = database();
 
@@ -535,18 +543,18 @@ export class NLLSimulator implements Simulator {
     const [sf1, sf2] = sfMatches;
     const finalMatch = finalMatches[0];
 
-    for (let s = 0; s < NUM_SIMULATIONS; s++) {
-      const r_qf1 = resolveQfMatch(qf1, eloMap);
-      const r_qf2 = resolveQfMatch(qf2, eloMap);
-      const r_qf3 = resolveQfMatch(qf3, eloMap);
-      const r_qf4 = resolveQfMatch(qf4, eloMap);
+    for (let s = 0; s < numSimulations; s++) {
+      const r_qf1 = resolveQfMatch(qf1, eloMap, parityFactor);
+      const r_qf2 = resolveQfMatch(qf2, eloMap, parityFactor);
+      const r_qf3 = resolveQfMatch(qf3, eloMap, parityFactor);
+      const r_qf4 = resolveQfMatch(qf4, eloMap, parityFactor);
 
       // SF arm A: QF1 winner vs QF2 winner (1/8 vs 4/5 bracket arm)
-      const r_sf1 = resolveBo3Match(sf1, gamesByMatch.get(sf1.id) ?? [], eloMap, r_qf1.winner, r_qf2.winner);
+      const r_sf1 = resolveBo3Match(sf1, gamesByMatch.get(sf1.id) ?? [], eloMap, r_qf1.winner, r_qf2.winner, parityFactor);
       // SF arm B: QF3 winner vs QF4 winner (2/7 vs 3/6 bracket arm)
-      const r_sf2 = resolveBo3Match(sf2, gamesByMatch.get(sf2.id) ?? [], eloMap, r_qf3.winner, r_qf4.winner);
+      const r_sf2 = resolveBo3Match(sf2, gamesByMatch.get(sf2.id) ?? [], eloMap, r_qf3.winner, r_qf4.winner, parityFactor);
 
-      const r_final = resolveBo3Match(finalMatch, gamesByMatch.get(finalMatch.id) ?? [], eloMap, r_sf1.winner, r_sf2.winner);
+      const r_final = resolveBo3Match(finalMatch, gamesByMatch.get(finalMatch.id) ?? [], eloMap, r_sf1.winner, r_sf2.winner, parityFactor);
 
       championCounts.set(r_final.winner, (championCounts.get(r_final.winner) ?? 0) + 1);
       finalistCounts.set(r_final.loser, (finalistCounts.get(r_final.loser) ?? 0) + 1);
@@ -558,22 +566,24 @@ export class NLLSimulator implements Simulator {
       qfLoserCounts.set(r_qf4.loser, (qfLoserCounts.get(r_qf4.loser) ?? 0) + 1);
     }
 
-    return this.buildResults(allIds, championCounts, finalistCounts, sfLoserCounts, qfLoserCounts);
+    return this.buildResults(allIds, championCounts, finalistCounts, sfLoserCounts, qfLoserCounts, numSimulations);
   }
 
   // ── Mode 2: Known-Seed ────────────────────────────────────────────────────
 
   private simulateKnownSeeds(
     allIds: string[],
-    seeds: SeedEntry[]
+    seeds: SeedEntry[],
+    parityFactor = PARITY_FACTOR,
+    numSimulations = DEFAULT_NUM_SIMULATIONS
   ): SimulationResult[] {
     const championCounts = new Map(allIds.map((id) => [id, 0]));
     const finalistCounts = new Map(allIds.map((id) => [id, 0]));
     const sfLoserCounts = new Map(allIds.map((id) => [id, 0]));
     const qfLoserCounts = new Map(allIds.map((id) => [id, 0]));
 
