* Add CS2 Major qualifying points simulator Implements a full CS2 Major tournament simulator with: - 3-stage Swiss format (Opening Bo1, Elimination Bo1/Bo3, Decider all Bo3) + Champions Stage 8-team single-elimination (QF Bo3, SF Bo3, GF Bo5) - Monte Carlo simulation (10,000 iterations) accumulating QP across 2 majors/season - Sampled 24-team field per iteration: top 12 guaranteed, remaining weighted by 1/rank - Stage 3 exits (placements 9-16) sub-ranked by W-L record (2-3 > 1-3 > 0-3) - Stage assignments stored per-event so actual field composition drives simulation - Admin CS Elo form for entering team Elo + HLTV world rankings - Admin CS2 stage setup page for assigning teams to stages and tracking advancement - Database migration: cs2_major_qualifying_points enum value + cs2_major_stage_results table - 24 unit tests covering all exported pure functions https://claude.ai/code/session_019w21Nkf5TvTZHH6oVHaQXR * Consolidate Elo + ranking input into generic elo-ratings page The darts-elo and cs-elo pages were unreachable from the admin nav, which always links to the generic elo-ratings page. Extended elo-ratings to conditionally show world ranking fields for simulator types that need it (darts_bracket, cs2_major_qualifying_points), then deleted the redundant sport-specific pages. https://claude.ai/code/session_019w21Nkf5TvTZHH6oVHaQXR * Consolidate server postgres connections into one shared pool Four separate postgres() clients were open simultaneously (app, timer, snapshots, socket), each defaulting to 10 connections, exhausting the database's max_connections limit. Replaced with a single shared lazy- initialized client in server/db.ts using a Proxy to defer the DATABASE_URL check until first use (preserving test compatibility). Also bumps the CS2 Champions Stage stochastic test from 200 → 1000 iterations to eliminate flakiness. https://claude.ai/code/session_019w21Nkf5TvTZHH6oVHaQXR * Fix and() bug and add Swiss loop safety guard - cs2-major-stage.ts: markCs2StageEliminations and setCs2FinalPlacements were using JS && instead of Drizzle and(), causing WHERE to filter only by participantId (not scoringEventId), which would update rows across all events instead of just the target event - cs-major-simulator.ts: add break guard in simulateSwiss while loop to prevent infinite loop if pairGroups returns no pairs https://claude.ai/code/session_019w21Nkf5TvTZHH6oVHaQXR * Fix all remaining code review issues - cs2-major-stage.ts: use schema column reference for stageEliminated in markCs2StageEliminations instead of raw SQL string - cs-major-simulator.ts: simulateOneMajor now locks in known stage results when a stage is complete (8 recorded eliminations), only simulating the remaining stages during live events - admin event page: add CS2 Stage Setup button for cs2_major_qualifying_points simulator types; expose simulatorType in server loader type cast - cs2-setup.tsx: replace document.getElementById DOM manipulation with React state (eliminatedChecked map) for checkbox show/hide logic; remove unused stageMap and unassignedParticipants variables https://claude.ai/code/session_019w21Nkf5TvTZHH6oVHaQXR * Fix oxlint errors: non-null assertions, sort→toSorted, unused vars - cs-major-simulator.ts: replace 5 non-null assertions (!) with safe optional chaining / if-guards; replace 6 .sort() with .toSorted() - cs2-major-stage.ts: remove unused `inArray` import - cs2-setup.tsx: remove unused `assignedIds` variable https://claude.ai/code/session_019w21Nkf5TvTZHH6oVHaQXR * Fix flaky Champions Stage stochastic test The makeTeams(8) helper creates only a 70-pt Elo spread (1800→1730). With the Champions Stage bracket math this gives team-0 a ~19.6% win rate — right at the 0.2 threshold, causing the test to fail ~63% of the time in CI despite 1000 iterations. Use 100-pt steps (1800→1100) instead, giving team-0 a ~40% win rate and raising the assertion threshold to 0.25 for a clear safety margin. https://claude.ai/code/session_019w21Nkf5TvTZHH6oVHaQXR --------- Co-authored-by: Claude <noreply@anthropic.com>
658 lines
26 KiB
TypeScript
658 lines
26 KiB
TypeScript
/**
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* CS2 Major Qualifying Points Simulator
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*
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* Monte Carlo simulation of the 2 CS2 Majors per year. Qualifying points (QP)
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* accumulate across both majors; final QP totals determine fantasy placements (1st–8th).
