brackt/app/services/simulations/cs-major-simulator.ts
Claude 8990bf4281
Condition CS2 Major simulator on already-known results
The CS2 Major projected-points simulator re-simulated outcomes that had
already happened, so its projections drifted from reality as a major
played out. Specifically it ignored the Champions Stage bracket entirely
(re-simulating the whole 8-team playoff each iteration), only locked in
Swiss stages all-or-nothing once 8 eliminations were recorded, seeded the
bracket by world rank rather than real Stage 3 performance, and read
qualifying points only from fully-completed events.

This conditions each simulation on whatever is already known and only
randomizes the undecided remainder:

- Champions Stage now honors the real bracket (playoffMatches): actual QF
  pairings supply the seeding, and any completed QF/SF/Final result is used
  verbatim instead of re-simulated. Falls back to Elo seeding when no
  bracket exists.
- Swiss stages reconstruct each team's current W-L from real match results
  (seasonMatches) so partly-played stages lock in their decided games and
  only the remaining teams are simulated; generalize simulateSwiss to start
  from seeded records.
- Provisional QP already written to event_results for settled (eliminated)
  teams is used verbatim.
- reconcileAdvancers keeps each stage at exactly 8 advancers so ragged
  mid-stage snapshots can't produce malformed downstream stages.

Adds unit coverage for bracket honoring (full and partial), partial-stage
locking, and recorded-QP override.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_018zMG6JFng8bMqZYweffVuE
2026-06-20 02:14:49 +00:00

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/**
* CS2 Major Qualifying Points Simulator
*
* Monte Carlo simulation of the 2 CS2 Majors per year. Qualifying points (QP)
* accumulate across both majors; final QP totals determine fantasy placements (1st8th).
*
* CS2 Major format (32 teams, 3 Swiss stages + playoffs):
* Stage 1 (Opening Stage): 16 teams, Swiss, all Bo1
* Stage 2 (Challengers Stage): 16 teams (8 Challengers + 8 from Stage 1), Swiss,
* Bo1 normally, Bo3 for decisive matches (either team
* can advance or be eliminated)
* Stage 3 (Legends Stage): 16 teams (8 Legends + 8 from Stage 2), Swiss, all Bo3
* Champions Stage: 8 teams, single-elimination (QF Bo3, SF Bo3, GF Bo5)
*
* Field selection (per iteration):
* - Top 12 participants by world ranking are always in the simulated field.
* - Remaining spots (up to 32 total) are sampled from the rest of the pool,
* weighted by 1/rank (lower rank = higher inclusion probability).
* - If cs2MajorStageResults records exist for an event, those explicit
* stage assignments are used instead of sampling/rank inference.
*
* Stage assignment within the 32-team field:
* - With explicit stage data: use stageEntry from cs2MajorStageResults
* - Without: top 8 by world ranking → Stage 3, next 8 → Stage 2, bottom 16 → Stage 1
*
* Champions Stage seeding:
* - Seeds are assigned by Stage 3 performance: fewer losses = higher seed.
* - World rank is used as tiebreaker within the same loss count.
* - When stage data is used (stage3Complete), losses are unknown and rank is used directly.
*
* QP for Stage 3 exits (placements 916) is sub-ranked by W-L record:
* - 2-3 teams → higher placements within 916
* - 1-3 teams → middle placements
* - 0-3 teams → lowest placements within 916
* QP is tie-split (averaged) within each W-L group.
*
* QP for Champions Stage:
* - QF losers (4 teams, placements 58): tie-split averaged across slots 58.
* - SF losers (2 teams, placements 34): tie-split averaged across slots 34.
* - Finalist and Champion earn their exact placement QP.
*
* Stages 1 and 2 exits (placements 1732) earn 0 QP.
*/
import { database } from "~/database/context";
import { eq, and, inArray } from "drizzle-orm";
import * as schema from "~/database/schema";
import { getQPConfig } from "~/models/qualifying-points";
import { getCs2StageResultsMapForEvent, computeStage3ExitQP as calcStage3ExitQP } from "~/models/cs2-major-stage";
export { calcStage3ExitQP };
import { getExcludedByEventMap } from "~/models/event-result";
import { findPlayoffMatchesByEventId } from "~/models/playoff-match";
import { findSeasonMatchesByScoringEventId } from "~/models/season-match";
import type { Simulator, SimulationResult } from "./types";
// ─── Simulation parameters ────────────────────────────────────────────────────
const NUM_SIMULATIONS = 10_000;
/** Total field size per CS2 Major. */
const FIELD_SIZE = 32;
/** Number of teams guaranteed in the simulated field (always included). */
const GUARANTEED_COUNT = 12;
/**
* Elo divisor for per-game win probability.
* Standard chess Elo uses 400. CS2 maps well to single-game level.
* 200-pt gap ≈ 76% win probability; 400-pt gap ≈ 91%.
*/
const ELO_DIVISOR = 400;
/** Fallback Elo for teams with no stored rating. */
const FALLBACK_ELO = 1500;
// ─── Math helpers ─────────────────────────────────────────────────────────────
/**
* Per-game win probability for team 1 vs team 2.
* Exported for unit testing.
