c097e4827c
* Add MLS sport simulator (mls_bracket)
Adds Major League Soccer as a draftable sport with a full-season Monte Carlo
simulator. Models both preseason regular-season projection (34 games across
Eastern and Western conferences) and the MLS Cup Playoffs bracket, including
the Wild Card (single game + PKs), Round 1 best-of-3 series, Conference
Semis/Finals (single game), and MLS Cup.
P1–P8 mapping: MLS Cup winner, finalist, Conference Finals losers, Conference
Semifinals losers. Conference assignment reads from regularSeasonStandings.conference
or falls back to the region simulator input ("Eastern"/"Western").
Admin inputs: projectedTablePoints (primary, max 102 for 34×3), with derivation
chain to sourceElo via existing input-policy; sourceOdds as alternative.
No hardcoded team data — all inputs are admin-managed per season.
- database/schema.ts: add mls_bracket to simulatorTypeEnum
- drizzle/0104_chief_boom_boom.sql: migration for the new enum value
- mls-simulator.ts: MLSSimulator + exported pure helpers for testability
- registry.ts / manifest.ts / simulator-config.ts: register mls_bracket
- mls-simulator.test.ts: 38 unit tests covering all helpers and sync checks
https://claude.ai/code/session_015wkBJ3SYGcMGjsddKKGkwa
* Fix MLS simulator: config loading, sourceOdds fallback, normalization
Three issues found in code review comparing against EPL and NFL simulators:
1. Load simulator config from DB via getSportsSeasonSimulatorConfig so
admins can override iterations, seasonGames, parityFactor, drawRates
per season without code changes. Previously all constants were hardcoded.
2. Add sourceOdds → convertFuturesToElo fallback when no sourceElo is
present. EPL and NFL both do this; MLS was throwing immediately instead
of attempting the odds conversion that the manifest declares as optional.
3. Call normalizeSimulationResultColumns before returning results, matching
EPL's local normalization pattern for consistency (runner also normalizes
globally, but EPL calls it locally too).
https://claude.ai/code/session_015wkBJ3SYGcMGjsddKKGkwa
* Polish MLS simulator: configNumber zero, logger warning, Map lookup
Three small fixes from secondary code review:
1. configNumber: allow value >= 0 (not just > 0) so admins can
legitimately set baseDrawRate or drawDecay to 0 without the value
being silently discarded and replaced with the default.
2. Add logger.warn when a participant is excluded from simulation due
to a missing Elo rating, matching the NLL bracket-aware pattern.
Gives admins a visible signal instead of a silent exclusion.
3. getBySeeds: build a Map once instead of calling Array.find() per
seed. Eliminates 4M linear scans across 50k iterations for a 9-
element array — trivially fast either way, but Map is the right tool.
https://claude.ai/code/session_015wkBJ3SYGcMGjsddKKGkwa
---------
Co-authored-by: Claude <noreply@anthropic.com>
110 lines
3.2 KiB
TypeScript
110 lines
3.2 KiB
TypeScript
/**
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* Simulator Configuration
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*
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* Per-sport parameters used by simulators and admin UI tools.
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* Centralizes season length, parity factors, and other sport-specific
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* constants so they can be shared between simulators and the Elo Ratings
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* admin page (e.g., for projected wins → Elo conversion).
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*/
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import type { SimulatorType } from "./registry";
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export interface SimulatorConfig {
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/** Total regular season games per team in this sport. */
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seasonGames: number;
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/** Elo parity factor for single-game win probability.
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* P(A) = 1 / (1 + 10^((eloB - eloA) / parityFactor))
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* Higher = more unpredictable per game. */
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parityFactor: number;
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/** Average opponent Elo — used for season projections against a generic opponent. */
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averageOpponentElo: number;
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/** Label/type for the admin projection input. Defaults to projected wins. */
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projectionInput?: "wins" | "tablePoints";
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}
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const CONFIG: Record<SimulatorType, SimulatorConfig | null> = {
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afl_bracket: {
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seasonGames: 23,
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parityFactor: 450,
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averageOpponentElo: 1500,
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},
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nfl_bracket: {
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seasonGames: 17,
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parityFactor: 400,
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averageOpponentElo: 1500,
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},
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nba_bracket: {
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seasonGames: 82,
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parityFactor: 400,
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averageOpponentElo: 1500,
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},
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nhl_bracket: {
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seasonGames: 82,
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// NHL is the highest-parity major North American league — roughly 1 in 3 games
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// goes to overtime/shootout and favourites win far less reliably than in NBA/NFL.
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// 1000 was calibrated so that a team projected at 55 wins (67%) maps to ~1570 Elo,
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// which keeps the spread tight and reflects the empirical upset rate.
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parityFactor: 1000,
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averageOpponentElo: 1500,
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},
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mlb_bracket: {
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seasonGames: 162,
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parityFactor: 400,
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averageOpponentElo: 1500,
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},
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epl_standings: {
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seasonGames: 38,
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parityFactor: 400,
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averageOpponentElo: 1500,
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projectionInput: "tablePoints",
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},
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wnba_bracket: {
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seasonGames: 44,
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parityFactor: 400,
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averageOpponentElo: 1500,
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},
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nll_bracket: {
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seasonGames: 18,
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parityFactor: 400,
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averageOpponentElo: 1500,
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},
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mls_bracket: {
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seasonGames: 34,
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parityFactor: 400,
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averageOpponentElo: 1500,
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projectionInput: "tablePoints",
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},
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// Simulators below don't use projected-wins → Elo conversion.
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// They can be populated later if needed.
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f1_standings: null,
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indycar_standings: null,
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golf_qualifying_points: null,
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playoff_bracket: null,
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ucl_bracket: null,
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ncaam_bracket: null,
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ncaaw_bracket: null,
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snooker_bracket: null,
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tennis_qualifying_points: null,
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world_cup: null,
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darts_bracket: null,
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cs2_major_qualifying_points: null,
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ncaa_football_bracket: null,
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llws_bracket: null,
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college_hockey_bracket: null,
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brackt: null,
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};
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/**
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* Get the simulator config for a given simulator type.
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* Returns null for simulator types that don't have season-game / Elo config.
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*/
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export function getSimulatorConfig(simulatorType: SimulatorType): SimulatorConfig | null {
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return CONFIG[simulatorType];
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}
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/**
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* Check if a simulator type supports projected-wins → Elo conversion.
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*/
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export function supportsProjectedWins(simulatorType: SimulatorType): boolean {
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return CONFIG[simulatorType] !== null;
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}
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