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*
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* CS2 Major format (32 teams, 3 Swiss stages + playoffs):
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* Stage 1 (Opening Stage): 16 teams, Swiss, Bo1 matches
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* Stage 2 (Elimination Stage): 16 teams (8 Challengers + 8 from Stage 1), Swiss, Bo1/Bo3
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* Stage 3 (Decider Stage): 16 teams (8 Legends + 8 from Stage 2), Swiss, all Bo3
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* Champions Stage: 8 teams, single-elimination (QF Bo3, SF Bo3, GF Bo5)
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*
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* Field selection (per iteration):
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* - Top 12 participants by world ranking are always in the simulated field.
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* - Remaining spots (up to 32 total) are sampled from the rest of the pool,
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* weighted by 1/rank (lower rank = higher inclusion probability).
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* - If cs2MajorStageResults records exist for an event, those explicit
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* stage assignments are used instead of sampling/rank inference.
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*
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* Stage assignment within the 32-team field:
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* - With explicit stage data: use stageEntry from cs2MajorStageResults
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* - Without: top 8 by world ranking → Stage 3, next 8 → Stage 2, bottom 16 → Stage 1
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*
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* QP for Stage 3 exits (placements 9–16) is sub-ranked by W-L record:
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* - 2-3 teams → higher placements within 9–16
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* - 1-3 teams → middle placements
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* - 0-3 teams → lowest placements within 9–16
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* QP is tie-split (averaged) within each W-L group.
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*
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* Stages 1 and 2 exits (placements 17–32) earn 0 QP.
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*/
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import { database } from "~/database/context";
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import { eq, and, inArray } from "drizzle-orm";
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import * as schema from "~/database/schema";
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import { getQPConfig } from "~/models/qualifying-points";
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import { getCs2StageResultsMapForEvent } from "~/models/cs2-major-stage";
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import type { Simulator, SimulationResult } from "./types";
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// ─── Simulation parameters ────────────────────────────────────────────────────
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const NUM_SIMULATIONS = 10_000;
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/** Total field size per CS2 Major. */
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const FIELD_SIZE = 32;
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/** Number of teams guaranteed in the simulated field (always included). */
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const GUARANTEED_COUNT = 12;
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/**
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* Elo divisor for per-game win probability.
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* Standard chess Elo uses 400. CS2 maps well to single-game level.
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* 200-pt gap ≈ 76% win probability; 400-pt gap ≈ 91%.
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*/
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const ELO_DIVISOR = 400;
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/** Fallback Elo for teams with no stored rating. */
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const FALLBACK_ELO = 1500;
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// ─── Math helpers ─────────────────────────────────────────────────────────────
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/**
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* Per-game win probability for team 1 vs team 2.
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* Exported for unit testing.
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*/
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export function gameWinProb(elo1: number, elo2: number): number {
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return 1 / (1 + Math.pow(10, (elo2 - elo1) / ELO_DIVISOR));
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}
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/**
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* Match win probability using the Bernoulli series model.
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* For a best-of-(2S-1) match (first to S wins):
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* P(win) = Σ_{k=0}^{S-1} C(S-1+k, k) × p^S × (1-p)^k
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* Exported for unit testing.