-    for (let s = 0; s < NUM_SIMULATIONS; s++) {
-      const result = simulateNllPlayoffs(seeds);
+    for (let s = 0; s < numSimulations; s++) {
+      const result = simulateNllPlayoffs(seeds, parityFactor);
       championCounts.set(result.champion, (championCounts.get(result.champion) ?? 0) + 1);
       finalistCounts.set(result.finalist, (finalistCounts.get(result.finalist) ?? 0) + 1);
       for (const id of result.sfLosers) {
@@ -584,23 +594,25 @@ export class NLLSimulator implements Simulator {
       }
     }
 
-    return this.buildResults(allIds, championCounts, finalistCounts, sfLoserCounts, qfLoserCounts);
+    return this.buildResults(allIds, championCounts, finalistCounts, sfLoserCounts, qfLoserCounts, numSimulations);
   }
 
   // ── Mode 3: Regular-Season Projection ────────────────────────────────────
 
   private simulateRegularSeason(
     allIds: string[],
-    teams: TeamProjection[]
+    teams: TeamProjection[],
+    parityFactor = PARITY_FACTOR,
+    numSimulations = DEFAULT_NUM_SIMULATIONS
   ): SimulationResult[] {
     const championCounts = new Map(allIds.map((id) => [id, 0]));
     const finalistCounts = new Map(allIds.map((id) => [id, 0]));
     const sfLoserCounts = new Map(allIds.map((id) => [id, 0]));
     const qfLoserCounts = new Map(allIds.map((id) => [id, 0]));
 
-    for (let s = 0; s < NUM_SIMULATIONS; s++) {
-      const seeds = simulateRegularSeasonSeeds(teams);
-      const result = simulateNllPlayoffs(seeds);
+    for (let s = 0; s < numSimulations; s++) {
+      const seeds = simulateRegularSeasonSeeds(teams, parityFactor);
+      const result = simulateNllPlayoffs(seeds, parityFactor);
       championCounts.set(result.champion, (championCounts.get(result.champion) ?? 0) + 1);
       finalistCounts.set(result.finalist, (finalistCounts.get(result.finalist) ?? 0) + 1);
       for (const id of result.sfLosers) {
@@ -611,7 +623,7 @@ export class NLLSimulator implements Simulator {
       }
     }
 
-    return this.buildResults(allIds, championCounts, finalistCounts, sfLoserCounts, qfLoserCounts);
+    return this.buildResults(allIds, championCounts, finalistCounts, sfLoserCounts, qfLoserCounts, numSimulations);
   }
 
   // ── Shared result builder ─────────────────────────────────────────────────
@@ -621,9 +633,10 @@ export class NLLSimulator implements Simulator {
     championCounts: Map<string, number>,
     finalistCounts: Map<string, number>,
     sfLoserCounts: Map<string, number>,
-    qfLoserCounts: Map<string, number>
+    qfLoserCounts: Map<string, number>,
+    numSimulations = DEFAULT_NUM_SIMULATIONS
   ): SimulationResult[] {
-    const N = NUM_SIMULATIONS;
+    const N = numSimulations;
     return allIds.map((id) => ({
       participantId: id,
       probabilities: {
diff --git a/app/services/simulations/runner.ts b/app/services/simulations/runner.ts
index beb8688..3c4fa45 100644
--- a/app/services/simulations/runner.ts
+++ b/app/services/simulations/runner.ts
@@ -105,7 +105,7 @@ export async function runSportsSeasonSimulation(
 
   try {
     const simulator = getSimulator(simulatorConfig.simulatorType);
-    const results = await simulator.simulate(sportsSeasonId);
+    const results = await simulator.simulate(sportsSeasonId, simulatorConfig.config);
 
     if (results.length === 0) {
       throw new Error("Simulation returned no results. Check that participants have simulator input data.");
diff --git a/app/services/simulations/snooker-simulator.ts b/app/services/simulations/snooker-simulator.ts
index 2b4db9a..5447b94 100644
--- a/app/services/simulations/snooker-simulator.ts
+++ b/app/services/simulations/snooker-simulator.ts
@@ -41,10 +41,11 @@ import { database } from "~/database/context";
 import { eq, and } from "drizzle-orm";
 import * as schema from "~/database/schema";
 import type { Simulator, SimulationResult } from "./types";
+import { positiveConfigNumber } from "./config-access";
 