*/
export function gameWinProb(elo1: number, elo2: number): number {
return 1 / (1 + Math.pow(10, (elo2 - elo1) / ELO_DIVISOR));
}
/**
* Match win probability using the Bernoulli series model.
* For a best-of-(2S-1) match (first to S wins):
* P(win) = Σ_{k=0}^{S-1} C(S-1+k, k) × p^S × (1-p)^k
* Exported for unit testing.
*/
export function seriesWinProb(p: number, winsNeeded: number): number {
let prob = 0;
for (let k = 0; k < winsNeeded; k++) {
prob += binomialCoeff(winsNeeded - 1 + k, k) * Math.pow(p, winsNeeded) * Math.pow(1 - p, k);
}
return prob;
}
/** Binomial coefficient C(n, k). */
function binomialCoeff(n: number, k: number): number {
if (k === 0) return 1;
if (k > n - k) k = n - k;
let result = 1;
for (let i = 0; i < k; i++) {
result = (result * (n - i)) / (i + 1);
}
return result;
}
/** Fisher-Yates in-place shuffle. Returns the array for chaining. */
function shuffle<T>(arr: T[]): T[] {
for (let i = arr.length - 1; i > 0; i--) {
const j = Math.floor(Math.random() * (i + 1));
[arr[i], arr[j]] = [arr[j], arr[i]];
}
return arr;
}
// ─── Field selection ──────────────────────────────────────────────────────────
interface TeamWithElo {
id: string;
elo: number;
rank: number; // HLTV world ranking (lower = better)
}
/**
* A team that has advanced through a Swiss stage, with their loss count at advancement.
* Used for Champions Stage seeding: fewer losses = higher seed (better stage performance).
*/
export interface AdvancedTeam extends TeamWithElo {
/** Number of losses accumulated when advancing (0 = 3-0, 1 = 3-1, 2 = 3-2). */
losses: number;
}
/** A single CS2 Major stage result row, as the simulator consumes it. */
export type StageResultsMap = Map<
string,
{ stageEntry: number; stageEliminated: number | null; stageEliminatedWins: number | null }
>;
/**
* A Champions Stage bracket match (subset of the playoffMatches row used by the
* simulator). Lets the simulator honor real, already-played bracket results
* instead of re-simulating the whole 8-team bracket each iteration.
*/
export interface BracketMatchInput {
round: string; // "Quarterfinals" | "Semifinals" | "Finals"
matchNumber: number; // QF: 14, SF: 12, Finals: 1
participant1Id: string | null;
participant2Id: string | null;
winnerId: string | null;
isComplete: boolean;
}
/**
* A Swiss-stage match (subset of the seasonMatches row). Used to reconstruct
* each team's current WL record mid-stage so already-played rounds are locked
* in and only the undecided remainder is simulated.
*/
export interface SwissMatchInput {
matchStage: number | null; // 1, 2, or 3
participant1Id: string | null;
participant2Id: string | null;
winnerId: string | null;
}
/** Optional already-known results that condition a single-major simulation. */
export interface SimulateOneMajorOptions {
/** Real Champions Stage bracket results, if entered. */
bracketMatches?: BracketMatchInput[];
/** Real Swiss match results, used to reconstruct mid-stage records. */
swissMatches?: SwissMatchInput[];
/** participantId → QP already recorded in event_results (provisional/locked). */
recordedResults?: Map<string, number>;
}
/**
* Sample a 32-team field from the pool.
* - Top GUARANTEED_COUNT (12) by rank are always included.
* - Remaining spots are weighted-randomly sampled from the rest, weight = 1/rank.
* - If pool.length <= FIELD_SIZE, returns all teams.
* Exported for unit testing.
*/
export function sampleField(
pool: TeamWithElo[],
fieldSize: number = FIELD_SIZE
): TeamWithElo[] {
const sorted = [...pool].toSorted((a, b) => a.rank - b.rank);
if (sorted.length <= fieldSize) return sorted;
const guaranteed = sorted.slice(0, GUARANTEED_COUNT);
const rest = sorted.slice(GUARANTEED_COUNT);
const needed = fieldSize - guaranteed.length;
if (needed <= 0) return guaranteed;
if (rest.length <= needed) return [...guaranteed, ...rest];
// Weighted sample without replacement, weight = 1/rank
const weights = rest.map((t) => 1 / t.rank);
const sampled = weightedSampleWithoutReplacement(rest, weights, needed);
return [...guaranteed, ...sampled];
}
/** Weighted sampling without replacement using the Gumbel-max trick. */
function weightedSampleWithoutReplacement<T>(
items: T[],
weights: number[],
count: number
): T[] {
const keys = weights.map((w) => -Math.log(Math.random()) / w);
const indexed = items.map((item, i) => ({ item, key: keys[i] }));
const sortedIndexed = indexed.toSorted((a, b) => a.key - b.key);
return sortedIndexed.slice(0, count).map((x) => x.item);
}
// ─── Swiss stage simulation ───────────────────────────────────────────────────
interface SwissResult {
/** Teams that advanced (3 wins), with their loss count at advancement. */
advanced: AdvancedTeam[];
/** Teams eliminated, with their win count at time of elimination. */
eliminated: Array<{ id: string; elo: number; rank: number; wins: number }>;
}
/**
* Simulate one Swiss-format stage.