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*/
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export function seriesWinProb(p: number, winsNeeded: number): number {
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let prob = 0;
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for (let k = 0; k < winsNeeded; k++) {
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prob += binomialCoeff(winsNeeded - 1 + k, k) * Math.pow(p, winsNeeded) * Math.pow(1 - p, k);
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}
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return prob;
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}
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/** Binomial coefficient C(n, k). */
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function binomialCoeff(n: number, k: number): number {
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if (k === 0) return 1;
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if (k > n - k) k = n - k;
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let result = 1;
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for (let i = 0; i < k; i++) {
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result = (result * (n - i)) / (i + 1);
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}
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return result;
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}
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/** Fisher-Yates in-place shuffle. Returns the array for chaining. */
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function shuffle<T>(arr: T[]): T[] {
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for (let i = arr.length - 1; i > 0; i--) {
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const j = Math.floor(Math.random() * (i + 1));
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[arr[i], arr[j]] = [arr[j], arr[i]];
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}
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return arr;
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}
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// ─── Field selection ──────────────────────────────────────────────────────────
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interface TeamWithElo {
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id: string;
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elo: number;
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rank: number; // HLTV world ranking (lower = better)
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}
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/**
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* Sample a 32-team field from the pool.
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* - Top GUARANTEED_COUNT (12) by rank are always included.
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* - Remaining spots are weighted-randomly sampled from the rest, weight = 1/rank.
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* - If pool.length <= FIELD_SIZE, returns all teams.
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* Exported for unit testing.
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*/
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export function sampleField(
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pool: TeamWithElo[],
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fieldSize: number = FIELD_SIZE
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): TeamWithElo[] {
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const sorted = [...pool].toSorted((a, b) => a.rank - b.rank);
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if (sorted.length <= fieldSize) return sorted;
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const guaranteed = sorted.slice(0, GUARANTEED_COUNT);
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const rest = sorted.slice(GUARANTEED_COUNT);
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const needed = fieldSize - guaranteed.length;
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if (needed <= 0) return guaranteed;
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if (rest.length <= needed) return [...guaranteed, ...rest];
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// Weighted sample without replacement, weight = 1/rank
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const weights = rest.map((t) => 1 / t.rank);
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const sampled = weightedSampleWithoutReplacement(rest, weights, needed);
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return [...guaranteed, ...sampled];
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}
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/** Weighted sampling without replacement using the Gumbel-max trick. */
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function weightedSampleWithoutReplacement<T>(
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items: T[],
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weights: number[],
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count: number
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): T[] {
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const keys = weights.map((w) => -Math.log(Math.random()) / w);
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const indexed = items.map((item, i) => ({ item, key: keys[i] }));
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const sortedIndexed = indexed.toSorted((a, b) => a.key - b.key);
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return sortedIndexed.slice(0, count).map((x) => x.item);
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}
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// ─── Swiss stage simulation ───────────────────────────────────────────────────
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interface SwissResult {
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/** Teams that advanced (3 wins). */
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advanced: Array<{ id: string; elo: number; rank: number }>;
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/** Teams eliminated, with their win count at time of elimination. */
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eliminated: Array<{ id: string; elo: number; rank: number; wins: number }>;
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}
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/**
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* Simulate one Swiss-format stage.
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* Teams are grouped by their (wins, losses) record each round. Teams are paired
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* randomly within each record group. First to 3 wins advances; first to 3 losses
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* is eliminated.
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*
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* @param teams - Teams entering this stage.
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* @param bo3 - If true, use Bo3 series win probability; otherwise Bo1 (single game).
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* @returns advanced and eliminated arrays.
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*
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* Exported for unit testing.