 // ─── Simulation parameters ────────────────────────────────────────────────────
 
-const NUM_SIMULATIONS = 50000;
+const DEFAULT_NUM_SIMULATIONS = 50000;
 
 /**
  * Controls how much Elo gaps affect per-frame win probability.
@@ -229,7 +230,8 @@ function shuffle<T>(arr: T[]): T[] {
 // ─── Simulator ────────────────────────────────────────────────────────────────
 
 export class SnookerSimulator implements Simulator {
-  async simulate(sportsSeasonId: string): Promise<SimulationResult[]> {
+  async simulate(sportsSeasonId: string, config: Record<string, unknown> = {}): Promise<SimulationResult[]> {
+    const numSimulations = Math.round(positiveConfigNumber(config, "iterations", DEFAULT_NUM_SIMULATIONS));
     const db = database();
 
     // 1. Find the bracket scoring event for this sports season.
@@ -272,9 +274,9 @@ export class SnookerSimulator implements Simulator {
       allMatches.some((m) => m.participant1Id && m.participant2Id);
 
     if (bracketPopulated) {
-      return this.simulateBracket(allMatches, eloMap);
+      return this.simulateBracket(allMatches, eloMap, numSimulations);
     } else {
-      return this.simulatePreBracket(sportsSeasonId, eloMap, db);
+      return this.simulatePreBracket(sportsSeasonId, eloMap, db, numSimulations);
     }
   }
 
@@ -282,7 +284,8 @@ export class SnookerSimulator implements Simulator {
 
   private async simulateBracket(
     allMatches: Awaited<ReturnType<ReturnType<typeof database>["query"]["playoffMatches"]["findMany"]>>,
-    eloMap: Map<string, number>
+    eloMap: Map<string, number>,
+    numSimulations: number
   ): Promise<SimulationResult[]> {
     // Group matches by round, sorted by match count descending (R32 first).
     const byRound = new Map<string, typeof allMatches>();
@@ -354,7 +357,7 @@ export class SnookerSimulator implements Simulator {
     const sfLoserCounts   = new Map<string, number>(participantIds.map((id) => [id, 0]));
     const qfLoserCounts   = new Map<string, number>(participantIds.map((id) => [id, 0]));
 
-    for (let s = 0; s < NUM_SIMULATIONS; s++) {
+    for (let s = 0; s < numSimulations; s++) {
       // ── First Round (R32) ──────────────────────────────────────────────────
       const r32Winners: string[] = [];
       for (let i = 1; i <= 16; i++) {
@@ -433,7 +436,7 @@ export class SnookerSimulator implements Simulator {
       finalistCounts.set(finalist, (finalistCounts.get(finalist) ?? 0) + 1);
     }
 
-    return buildResults(participantIds, NUM_SIMULATIONS, {
+    return buildResults(participantIds, numSimulations, {
       championCounts,
       finalistCounts,
       sfLoserCounts,
@@ -450,7 +453,8 @@ export class SnookerSimulator implements Simulator {
   private async simulatePreBracket(
     sportsSeasonId: string,
     eloMap: Map<string, number>,
-    db: ReturnType<typeof database>
+    db: ReturnType<typeof database>,
+    numSimulations: number
   ): Promise<SimulationResult[]> {
     const allParticipants = await db
       .select({ id: schema.seasonParticipants.id, name: schema.seasonParticipants.name })
@@ -500,7 +504,7 @@ export class SnookerSimulator implements Simulator {
     // are in the DB), skip the qualifying simulation and use them directly as seeds 17-32.
     const needsQualifying = qualifiers.length > 16;
 
-    for (let s = 0; s < NUM_SIMULATIONS; s++) {
+    for (let s = 0; s < numSimulations; s++) {
       // ── Qualifying: run elimination rounds until exactly 16 qualifiers remain ──
       let drawnQualifiers: string[];
       if (!needsQualifying) {
@@ -579,7 +583,7 @@ export class SnookerSimulator implements Simulator {
       finalistCounts.set(finalist, (finalistCounts.get(finalist) ?? 0) + 1);
     }
 