* Teams are grouped by their (wins, losses) record each round. Teams are paired
* randomly within each record group. First to 3 wins advances; first to 3 losses
* is eliminated.
*
* @param teams - Teams entering this stage (must be an even count).
* @param bo3 - If true, all matches are Bo3; otherwise Bo1.
* @param decisiveMatchesBo3 - If true, matches where either team can advance or
* be eliminated (≥2 wins or ≥2 losses) are promoted to
* Bo3 regardless of the `bo3` flag. Used for Stage 2.
* @param initialRecords - Optional per-team starting (wins, losses). Teams
* already at the 3W/3L threshold are locked in as
* advanced/eliminated and only the undecided
* remainder is simulated. Defaults to 00 for all
* teams (a fresh stage).
* @returns advanced (with losses) and eliminated (with wins) arrays.
*
* Exported for unit testing.
*/
export function simulateSwiss(
teams: TeamWithElo[],
bo3: boolean,
decisiveMatchesBo3 = false,
initialRecords?: Map<string, { wins: number; losses: number }>
): SwissResult {
if (teams.length === 0) return { advanced: [], eliminated: [] };
if (teams.length % 2 !== 0) {
throw new Error(`simulateSwiss requires an even number of teams, got ${teams.length}`);
}
const wins = new Map<string, number>(teams.map((t) => [t.id, initialRecords?.get(t.id)?.wins ?? 0]));
const losses = new Map<string, number>(teams.map((t) => [t.id, initialRecords?.get(t.id)?.losses ?? 0]));
const eloMap = new Map<string, number>(teams.map((t) => [t.id, t.elo]));
const advanced: AdvancedTeam[] = [];
const eliminated: SwissResult["eliminated"] = [];
const advancedIds = new Set<string>();
const eliminatedIds = new Set<string>();
const teamById = new Map<string, TeamWithElo>(teams.map((t) => [t.id, t]));
// Pre-resolve teams whose seeded record already meets a threshold (locked
// results carried in from real match data): 3+ wins = advanced, 3+ losses =
// eliminated. Teams below both thresholds continue in the Swiss loop below.
for (const t of teams) {
const w = wins.get(t.id) ?? 0;
const l = losses.get(t.id) ?? 0;
if (w >= 3) {
advancedIds.add(t.id);
advanced.push({ id: t.id, elo: t.elo, rank: t.rank, losses: l });
} else if (l >= 3) {
eliminatedIds.add(t.id);
eliminated.push({ id: t.id, elo: t.elo, rank: t.rank, wins: w });
}
}
// Run rounds until every team has reached 3W or 3L
while (advancedIds.size + eliminatedIds.size < teams.length) {
// Collect active teams grouped by (W, L) record
const active = teams.filter((t) => !advancedIds.has(t.id) && !eliminatedIds.has(t.id));
const groups = groupByRecord(active, wins, losses);
// If a group has an odd number, move one team to the nearest adjacent group
// (simplified: skip teams that can't be paired — they sit out this round)
const pairs = pairGroups(groups);
// Safety: if no pairs can be formed (shouldn't happen with even team counts
// but guards against an infinite loop if an odd active count somehow occurs)
if (pairs.length === 0) break;
for (const [t1, t2] of pairs) {
const e1 = eloMap.get(t1.id) ?? FALLBACK_ELO;
const e2 = eloMap.get(t2.id) ?? FALLBACK_ELO;
// A match is "decisive" if either team can advance (2W) or be eliminated (2L)
const w1 = wins.get(t1.id) ?? 0;
const l1 = losses.get(t1.id) ?? 0;
const w2 = wins.get(t2.id) ?? 0;
const l2 = losses.get(t2.id) ?? 0;
const isDecisive = decisiveMatchesBo3 && (w1 >= 2 || l1 >= 2 || w2 >= 2 || l2 >= 2);
const p = (bo3 || isDecisive)
? seriesWinProb(gameWinProb(e1, e2), 2) // Bo3: first to 2
: gameWinProb(e1, e2); // Bo1: single game
const t1Wins = Math.random() < p;
const winnerId = t1Wins ? t1.id : t2.id;
const loserId = t1Wins ? t2.id : t1.id;
wins.set(winnerId, (wins.get(winnerId) ?? 0) + 1);
losses.set(loserId, (losses.get(loserId) ?? 0) + 1);
if ((wins.get(winnerId) ?? 0) >= 3) {
advancedIds.add(winnerId);
const t = teamById.get(winnerId);
if (t) advanced.push({ id: t.id, elo: t.elo, rank: t.rank, losses: losses.get(winnerId) ?? 0 });
}
if ((losses.get(loserId) ?? 0) >= 3) {
eliminatedIds.add(loserId);
const t = teamById.get(loserId);
if (t) eliminated.push({ id: t.id, elo: t.elo, rank: t.rank, wins: wins.get(loserId) ?? 0 });
}
}
}
// Safety net: a ragged mid-stage snapshot (records that don't fall on a clean
// round boundary) can leave a team unpaired and unresolved. Resolve any
// stragglers by their current record so the partition is always complete.