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*/
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export function simulateSwiss(teams: TeamWithElo[], bo3: boolean): SwissResult {
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const wins = new Map<string, number>(teams.map((t) => [t.id, 0]));
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const losses = new Map<string, number>(teams.map((t) => [t.id, 0]));
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const eloMap = new Map<string, number>(teams.map((t) => [t.id, t.elo]));
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const advanced: SwissResult["advanced"] = [];
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const eliminated: SwissResult["eliminated"] = [];
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const advancedIds = new Set<string>();
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const eliminatedIds = new Set<string>();
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const teamById = new Map<string, TeamWithElo>(teams.map((t) => [t.id, t]));
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// Run rounds until every team has reached 3W or 3L
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while (advancedIds.size + eliminatedIds.size < teams.length) {
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// Collect active teams grouped by (W, L) record
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const active = teams.filter((t) => !advancedIds.has(t.id) && !eliminatedIds.has(t.id));
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const groups = groupByRecord(active, wins, losses);
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// If a group has an odd number, move one team to the nearest adjacent group
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// (simplified: skip teams that can't be paired — they sit out this round)
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const pairs = pairGroups(groups);
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// Safety: if no pairs can be formed (shouldn't happen with even team counts
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// but guards against an infinite loop if an odd active count somehow occurs)
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if (pairs.length === 0) break;
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for (const [t1, t2] of pairs) {
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const e1 = eloMap.get(t1.id) ?? FALLBACK_ELO;
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const e2 = eloMap.get(t2.id) ?? FALLBACK_ELO;
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const p = bo3
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? seriesWinProb(gameWinProb(e1, e2), 2) // Bo3: first to 2
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: gameWinProb(e1, e2); // Bo1: single game
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const t1Wins = Math.random() < p;
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const winnerId = t1Wins ? t1.id : t2.id;
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const loserId = t1Wins ? t2.id : t1.id;
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wins.set(winnerId, (wins.get(winnerId) ?? 0) + 1);
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losses.set(loserId, (losses.get(loserId) ?? 0) + 1);
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if ((wins.get(winnerId) ?? 0) >= 3) {
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advancedIds.add(winnerId);
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const t = teamById.get(winnerId);
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if (t) advanced.push({ id: t.id, elo: t.elo, rank: t.rank });
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}
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if ((losses.get(loserId) ?? 0) >= 3) {
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eliminatedIds.add(loserId);
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const t = teamById.get(loserId);
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if (t) eliminated.push({ id: t.id, elo: t.elo, rank: t.rank, wins: wins.get(loserId) ?? 0 });
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}
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}
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}
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return { advanced, eliminated };
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}
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/** Group active teams by (wins, losses) record key. */
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function groupByRecord(
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active: TeamWithElo[],
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wins: Map<string, number>,
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losses: Map<string, number>
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): Map<string, TeamWithElo[]> {
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const groups = new Map<string, TeamWithElo[]>();
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for (const t of active) {
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const key = `${wins.get(t.id) ?? 0}-${losses.get(t.id) ?? 0}`;
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if (!groups.has(key)) groups.set(key, []);
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groups.get(key)?.push(t);
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}
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return groups;
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}
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/**
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* Pair teams within each record group. Teams in groups with an odd count
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* are handled by merging the leftover into an adjacent group (simpler: skip
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* them for this round — they sit out and play next round).
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*/
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function pairGroups(groups: Map<string, TeamWithElo[]>): Array<[TeamWithElo, TeamWithElo]> {
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const pairs: Array<[TeamWithElo, TeamWithElo]> = [];
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const leftover: TeamWithElo[] = [];
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for (const group of groups.values()) {
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const shuffled = shuffle([...group]);
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for (let i = 0; i + 1 < shuffled.length; i += 2) {
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pairs.push([shuffled[i], shuffled[i + 1]]);
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}
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if (shuffled.length % 2 !== 0) {
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leftover.push(shuffled[shuffled.length - 1]);
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}
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}
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// Pair leftover teams with each other (different records, cross-group match)
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for (let i = 0; i + 1 < leftover.length; i += 2) {
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pairs.push([leftover[i], leftover[i + 1]]);
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}
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return pairs;
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}
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// ─── Champions Stage (8-team single-elimination bracket) ─────────────────────
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interface ChampionsResult {
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placements: Map<string, number>; // participantId → placement (1–8)
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}
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/**
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* Simulate the Champions Stage 8-team single-elimination bracket.