-    return buildResults(allParticipantIds, NUM_SIMULATIONS, {
+    return buildResults(allParticipantIds, numSimulations, {
       championCounts,
       finalistCounts,
       sfLoserCounts,
diff --git a/app/services/simulations/tennis-simulator.ts b/app/services/simulations/tennis-simulator.ts
index eb8230e..d6e4fd0 100644
--- a/app/services/simulations/tennis-simulator.ts
+++ b/app/services/simulations/tennis-simulator.ts
@@ -48,10 +48,11 @@ import { getQPConfig, calculateSplitQualifyingPoints } from "~/models/qualifying
 import { resolveStructureSource, type IdTranslator } from "./shared-major";
 import { BRACKET_TEMPLATES } from "~/lib/bracket-templates";
 import type { Simulator, SimulationResult } from "./types";
+import { positiveConfigNumber } from "./config-access";
 
 // ─── Simulation parameters ────────────────────────────────────────────────────
 
-const NUM_SIMULATIONS = 10_000;
+const DEFAULT_NUM_SIMULATIONS = 10_000;
 
 /**
  * Elo divisor for per-match win probability.
@@ -363,7 +364,8 @@ export function drawFromBracket(
 // ─── Simulator ────────────────────────────────────────────────────────────────
 
 export class TennisSimulator implements Simulator {
-  async simulate(sportsSeasonId: string): Promise<SimulationResult[]> {
+  async simulate(sportsSeasonId: string, config: Record<string, unknown> = {}): Promise<SimulationResult[]> {
+    const numSimulations = Math.round(positiveConfigNumber(config, "iterations", DEFAULT_NUM_SIMULATIONS));
     const db = database();
 
     // 1. Load all participants for this sports season.
@@ -505,7 +507,7 @@ export class TennisSimulator implements Simulator {
     const counts: number[][] = Array.from({ length: participantIds.length }, () => Array.from({ length: 8 }, () => 0));
     const idToIndex = new Map<string, number>(participantIds.map((id, i) => [id, i]));
 
-    for (let sim = 0; sim < NUM_SIMULATIONS; sim++) {
+    for (let sim = 0; sim < numSimulations; sim++) {
       // Start each simulation from the locked actual QP.
       const simQP = new Map<string, number>(actualQPMap);
 