for (const t of teams) {
if (advancedIds.has(t.id) || eliminatedIds.has(t.id)) continue;
const w = wins.get(t.id) ?? 0;
const l = losses.get(t.id) ?? 0;
if (w >= l) {
advancedIds.add(t.id);
advanced.push({ id: t.id, elo: t.elo, rank: t.rank, losses: l });
} else {
eliminatedIds.add(t.id);
eliminated.push({ id: t.id, elo: t.elo, rank: t.rank, wins: w });
}
}
return { advanced, eliminated };
}
/** Group active teams by (wins, losses) record key. */
function groupByRecord(
active: TeamWithElo[],
wins: Map<string, number>,
losses: Map<string, number>
): Map<string, TeamWithElo[]> {
const groups = new Map<string, TeamWithElo[]>();
for (const t of active) {
const key = `${wins.get(t.id) ?? 0}-${losses.get(t.id) ?? 0}`;
if (!groups.has(key)) groups.set(key, []);
groups.get(key)?.push(t);
}
return groups;
}
/**
* Pair teams within each record group. Teams in groups with an odd count
* are handled by merging the leftover into an adjacent group (simpler: skip
* them for this round — they sit out and play next round).
*/
function pairGroups(groups: Map<string, TeamWithElo[]>): Array<[TeamWithElo, TeamWithElo]> {
const pairs: Array<[TeamWithElo, TeamWithElo]> = [];
const leftover: TeamWithElo[] = [];
for (const group of groups.values()) {
const shuffled = shuffle([...group]);
for (let i = 0; i + 1 < shuffled.length; i += 2) {
pairs.push([shuffled[i], shuffled[i + 1]]);
}
if (shuffled.length % 2 !== 0) {
leftover.push(shuffled[shuffled.length - 1]);
}
}
// Pair leftover teams with each other (different records, cross-group match)
for (let i = 0; i + 1 < leftover.length; i += 2) {
pairs.push([leftover[i], leftover[i + 1]]);
}
return pairs;
}
// ─── Champions Stage (8-team single-elimination bracket) ─────────────────────
interface ChampionsResult {
/**
* participantId → placement group:
* 1 = champion, 2 = finalist
* 3 = both SF losers (tie-split QP across slots 34 in the caller)
* 5 = all 4 QF losers (tie-split QP across slots 58 in the caller)
*/
placements: Map<string, number>;
}
/**
* Simulate the Champions Stage 8-team single-elimination bracket.
* Rounds: QF (Bo3), SF (Bo3), GF (Bo5).
*
* When `bracketMatches` describes a real, fully-seeded bracket (4 QF matches
* whose participants are all in this field), the actual QF pairings are used —
* this preserves the real Stage 3 seeding the admin built — and any match
* already played (`isComplete` with a `winnerId`) is honored instead of
* re-simulated. Undecided matches fall back to the Elo-based model. Without a
* usable bracket, seeds are assigned by stage performance (losses ascending,
* world rank as tiebreaker) with standard 1v8/4v5/3v6/2v7 pairings.
*
* Feed mapping matches advanceWinner: QF1/QF2 → SF1, QF3/QF4 → SF2, SF1/SF2 → F.
*
* QF losers are all assigned placement 5 (tie-split across slots 58 by caller).
* SF losers are both assigned placement 3 (tie-split across slots 34 by caller).
* Exported for unit testing.
*/
export function simulateChampionsStage(
teams: AdvancedTeam[],
bracketMatches?: BracketMatchInput[]
): ChampionsResult {
if (teams.length !== 8) {
throw new Error(`simulateChampionsStage expects exactly 8 teams, got ${teams.length}`);
}
const byId = new Map<string, AdvancedTeam>(teams.map((t) => [t.id, t]));
const placements = new Map<string, number>();
const simMatch = (t1: AdvancedTeam, t2: AdvancedTeam, winsNeeded: number): AdvancedTeam => {
const p = seriesWinProb(gameWinProb(t1.elo, t2.elo), winsNeeded);
return Math.random() < p ? t1 : t2;
};
const recordedMatch = (round: string, matchNumber: number): BracketMatchInput | undefined =>
bracketMatches?.find((m) => m.round === round && m.matchNumber === matchNumber);
// Honor a completed match's recorded winner; otherwise simulate.
const resolve = (
t1: AdvancedTeam,
t2: AdvancedTeam,
winsNeeded: number,
rec: BracketMatchInput | undefined
): AdvancedTeam => {
if (rec?.isComplete && rec.winnerId) {
if (rec.winnerId === t1.id) return t1;
if (rec.winnerId === t2.id) return t2;
}
return simMatch(t1, t2, winsNeeded);
};
// Determine QF pairings from the real bracket when it is fully seeded with
// teams from this field; otherwise seed by stage performance.
const qf = bracketMatches
?.filter((m) => m.round === "Quarterfinals")
.toSorted((a, b) => a.matchNumber - b.matchNumber);
const realBracket =
qf?.length === 4 &&
qf.every(
(m) =>
m.participant1Id != null &&
m.participant2Id != null &&
byId.has(m.participant1Id) &&
byId.has(m.participant2Id)
);
let qfPairs: [AdvancedTeam, AdvancedTeam][];
if (realBracket && qf) {
qfPairs = qf.map((m) => [byId.get(m.participant1Id!)!, byId.get(m.participant2Id!)!]);
} else {
// Seed by stage performance: fewer losses = higher seed; rank as tiebreaker.