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* Seeds are assigned by rank within the 8 advancing teams.
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* Rounds: QF (Bo3), SF (Bo3), GF (Bo5).
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* Exported for unit testing.
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*/
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export function simulateChampionsStage(teams: TeamWithElo[]): ChampionsResult {
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if (teams.length !== 8) {
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throw new Error(`simulateChampionsStage expects exactly 8 teams, got ${teams.length}`);
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}
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// Seed by rank ascending
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const seeded = [...teams].toSorted((a, b) => a.rank - b.rank);
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// Standard 8-team seeding: 1v8, 4v5, 3v6, 2v7
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const bracket: [TeamWithElo, TeamWithElo][] = [
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[seeded[0], seeded[7]],
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[seeded[3], seeded[4]],
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[seeded[2], seeded[5]],
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[seeded[1], seeded[6]],
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];
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const placements = new Map<string, number>();
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const simMatch = (t1: TeamWithElo, t2: TeamWithElo, winsNeeded: number): TeamWithElo => {
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const p = seriesWinProb(gameWinProb(t1.elo, t2.elo), winsNeeded);
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return Math.random() < p ? t1 : t2;
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};
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// Quarterfinals (Bo3 = first to 2)
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const sfTeams: TeamWithElo[] = [];
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for (const [t1, t2] of bracket) {
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const winner = simMatch(t1, t2, 2);
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const loser = winner.id === t1.id ? t2 : t1;
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sfTeams.push(winner);
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placements.set(loser.id, 7); // QF losers: 5th–8th (averaged to 6.5, use 7 for counting)
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}
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// Assign QF losers to placements 5–8
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const qfLosers = [...placements.keys()];
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qfLosers.forEach((id, i) => placements.set(id, 5 + i));
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// Semifinals (Bo3 = first to 2)
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const finalTeams: TeamWithElo[] = [];
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const sfLosers: TeamWithElo[] = [];
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for (let i = 0; i < sfTeams.length; i += 2) {
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const winner = simMatch(sfTeams[i], sfTeams[i + 1], 2);
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const loser = winner.id === sfTeams[i].id ? sfTeams[i + 1] : sfTeams[i];
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finalTeams.push(winner);
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sfLosers.push(loser);
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}
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sfLosers.forEach((t, i) => placements.set(t.id, 3 + i));
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// Grand Final (Bo5 = first to 3)
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const champion = simMatch(finalTeams[0], finalTeams[1], 3);
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const finalist = champion.id === finalTeams[0].id ? finalTeams[1] : finalTeams[0];
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placements.set(champion.id, 1);
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placements.set(finalist.id, 2);
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return { placements };
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}
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// ─── QP helpers ───────────────────────────────────────────────────────────────
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/**
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* Calculate QP for Stage 3 exits based on their W-L record.
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* Teams are ranked within 9–16 by wins (2-3 > 1-3 > 0-3).
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* Within the same wins count, QP is tie-split (averaged) across placement slots.
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*
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* qpConfig: array indexed by placement (1-indexed), qpConfig[placement] = QP value.
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* Placements 9–16 correspond to indices 9–16.
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*/
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function calcStage3ExitQP(
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elimTeams: Array<{ id: string; wins: number }>,
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qpConfig: Map<number, number>
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): Map<string, number> {
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// Group teams by wins count (0, 1, 2)
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const byWins = new Map<number, string[]>();
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for (const t of elimTeams) {
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if (!byWins.has(t.wins)) byWins.set(t.wins, []);
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byWins.get(t.wins)?.push(t.id);
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}
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// Assign placement slots 9–16 from highest wins first
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const result = new Map<string, number>();
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const winsGroups = [...byWins.entries()].toSorted((a, b) => b[0] - a[0]); // descending wins
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let slotStart = 9;
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for (const [, ids] of winsGroups) {
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const slots = Array.from({ length: ids.length }, (_, i) => slotStart + i);
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const avgQP = slots.reduce((sum, s) => sum + (qpConfig.get(s) ?? 0), 0) / slots.length;
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for (const id of ids) {
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result.set(id, avgQP);
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}
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slotStart += ids.length;
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}
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return result;
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}
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// ─── Simulator ────────────────────────────────────────────────────────────────
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export class CSMajorSimulator implements Simulator {
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async simulate(sportsSeasonId: string): Promise<SimulationResult[]> {
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const db = database();
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// 1. Load all participants for this sports season.