@@ -551,14 +553,14 @@ export class TennisSimulator implements Simulator {
     return participantIds.map((participantId, i) => ({
       participantId,
       probabilities: {
-        probFirst:   counts[i][0] / NUM_SIMULATIONS,
-        probSecond:  counts[i][1] / NUM_SIMULATIONS,
-        probThird:   counts[i][2] / NUM_SIMULATIONS,
-        probFourth:  counts[i][3] / NUM_SIMULATIONS,
-        probFifth:   counts[i][4] / NUM_SIMULATIONS,
-        probSixth:   counts[i][5] / NUM_SIMULATIONS,
-        probSeventh: counts[i][6] / NUM_SIMULATIONS,
-        probEighth:  counts[i][7] / NUM_SIMULATIONS,
+        probFirst:   counts[i][0] / numSimulations,
+        probSecond:  counts[i][1] / numSimulations,
+        probThird:   counts[i][2] / numSimulations,
+        probFourth:  counts[i][3] / numSimulations,
+        probFifth:   counts[i][4] / numSimulations,
+        probSixth:   counts[i][5] / numSimulations,
+        probSeventh: counts[i][6] / numSimulations,
+        probEighth:  counts[i][7] / numSimulations,
       },
       source: "tennis_grand_slam_monte_carlo",
     }));
diff --git a/app/services/simulations/types.ts b/app/services/simulations/types.ts
index d2b3ed0..bdb4555 100644
--- a/app/services/simulations/types.ts
+++ b/app/services/simulations/types.ts
@@ -33,7 +33,12 @@ export interface SimulationResult {
  * Simulators consume a single resolved Elo per participant (already blended from
  * its sources — raw Elo, projections, futures odds — by the input policy and
  * persisted before the run), so they need only the season id.
+ *
+ * `config` is the merged simulator config (profile defaults overlaid with the
+ * season's overrides) that the runner has already fetched. It carries the engine
+ * knobs (`iterations`, `parityFactor`, `seasonGames`, …). It is optional so unit
+ * tests can call `simulate(id)` and get each simulator's built-in defaults.
  */
 export interface Simulator {
-  simulate(sportsSeasonId: string): Promise<SimulationResult[]>;
+  simulate(sportsSeasonId: string, config?: Record<string, unknown>): Promise<SimulationResult[]>;
 }
diff --git a/app/services/simulations/ucl-simulator.ts b/app/services/simulations/ucl-simulator.ts
index 6836b3f..682fa89 100644
--- a/app/services/simulations/ucl-simulator.ts
+++ b/app/services/simulations/ucl-simulator.ts
@@ -5,12 +5,12 @@
  *
  * Algorithm:
  *   1. Load the bracket scoring event and all playoff matches from DB
- *   2. Load futures odds (American format) from participantExpectedValues
- *   3. Build two probability signals per team:
- *      a. Elo — derived from futures via convertFuturesToElo() (long-run team strength)
- *      b. Normalized odds — vig-removed implied win probability from the same futures
- *   4. Per-match win probability = ELO_WEIGHT * eloProb + ODDS_WEIGHT * oddsProb
- *   5. Simulate 50,000 tournaments, respecting already-completed matches
+ *   2. Load each team's resolved Elo (the input policy already blended any raw
+ *      Elo and futures odds into a single sourceElo before the run)
+ *   3. Per-match win probability = eloWinProbabilityWithParity(eloA, eloB, parityFactor).
+ *      Odds are NOT blended in per-match here — that would double-count the futures
+ *      signal already baked into the Elo.
+ *   5. Simulate `iterations` tournaments, respecting already-completed matches
  *   6. Track integer placement counts per tier (champion / finalist / SF loser / QF loser).
  *      At conversion, exact denominators guarantee column sums of 1.0 by construction:
  *      - probFirst           = champion / N
@@ -30,19 +30,23 @@
  *
  * Notes:
  *   - Requires futures odds in sourceOdds (American format) to be imported first.
- *   - Falls back to uniform probability (coin flip) when no odds are stored.
- *   - ELO_WEIGHT and ODDS_WEIGHT can be tuned here; 0.7/0.3 matches the Python calibration.
+ *   - Falls back to a 1500 Elo (coin flip vs. equals) when no Elo is resolved.
+ *   - `parityFactor` (season config) tunes per-match variance; default 400.
  */
 
 import { database } from "~/database/context";
 import { eq, and } from "drizzle-orm";
 import * as schema from "~/database/schema";
-import { eloWinProbability } from "~/services/probability-engine";
+import { eloWinProbabilityWithParity } from "~/services/probability-engine";
 import type { Simulator, SimulationResult } from "./types";
+import { positiveConfigNumber } from "./config-access";
 
-// ─── Simulation parameters ────────────────────────────────────────────────────
+// ─── Simulation parameters (defaults; overridable via season config) ───────────
 
-const NUM_SIMULATIONS = 50000;
+const DEFAULT_NUM_SIMULATIONS = 50000;
+
+/** Elo parity factor. Defaults to 400 (standard formula). */
+const DEFAULT_PARITY_FACTOR = 400;
 
 // ─── Odds helper ──────────────────────────────────────────────────────────────
 