const seeded = [...teams].toSorted((a, b) =>
a.losses !== b.losses ? a.losses - b.losses : a.rank - b.rank
);
// Standard 8-team seeding: 1v8, 4v5, 3v6, 2v7
qfPairs = [
[seeded[0], seeded[7]],
[seeded[3], seeded[4]],
[seeded[2], seeded[5]],
[seeded[1], seeded[6]],
];
}
// Quarterfinals (Bo3 = first to 2)
const sfFeeders: AdvancedTeam[] = [];
qfPairs.forEach(([t1, t2], i) => {
const winner = resolve(t1, t2, 2, recordedMatch("Quarterfinals", i + 1));
const loser = winner.id === t1.id ? t2 : t1;
placements.set(loser.id, 5); // QF losers: all get placement 5 (tie-split 58 by caller)
sfFeeders[i] = winner;
});
// Semifinals (Bo3 = first to 2): SF1 = QF1/QF2 winners, SF2 = QF3/QF4 winners
const finalFeeders: AdvancedTeam[] = [];
for (let i = 0; i < 2; i++) {
const t1 = sfFeeders[i * 2];
const t2 = sfFeeders[i * 2 + 1];
const winner = resolve(t1, t2, 2, recordedMatch("Semifinals", i + 1));
const loser = winner.id === t1.id ? t2 : t1;
placements.set(loser.id, 3); // SF losers: both get placement 3 (tie-split 34)
finalFeeders[i] = winner;
}
// Grand Final (Bo5 = first to 3)
const champion = resolve(finalFeeders[0], finalFeeders[1], 3, recordedMatch("Finals", 1));
const finalist = champion.id === finalFeeders[0].id ? finalFeeders[1] : finalFeeders[0];
placements.set(champion.id, 1);
placements.set(finalist.id, 2);
return { placements };
}
// ─── QP helpers ───────────────────────────────────────────────────────────────
// ─── Simulator ────────────────────────────────────────────────────────────────
export class CSMajorSimulator implements Simulator {
async simulate(sportsSeasonId: string): Promise<SimulationResult[]> {
const db = database();
// 1. Load all participants for this sports season.
const allParticipants = await db
.select({ id: schema.seasonParticipants.id })
.from(schema.seasonParticipants)
.where(eq(schema.seasonParticipants.sportsSeasonId, sportsSeasonId));
const participantIds = allParticipants.map((p) => p.id);
if (participantIds.length === 0) {
throw new Error(`No participants found for sports season ${sportsSeasonId}.`);
}
// 2. Load Elo ratings and world rankings from participantExpectedValues.
const evRows = await db
.select({
participantId: schema.seasonParticipantExpectedValues.participantId,
sourceElo: schema.seasonParticipantExpectedValues.sourceElo,
worldRanking: schema.seasonParticipantExpectedValues.worldRanking,
})
.from(schema.seasonParticipantExpectedValues)
.where(eq(schema.seasonParticipantExpectedValues.sportsSeasonId, sportsSeasonId));
const eloMap = new Map<string, { elo: number; rank: number }>();
for (const row of evRows) {
if (row.sourceElo !== null) {
eloMap.set(row.participantId, {
elo: row.sourceElo,
rank: row.worldRanking ?? 9999,
});
}
}
// Build pool: all participants, using FALLBACK_ELO for those without ratings, sorted by rank
const pool: TeamWithElo[] = participantIds
.map((id) => {
const e = eloMap.get(id);
return { id, elo: e?.elo ?? FALLBACK_ELO, rank: e?.rank ?? 9999 };
})
.toSorted((a, b) => a.rank - b.rank);
const hasAnyElo = participantIds.some((id) => eloMap.has(id));
if (!hasAnyElo) {
throw new Error(
`No participants with Elo ratings found for sports season ${sportsSeasonId}. ` +
`Enter Elo ratings via the CS Elo admin page before simulating.`
);
}
// 3. Load QP config (placements 116 earn QP; 17+ earn 0).
const qpConfigArray = await getQPConfig(sportsSeasonId);
const qpConfig = new Map<number, number>(
qpConfigArray.map((c) => [c.placement, parseFloat(c.points)])
);
// 4. Load all CS major scoring events for this sports season.
const events = await db.query.scoringEvents.findMany({
where: and(
eq(schema.scoringEvents.sportsSeasonId, sportsSeasonId),
eq(schema.scoringEvents.eventType, "major_tournament")
),
orderBy: (e, { asc }) => [asc(e.eventDate)],
});
if (events.length === 0) {
throw new Error(
`No major_tournament scoring events found for sports season ${sportsSeasonId}. ` +
`Create the CS Major scoring events first.`
);
}
// 5. For completed events, read actual QP from eventResults.
const completedEventIds = events.filter((e) => e.isComplete).map((e) => e.id);
const actualQPMap = new Map<string, number>(participantIds.map((id) => [id, 0]));
if (completedEventIds.length > 0) {
const actualResults = await db
.select({
participantId: schema.eventResults.seasonParticipantId,
qualifyingPointsAwarded: schema.eventResults.qualifyingPointsAwarded,
})
.from(schema.eventResults)
.where(inArray(schema.eventResults.scoringEventId, completedEventIds));
for (const r of actualResults) {
if (r.qualifyingPointsAwarded !== null) {
const prev = actualQPMap.get(r.participantId) ?? 0;
actualQPMap.set(r.participantId, prev + parseFloat(r.qualifyingPointsAwarded));
}
}
}
// 6. Load stage results for all events in parallel.