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const allParticipants = await db
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.select({ id: schema.participants.id })
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.from(schema.participants)
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.where(eq(schema.participants.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.participantExpectedValues.participantId,
|
||
sourceElo: schema.participantExpectedValues.sourceElo,
|
||
worldRanking: schema.participantExpectedValues.worldRanking,
|
||
})
|
||
.from(schema.participantExpectedValues)
|
||
.where(eq(schema.participantExpectedValues.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 with Elo ratings, sorted by rank
|
||
const pool: TeamWithElo[] = participantIds
|
||
.filter((id) => eloMap.has(id))
|
||
.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);
|
||
|
||
if (pool.length === 0) {
|
||
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 1–16 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.participantId,
|
||
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 each event (for explicit field composition).
|
||
const eventStageResults = new Map<string, Awaited<ReturnType<typeof getCs2StageResultsMapForEvent>>>();
|
||
for (const event of events) {
|
||
const stageResults = await getCs2StageResultsMapForEvent(event.id);
|
||
if (stageResults.size > 0) {
|
||
eventStageResults.set(event.id, stageResults);
|
||
}
|
||
}
|
||
|
||
const incompleteEvents = events.filter((e) => !e.isComplete);
|
||
|
||
// 7. 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 stageResultsForEvent = eventStageResults.get(event.id);
|
||
const eventQP = simulateOneMajor(pool, stageResultsForEvent, qpConfig);
|
||
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]++;
|
||
}
|
||
}
|
||
|
||
// 8. 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 ───────────────────────────────────────────────────
|
||
|
||
/**
|
||
* Simulate one CS2 Major and return QP earned per participant.
|
||
*
|
||
* If stage results are provided, uses them to determine field composition
|
||
* and to lock in results for any completed stages, only simulating the
|
||
* remaining stages. A stage is considered complete when the expected 8
|
||
* eliminations for that stage have been recorded.
|
||
*
|
||
* Returns a Map from participantId → QP earned in this major.
|
||
*/
|
||
function simulateOneMajor(
|
||
pool: TeamWithElo[],
|
||
stageResults: Map<string, { stageEntry: number; stageEliminated: number | null; stageEliminatedWins: number | null }> | undefined,
|
||
qpConfig: Map<number, number>
|
||
): Map<string, number> {
|
||
const qpMap = new Map<string, number>();
|
||
const poolById = new Map<string, TeamWithElo>(pool.map((t) => [t.id, t]));
|
||
|
||
// ── Determine field and stage assignments ─────────────────────────────────
|
||
let stage1Teams: TeamWithElo[];
|
||
let stage2Direct: TeamWithElo[];
|
||
let stage3Direct: TeamWithElo[];
|
||
|
||
if (stageResults && stageResults.size > 0) {
|
||
const s1: TeamWithElo[] = [];
|
||
const s2: TeamWithElo[] = [];
|
||
const s3: TeamWithElo[] = [];
|
||
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);
|
||
else if (result.stageEntry === 3) s3.push(team);
|
||
}
|
||
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);
|
||
stage2Direct = sorted.slice(8, 16);
|
||
stage1Teams = sorted.slice(16, 32);
|
||
}
|
||
|
||
// ── Lock in known stage results ───────────────────────────────────────────
|
||
// A stage is "complete" when exactly 8 teams have been recorded as
|
||
// eliminated at that stage (the expected output of each Swiss stage).