@@ -55,8 +59,10 @@ export function americanToImpliedProb(odds: number): number {
 // ─── Simulator ────────────────────────────────────────────────────────────────
 
 export class UCLSimulator implements Simulator {
-  async simulate(sportsSeasonId: string): Promise<SimulationResult[]> {
+  async simulate(sportsSeasonId: string, config: Record<string, unknown> = {}): Promise<SimulationResult[]> {
     const db = database();
+    const parityFactor = positiveConfigNumber(config, "parityFactor", DEFAULT_PARITY_FACTOR);
+    const numSimulations = Math.round(positiveConfigNumber(config, "iterations", DEFAULT_NUM_SIMULATIONS));
 
     // 1. Find the bracket scoring event for this sports season.
     //    UCL has exactly one playoff_game event per season.
@@ -166,7 +172,7 @@ export class UCLSimulator implements Simulator {
     const blendedWinProb = (p1: string, p2: string): number => {
       const elo1 = eloMap.get(p1) ?? 1500;
       const elo2 = eloMap.get(p2) ?? 1500;
-      return eloWinProbability(elo1, elo2);
+      return eloWinProbabilityWithParity(elo1, elo2, parityFactor);
     };
 
     const simMatch = (p1: string, p2: string): { winner: string; loser: string } => {
@@ -183,7 +189,7 @@ export class UCLSimulator implements Simulator {
     const qfLoserCounts  = new Map<string, number>(participantIds.map((id) => [id, 0]));
 
     // 10. Run Monte Carlo simulations.
-    for (let s = 0; s < NUM_SIMULATIONS; s++) {
+    for (let s = 0; s < numSimulations; s++) {
       // ── Round of 16 ──────────────────────────────────────────────────────
       // R16 losers: no count added (0 points per scoring rules)
       const r16Winners: string[] = [];
@@ -261,7 +267,7 @@ export class UCLSimulator implements Simulator {
     //       probFirst/Second  → N total (1 per sim)
     //       probThird/Fourth  → sfLoserCounts / (2*N)  — 2 SF losers per sim
     //       probFifth–Eighth  → qfLoserCounts / (4*N)  — 4 QF losers per sim
-    const N = NUM_SIMULATIONS;
+    const N = numSimulations;
     const results: SimulationResult[] = participantIds.map((participantId) => {
       const c = championCounts.get(participantId) ?? 0;
       const f = finalistCounts.get(participantId) ?? 0;
diff --git a/app/services/simulations/wnba-simulator.ts b/app/services/simulations/wnba-simulator.ts
index 98b36a1..df5c454 100644
--- a/app/services/simulations/wnba-simulator.ts
+++ b/app/services/simulations/wnba-simulator.ts
@@ -53,14 +53,18 @@ import * as schema from "~/database/schema";
 import type { Simulator, SimulationResult } from "./types";
 import { normalizeTeamName } from "~/lib/normalize-team-name";
 import { getRegularSeasonStandings } from "~/models/regular-season-standings";
-import { convertFuturesToElo, eloWinProbability } from "~/services/probability-engine";
+import { convertFuturesToElo, eloWinProbabilityWithParity } from "~/services/probability-engine";
+import { positiveConfigNumber } from "./config-access";
 
-// ─── Simulation parameters ────────────────────────────────────────────────────
+// ─── Simulation parameters (defaults; overridable via season config) ───────────
 
-const NUM_SIMULATIONS = 50_000;
+const DEFAULT_NUM_SIMULATIONS = 50_000;
+
+/** Elo parity factor. WNBA defaults to 400 (standard formula). */
+const DEFAULT_PARITY_FACTOR = 400;
 
 /** WNBA regular season games per team. */
-const WNBA_REGULAR_SEASON_GAMES = 40;
+const DEFAULT_REGULAR_SEASON_GAMES = 40;
 