const stageResultEntries = await Promise.all(
events.map(async (event) => {
const results = await getCs2StageResultsMapForEvent(event.id);
return [event.id, results] as const;
})
);
const eventStageResults = new Map(
stageResultEntries.filter(([, r]) => r.size > 0)
);
const incompleteEvents = events.filter((e) => !e.isComplete);
const incompleteEventIds = incompleteEvents.map((e) => e.id);
// Load not-participating exclusions for each incomplete event.
const excludedByEvent = await getExcludedByEventMap(incompleteEventIds);
// 6b. For incomplete events, load already-known results so the simulation
// conditions on them instead of re-simulating: the Champions Stage
// bracket, the Swiss match results, and provisional recorded QP.
const [bracketEntries, swissEntries] = await Promise.all([
Promise.all(
incompleteEvents.map(async (e) => [e.id, await findPlayoffMatchesByEventId(e.id)] as const)
),
Promise.all(
incompleteEvents.map(async (e) => [e.id, await findSeasonMatchesByScoringEventId(e.id)] as const)
),
]);
const eventBracket = new Map<string, BracketMatchInput[]>(
bracketEntries.map(([id, matches]) => [
id,
matches.map((m) => ({
round: m.round,
matchNumber: m.matchNumber,
participant1Id: m.participant1Id,
participant2Id: m.participant2Id,
winnerId: m.winnerId,
isComplete: m.isComplete,
})),
])
);
const eventSwiss = new Map<string, SwissMatchInput[]>(
swissEntries.map(([id, matches]) => [
id,
matches.map((m) => ({
matchStage: m.matchStage,
participant1Id: m.participant1Id,
participant2Id: m.participant2Id,
winnerId: m.winnerId,
})),
])
);
const eventRecordedQP = new Map<string, Map<string, number>>();
if (incompleteEventIds.length > 0) {
const provisionalResults = await db
.select({
eventId: schema.eventResults.scoringEventId,
participantId: schema.eventResults.seasonParticipantId,
qualifyingPointsAwarded: schema.eventResults.qualifyingPointsAwarded,
})
.from(schema.eventResults)
.where(inArray(schema.eventResults.scoringEventId, incompleteEventIds));
for (const r of provisionalResults) {
if (r.qualifyingPointsAwarded === null) continue;
let perEvent = eventRecordedQP.get(r.eventId);
if (!perEvent) {
perEvent = new Map<string, number>();
eventRecordedQP.set(r.eventId, perEvent);
}
perEvent.set(r.participantId, parseFloat(r.qualifyingPointsAwarded));
}
}
// 7. Short-circuit: if all events are complete, return deterministic probabilities
// based on actual QP totals — no simulation needed.
if (incompleteEvents.length === 0) {
const ranked = [...actualQPMap.entries()].toSorted((a, b) => b[1] - a[1]);
return participantIds.map((participantId) => {
const rank = ranked.findIndex(([id]) => id === participantId) + 1; // 1-indexed
return {
participantId,
probabilities: {
probFirst: rank === 1 ? 1.0 : 0.0,
probSecond: rank === 2 ? 1.0 : 0.0,
probThird: rank === 3 ? 1.0 : 0.0,
probFourth: rank === 4 ? 1.0 : 0.0,
probFifth: rank === 5 ? 1.0 : 0.0,
probSixth: rank === 6 ? 1.0 : 0.0,
probSeventh: rank === 7 ? 1.0 : 0.0,
probEighth: rank === 8 ? 1.0 : 0.0,
},
source: "cs2_major_qualifying_points_monte_carlo",
};
});
}
// 8. Monte Carlo loop.
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++) {
const simQP = new Map<string, number>(actualQPMap);
for (const event of incompleteEvents) {
const excluded = excludedByEvent.get(event.id) ?? new Set<string>();
const eventPool = excluded.size > 0 ? pool.filter((t) => !excluded.has(t.id)) : pool;
const stageResultsForEvent = eventStageResults.get(event.id);
const eventQP = simulateOneMajor(eventPool, stageResultsForEvent, qpConfig, {
bracketMatches: eventBracket.get(event.id),
swissMatches: eventSwiss.get(event.id),
recordedResults: eventRecordedQP.get(event.id),
});
for (const [pid, qp] of eventQP) {
simQP.set(pid, (simQP.get(pid) ?? 0) + qp);
}
}
// Rank all participants by total QP descending.
const ranked = [...simQP.entries()].toSorted((a, b) => b[1] - a[1]);
for (let rank = 0; rank < Math.min(8, ranked.length); rank++) {
const [pid] = ranked[rank];
const idx = idToIndex.get(pid);
if (idx !== undefined) counts[idx][rank]++;
}
}
// 9. Convert counts to probabilities.