|
||
const eliminatedAtStage = (stageNum: number) =>
|
||
stageResults
|
||
? [...stageResults.entries()]
|
||
.filter(([, r]) => r.stageEliminated === stageNum)
|
||
.map(([id, r]) => ({
|
||
id,
|
||
elo: poolById.get(id)?.elo ?? FALLBACK_ELO,
|
||
rank: poolById.get(id)?.rank ?? 9999,
|
||
wins: r.stageEliminatedWins ?? 0,
|
||
}))
|
||
: [];
|
||
|
||
const stage1Elim = eliminatedAtStage(1);
|
||
const stage2Elim = eliminatedAtStage(2);
|
||
const stage3Elim = eliminatedAtStage(3);
|
||
|
||
const stage1Complete = stage1Elim.length === 8;
|
||
const stage2Complete = stage2Elim.length === 8;
|
||
const stage3Complete = stage3Elim.length === 8;
|
||
|
||
// ── Stage 1 ───────────────────────────────────────────────────────────────
|
||
let stage1Advanced: TeamWithElo[];
|
||
let stage1EliminatedFinal: Array<{ id: string; elo: number; rank: number; wins: number }>;
|
||
|
||
if (stage1Complete) {
|
||
// Use known results: teams that entered Stage 1 but weren't eliminated there advanced
|
||
const stage1EliminatedIds = new Set(stage1Elim.map((t) => t.id));
|
||
stage1Advanced = stage1Teams.filter((t) => !stage1EliminatedIds.has(t.id));
|
||
stage1EliminatedFinal = stage1Elim;
|
||
} else {
|
||
const result = simulateSwiss(stage1Teams, false);
|
||
stage1Advanced = result.advanced;
|
||
stage1EliminatedFinal = result.eliminated;
|
||
}
|
||
|
||
// ── Stage 2 ───────────────────────────────────────────────────────────────
|
||
const stage2Teams = [...stage2Direct, ...stage1Advanced];
|
||
let stage2Advanced: TeamWithElo[];
|
||
let stage2EliminatedFinal: Array<{ id: string; elo: number; rank: number; wins: number }>;
|
||
|
||
if (stage2Complete) {
|
||
const stage2EliminatedIds = new Set(stage2Elim.map((t) => t.id));
|
||
stage2Advanced = stage2Teams.filter((t) => !stage2EliminatedIds.has(t.id));
|
||
stage2EliminatedFinal = stage2Elim;
|
||
} else {
|
||
const result = simulateSwiss(stage2Teams, false);
|
||
stage2Advanced = result.advanced;
|
||
stage2EliminatedFinal = result.eliminated;
|
||
}
|
||
|
||
// ── Stage 3 ───────────────────────────────────────────────────────────────
|
||
const stage3Teams = [...stage3Direct, ...stage2Advanced];
|
||
let champTeams: TeamWithElo[];
|
||
let stage3EliminatedFinal: Array<{ id: string; elo: number; rank: number; wins: number }>;
|
||
|
||
if (stage3Complete) {
|
||
const stage3EliminatedIds = new Set(stage3Elim.map((t) => t.id));
|
||
champTeams = stage3Teams.filter((t) => !stage3EliminatedIds.has(t.id));
|
||
stage3EliminatedFinal = stage3Elim;
|
||
} else {
|
||
const result = simulateSwiss(stage3Teams, true);
|
||
champTeams = result.advanced;
|
||
stage3EliminatedFinal = result.eliminated;
|
||
}
|
||
|
||
// ── Champions Stage ───────────────────────────────────────────────────────
|
||
const champResult = simulateChampionsStage(champTeams);
|
||
|
||
// ── Assign QP ─────────────────────────────────────────────────────────────
|
||
for (const [pid, placement] of champResult.placements) {
|
||
qpMap.set(pid, qpConfig.get(placement) ?? 0);
|
||
}
|
||
|
||
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);
|
||
|
||
return qpMap;
|
||
}
|