 /**
  * Multiplier converting SRS to Elo offset from 1500.
@@ -129,9 +133,10 @@ interface TeamEntry {
 export function simSeriesN(
   a: TeamEntry,
   b: TeamEntry,
-  winTarget: number
+  winTarget: number,
+  parityFactor = DEFAULT_PARITY_FACTOR
 ): { winner: TeamEntry; loser: TeamEntry } {
-  const winProb = eloWinProbability(a.elo, b.elo);
+  const winProb = eloWinProbabilityWithParity(a.elo, b.elo, parityFactor);
   let winsA = 0;
   let winsB = 0;
   while (winsA < winTarget && winsB < winTarget) {
@@ -153,8 +158,11 @@ function simulateProjectedWins(team: TeamEntry): number {
 // ─── Simulator ────────────────────────────────────────────────────────────────
 
 export class WNBASimulator implements Simulator {
-  async simulate(sportsSeasonId: string): Promise<SimulationResult[]> {
+  async simulate(sportsSeasonId: string, config: Record<string, unknown> = {}): Promise<SimulationResult[]> {
     const db = database();
+    const parityFactor = positiveConfigNumber(config, "parityFactor", DEFAULT_PARITY_FACTOR);
+    const numSimulations = Math.round(positiveConfigNumber(config, "iterations", DEFAULT_NUM_SIMULATIONS));
+    const seasonGames = Math.round(positiveConfigNumber(config, "seasonGames", DEFAULT_REGULAR_SEASON_GAMES));
 
     // 1. Load participants, standings, and futures odds in parallel.
     const [participantRows, standings, evRows] = await Promise.all([
@@ -228,8 +236,8 @@ export class WNBASimulator implements Simulator {
         name: r.name,
         elo,
         currentWins: standing?.wins ?? 0,
-        remainingGames: Math.max(0, WNBA_REGULAR_SEASON_GAMES - gamesPlayed),
-        winProb: eloWinProbability(elo, 1500),
+        remainingGames: Math.max(0, seasonGames - gamesPlayed),
+        winProb: eloWinProbabilityWithParity(elo, 1500, parityFactor),
       };
     });
 
@@ -255,14 +263,14 @@ export class WNBASimulator implements Simulator {
     const r1LoserCounts    = new Map<string, number>(participantIds.map((id) => [id, 0]));
 
     // 6. Monte Carlo simulation loop.
-    for (let s = 0; s < NUM_SIMULATIONS; s++) {
+    for (let s = 0; s < numSimulations; s++) {
       const [s1, s2, s3, s4, s5, s6, s7, s8] = buildSeededBracket();
 
       // Round 1 (best-of-3): 1v8, 4v5, 2v7, 3v6
-      const r1_a = simSeriesN(s1, s8, 2);
-      const r1_b = simSeriesN(s4, s5, 2);
-      const r1_c = simSeriesN(s2, s7, 2);
-      const r1_d = simSeriesN(s3, s6, 2);
+      const r1_a = simSeriesN(s1, s8, 2, parityFactor);
+      const r1_b = simSeriesN(s4, s5, 2, parityFactor);
+      const r1_c = simSeriesN(s2, s7, 2, parityFactor);
+      const r1_d = simSeriesN(s3, s6, 2, parityFactor);
 
       r1LoserCounts.set(r1_a.loser.id, (r1LoserCounts.get(r1_a.loser.id) ?? 0) + 1);
       r1LoserCounts.set(r1_b.loser.id, (r1LoserCounts.get(r1_b.loser.id) ?? 0) + 1);
@@ -270,14 +278,14 @@ export class WNBASimulator implements Simulator {
       r1LoserCounts.set(r1_d.loser.id, (r1LoserCounts.get(r1_d.loser.id) ?? 0) + 1);
 
       // Semifinals (best-of-5): winner(1/8) vs winner(4/5), winner(2/7) vs winner(3/6)
-      const sf_a = simSeriesN(r1_a.winner, r1_b.winner, 3);
-      const sf_b = simSeriesN(r1_c.winner, r1_d.winner, 3);
+      const sf_a = simSeriesN(r1_a.winner, r1_b.winner, 3, parityFactor);
+      const sf_b = simSeriesN(r1_c.winner, r1_d.winner, 3, parityFactor);
 
       semiLoserCounts.set(sf_a.loser.id, (semiLoserCounts.get(sf_a.loser.id) ?? 0) + 1);
       semiLoserCounts.set(sf_b.loser.id, (semiLoserCounts.get(sf_b.loser.id) ?? 0) + 1);
 