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,
},
source: "cs2_major_qualifying_points_monte_carlo",
}));
}
}
// ─── Single major simulation ───────────────────────────────────────────────────
/** Average QP across a range of placement slots (for tie-splitting). */
function avgSlotQP(slots: number[], qpConfig: Map<number, number>): number {
return slots.reduce((sum, s) => sum + (qpConfig.get(s) ?? 0), 0) / slots.length;
}
/**
* Reconstruct each team's current (wins, losses) within a stage from real Swiss
* match results. Only completed matches (those with a recorded winner) count.
*/
function reconstructStageRecords(
swissMatches: SwissMatchInput[] | undefined,
stageNum: number
): Map<string, { wins: number; losses: number }> {
const records = new Map<string, { wins: number; losses: number }>();
if (!swissMatches) return records;
const bump = (id: string, key: "wins" | "losses") => {
const r = records.get(id) ?? { wins: 0, losses: 0 };
r[key] += 1;
records.set(id, r);
};
for (const m of swissMatches) {
if (m.matchStage !== stageNum) continue;
if (!m.winnerId || !m.participant1Id || !m.participant2Id) continue;
const loserId = m.winnerId === m.participant1Id ? m.participant2Id : m.participant1Id;
bump(m.winnerId, "wins");
bump(loserId, "losses");
}
return records;
}
/**
* Build the seeded starting records for a stage's Swiss simulation, locking in
* everything already known from real data so only the undecided remainder is
* simulated:
* - Teams recorded as eliminated at this stage (cs2MajorStageResults) or with
* 3 losses in the Swiss match data are locked in as eliminated (losses = 3).
* - Teams with 3 recorded wins are locked in as advanced.
* - When the stage is complete (8 eliminations known) every other team is a
* locked advancer.
* - Remaining teams carry their partial real record (00 if none).
* Returns the seed map plus the set of teams locked in as eliminated (whose QP
* is settled, so recorded provisional QP may be applied verbatim).
*/
function buildStageInitialRecords(
stageTeams: TeamWithElo[],
stageNum: number,
swissMatches: SwissMatchInput[] | undefined,
stageResults: StageResultsMap | undefined
): { initialRecords: Map<string, { wins: number; losses: number }>; lockedEliminated: Set<string> } {
const recon = reconstructStageRecords(swissMatches, stageNum);
const initialRecords = new Map<string, { wins: number; losses: number }>();
const lockedEliminated = new Set<string>();
const cs2ElimIds = new Set<string>();
if (stageResults) {
for (const [id, r] of stageResults) {
if (r.stageEliminated === stageNum) cs2ElimIds.add(id);
}
}
const reconElimCount = [...recon.values()].filter((r) => r.losses >= 3).length;
const stageComplete = cs2ElimIds.size >= 8 || reconElimCount >= 8;
for (const t of stageTeams) {
const r = recon.get(t.id);
const cs2 = stageResults?.get(t.id);
if (cs2ElimIds.has(t.id)) {
initialRecords.set(t.id, { wins: cs2?.stageEliminatedWins ?? r?.wins ?? 0, losses: 3 });
lockedEliminated.add(t.id);
} else if (r && r.losses >= 3) {
initialRecords.set(t.id, { wins: r.wins, losses: 3 });
lockedEliminated.add(t.id);
} else if (r && r.wins >= 3) {
initialRecords.set(t.id, { wins: 3, losses: r.losses });
} else if (stageComplete) {
// Stage done and this team wasn't eliminated → it advanced. Exact loss
// count is unknown without match data; use 2 as a conservative fallback.
initialRecords.set(t.id, { wins: 3, losses: r?.losses ?? 2 });
} else if (r) {
initialRecords.set(t.id, { wins: r.wins, losses: r.losses });
}
}
return { initialRecords, lockedEliminated };
}
/**
* Each CS2 Swiss stage advances exactly 8 of its 16 teams. A consistent Swiss
* state always yields that split, but a ragged mid-stage snapshot (locked
* results that don't form a valid Swiss position) can over- or under-fill the
* advancer pool. Reconcile to exactly `target` advancers — demoting the weakest
* advancers (most losses, then worst rank) or promoting the strongest
* eliminated teams (most wins, then best rank) — so downstream stages stay
* well-formed. A no-op for the common, consistent case.
*/
function reconcileAdvancers(result: SwissResult, target: number): SwissResult {
if (result.advanced.length === target) return result;
const advanced = [...result.advanced];
const eliminated = [...result.eliminated];
if (advanced.length > target) {
advanced.sort((a, b) => (a.losses !== b.losses ? a.losses - b.losses : a.rank - b.rank));
for (const t of advanced.splice(target)) {
eliminated.push({ id: t.id, elo: t.elo, rank: t.rank, wins: 2 });
}
} else {
eliminated.sort((a, b) => (b.wins !== a.wins ? b.wins - a.wins : a.rank - b.rank));
for (const t of eliminated.splice(0, target - advanced.length)) {
advanced.push({ id: t.id, elo: t.elo, rank: t.rank, losses: 2 });
}
}
return { advanced, eliminated };
}
/**
* Simulate one CS2 Major and return QP earned per participant.
*
* Conditions the simulation on whatever has already happened, only randomizing
* the undecided remainder:
* - `stageResults` determines field composition and recorded eliminations.
* - `options.swissMatches` reconstructs mid-stage WL records so partly-played
* stages are locked in (not re-simulated from scratch).
* - `options.bracketMatches` makes the Champions Stage honor real bracket
* seeding and already-played QF/SF/Final results.
* - `options.recordedResults` supplies provisional QP already written for
* settled (eliminated) teams, used verbatim instead of re-derived.
*
* Returns a Map from participantId → QP earned in this major.
* Exported for unit testing.
*/
export function simulateOneMajor(
pool: TeamWithElo[],
stageResults: StageResultsMap | undefined,
qpConfig: Map<number, number>,
options: SimulateOneMajorOptions = {}
): Map<string, number> {
const { bracketMatches, swissMatches, recordedResults } = options;
const qpMap = new Map<string, number>();
const poolById = new Map<string, TeamWithElo>(pool.map((t) => [t.id, t]));
// ── Determine field and stage assignments ─────────────────────────────────
// stage2Direct / stage3Direct are AdvancedTeam[] (losses = 0: no prior Swiss stage)
let stage1Teams: TeamWithElo[];
let stage2Direct: AdvancedTeam[];
let stage3Direct: AdvancedTeam[];
if (stageResults && stageResults.size > 0) {
const s1: TeamWithElo[] = [];
const s2: AdvancedTeam[] = [];
const s3: AdvancedTeam[] = [];
for (const [participantId, result] of stageResults) {
const team = poolById.get(participantId);
if (!team) continue;
if (result.stageEntry === 1) s1.push(team);
else if (result.stageEntry === 2) s2.push({ ...team, losses: 0 });
else if (result.stageEntry === 3) s3.push({ ...team, losses: 0 });
}
stage1Teams = s1;
stage2Direct = s2;
stage3Direct = s3;
} else {
const field = sampleField(pool, FIELD_SIZE);
const sorted = field.toSorted((a, b) => a.rank - b.rank);
stage3Direct = sorted.slice(0, 8).map((t) => ({ ...t, losses: 0 }));
stage2Direct = sorted.slice(8, 16).map((t) => ({ ...t, losses: 0 }));
stage1Teams = sorted.slice(16, 32);
}
// ── Stage 1 (Opening) — all Bo1 ───────────────────────────────────────────
// Each stage advances exactly 8 teams; reconcile guards against ragged inputs.
const s1Seed = buildStageInitialRecords(stage1Teams, 1, swissMatches, stageResults);
const stage1Result = reconcileAdvancers(simulateSwiss(stage1Teams, false, false, s1Seed.initialRecords), 8);
const stage1Advanced = stage1Result.advanced;
const stage1EliminatedFinal = stage1Result.eliminated;
// ── Stage 2 (Challengers) — Bo1, Bo3 for decisive matches ────────────────
const stage2Teams: AdvancedTeam[] = [...stage2Direct, ...stage1Advanced];
const s2Seed = buildStageInitialRecords(stage2Teams, 2, swissMatches, stageResults);
const stage2Result = reconcileAdvancers(simulateSwiss(stage2Teams, false, true, s2Seed.initialRecords), 8);
const stage2Advanced = stage2Result.advanced;
const stage2EliminatedFinal = stage2Result.eliminated;
// ── Stage 3 (Legends) — all Bo3 ──────────────────────────────────────────
const stage3Teams: AdvancedTeam[] = [...stage3Direct, ...stage2Advanced];
const s3Seed = buildStageInitialRecords(stage3Teams, 3, swissMatches, stageResults);
const stage3Result = reconcileAdvancers(simulateSwiss(stage3Teams, true, false, s3Seed.initialRecords), 8);
const stage3EliminatedFinal = stage3Result.eliminated;
// Stage 3 reconciles to exactly 8 advancers — the Champions Stage field.
const champTeams = stage3Result.advanced;
// ── Champions Stage ───────────────────────────────────────────────────────
const champResult = simulateChampionsStage(champTeams, bracketMatches);
// ── Assign QP — tie-split QF losers (58) and SF losers (34) ────────────
// Group placements: placement 5 = QF losers, placement 3 = SF losers
const byPlacement = new Map<number, string[]>();
for (const [pid, placement] of champResult.placements) {
if (!byPlacement.has(placement)) byPlacement.set(placement, []);
const group = byPlacement.get(placement);
if (group) group.push(pid);
}
for (const [placement, pids] of byPlacement) {
const slots = Array.from({ length: pids.length }, (_, i) => placement + i);
const avgQP = avgSlotQP(slots, qpConfig);
for (const pid of pids) {
qpMap.set(pid, avgQP);
}
}
const stage3ExitQP = calcStage3ExitQP(stage3EliminatedFinal, qpConfig);
for (const [pid, qp] of stage3ExitQP) {
qpMap.set(pid, qp);
}
for (const t of stage1EliminatedFinal) qpMap.set(t.id, 0);
for (const t of stage2EliminatedFinal) qpMap.set(t.id, 0);
// For teams whose elimination is locked in from real data, prefer the QP
// already recorded in event_results so the simulation matches what fans see.
if (recordedResults) {
const lockedEliminated = new Set<string>([
...s1Seed.lockedEliminated,
...s2Seed.lockedEliminated,
...s3Seed.lockedEliminated,
]);
for (const id of lockedEliminated) {
const recorded = recordedResults.get(id);
if (recorded !== undefined) qpMap.set(id, recorded);
}
}
return qpMap;
}