       // Finals (best-of-7)
-      const final = simSeriesN(sf_a.winner, sf_b.winner, 4);
+      const final = simSeriesN(sf_a.winner, sf_b.winner, 4, parityFactor);
 
       championCounts.set(final.winner.id, (championCounts.get(final.winner.id) ?? 0) + 1);
       finalistCounts.set(final.loser.id,  (finalistCounts.get(final.loser.id) ?? 0)  + 1);
@@ -292,14 +300,14 @@ export class WNBASimulator implements Simulator {
       return {
         participantId,
         probabilities: {
-          probFirst:   c  / NUM_SIMULATIONS,
-          probSecond:  f  / NUM_SIMULATIONS,
-          probThird:   sl / (2 * NUM_SIMULATIONS),
-          probFourth:  sl / (2 * NUM_SIMULATIONS),
-          probFifth:   r1 / (4 * NUM_SIMULATIONS),
-          probSixth:   r1 / (4 * NUM_SIMULATIONS),
-          probSeventh: r1 / (4 * NUM_SIMULATIONS),
-          probEighth:  r1 / (4 * NUM_SIMULATIONS),
+          probFirst:   c  / numSimulations,
+          probSecond:  f  / numSimulations,
+          probThird:   sl / (2 * numSimulations),
+          probFourth:  sl / (2 * numSimulations),
+          probFifth:   r1 / (4 * numSimulations),
+          probSixth:   r1 / (4 * numSimulations),
+          probSeventh: r1 / (4 * numSimulations),
+          probEighth:  r1 / (4 * numSimulations),
         },
         source,
       };
diff --git a/app/services/simulations/world-cup-simulator.ts b/app/services/simulations/world-cup-simulator.ts
index 2927eb1..ff3e928 100644
--- a/app/services/simulations/world-cup-simulator.ts
+++ b/app/services/simulations/world-cup-simulator.ts
@@ -39,6 +39,7 @@ import { database } from "~/database/context";
 import { eq, and } from "drizzle-orm";
 import * as schema from "~/database/schema";
 import { eloWinProbability } from "~/services/probability-engine";
+import { positiveConfigNumber } from "./config-access";
 import { simulateEloSoccerMatch } from "./soccer-helpers";
 import { normalizeSimulationResultColumns } from "./simulation-probabilities";
 import { logger } from "~/lib/logger";
@@ -440,8 +441,9 @@ export class WorldCupSimulator implements Simulator {
     this.numSimulations = numSimulations;
   }
 
-  async simulate(sportsSeasonId: string): Promise<SimulationResult[]> {
+  async simulate(sportsSeasonId: string, config: Record<string, unknown> = {}): Promise<SimulationResult[]> {
     const db = database();
+    const numSimulations = Math.round(positiveConfigNumber(config, "iterations", this.numSimulations));
 
     // 1. Load all participants for this season
     const participantRows = await db.query.seasonParticipants.findMany({
@@ -669,7 +671,7 @@ export class WorldCupSimulator implements Simulator {
       return seeded;
     };
 
-    for (let sim = 0; sim < this.numSimulations; sim++) {
+    for (let sim = 0; sim < numSimulations; sim++) {
       // ── Knockout rounds ──────────────────────────────────────────
       // R32 → R16 → QF → SF → Third Place Game + Final, advancing via the
       // canonical ceil(n/2) tree. Completed matches lock in real results.
@@ -719,7 +721,7 @@ export class WorldCupSimulator implements Simulator {
     }
 
     // 9. Convert counts to probabilities
-    const N = this.numSimulations;
+    const N = numSimulations;
     const numQfLosers = 4; // 4 QF losers per sim
 
     const source =