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Add adaptive sports favorite pilot

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Theodore Song
2026-08-20 17:31:41 -04:00
parent 5f14d012a5
commit 7e75d98d8c
4 changed files with 214 additions and 47 deletions
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scripts/evaluate-sports-favorites.mjs
+7 -2
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@@ -4,6 +4,7 @@ const MARKET_LIMIT = Math.max(500, Math.min(5000, Number(process.env.SPORTS_FAVO
const CONCURRENCY = Math.max(1, Math.min(12, Number(process.env.SPORTS_FAVORITE_CONCURRENCY || 10)));
const COST = Math.max(0, Math.min(0.10, Number(process.env.SPORTS_FAVORITE_COST_CENTS || 5) / 100));
const MAX_STALENESS_HOURS = Math.max(1, Math.min(12, Number(process.env.SPORTS_FAVORITE_MAX_STALENESS_HOURS || 3)));
const EVENT_LEGS = Math.max(1, Math.min(4, Number(process.env.SPORTS_FAVORITE_EVENT_LEGS || 1)));
const HOUR = 3600;
function parseJson(value) {
@@ -147,7 +148,7 @@ function tradesFor(partition, rule) {
const rows = events.get(row.eventKey) || [];
rows.push(row);events.set(row.eventKey, rows);
});
return [...events.values()].flatMap((rows) => rows.sort((a, b) => b.entry - a.entry || a.marketId.localeCompare(b.marketId)).slice(0, 4));
return [...events.values()].flatMap((rows) => rows.sort((a, b) => b.entry - a.entry || a.marketId.localeCompare(b.marketId)).slice(0, EVENT_LEGS));
}
const evaluated = rules.map((rule) => {
@@ -162,15 +163,19 @@ const selected = evaluated.filter((row) => row.validationPassed).sort((a, b) =>
const baseline = evaluated.find((row) => row.rule.leadHours === 24 && row.rule.minEntry === 0.55 && row.rule.maxEntry === 0.95);
const compact = (stats) => Object.fromEntries(Object.entries(stats).map(([key, value]) => [key, Number.isFinite(value) ? +value.toFixed(5) : value]));
const candidate = (row) => ({ rule: row.rule, train: compact(row.train), validation: compact(row.validation), holdout: compact(row.holdout), passesHoldout: row.passesHoldout });
const closest = evaluated.filter((row) => row.train.events >= 25 && row.validation.events >= 10 && row.holdout.events >= 10)
.sort((a, b) => Math.min(b.train.lower, b.validation.lower, b.holdout.lower)
- Math.min(a.train.lower, a.validation.lower, a.holdout.lower));
console.log(JSON.stringify({ generatedAt: new Date().toISOString(), requestedMarkets: MARKET_LIMIT, sportsMarkets: markets.length,
historiesWithData: usable.length, failures: histories.filter((row) => row?.error).length,
methodology: { selection: "most recently closed eligible Yes/No sports markets", decisionAnchor: "published game start",
historyFidelityMinutes: 60, maxPriceStalenessHours: MAX_STALENESS_HOURS, modeledCostCents: COST * 100,
split: "60% train / 20% validation / 20% untouched holdout", clusterUnit: "equal-dollar event baskets split across at most four highest-priced eligible favorites", testedRules: rules.length },
split: "60% train / 20% validation / 20% untouched holdout", clusterUnit: `one equal-dollar position in each event's highest-priced eligible favorite (event legs ${EVENT_LEGS})`, testedRules: rules.length },
partitionMarkets: Object.fromEntries(Object.entries(partitions).map(([key, value]) => [key, value.length])),
trainPassed: evaluated.filter((row) => row.trainPassed).length, validationSelected: selected.length,
holdoutPassed: selected.filter((row) => row.passesHoldout).length, baseline: baseline ? candidate(baseline) : null,
closestCandidates: closest.slice(0, 15).map(candidate),
candidates: selected.slice(0, 20).map(candidate),
holdoutExamples: (selected.find((row) => row.passesHoldout)?.holdoutRows || []).slice(0, 12)
.map((row) => ({ question: row.question, event: row.event, side: row.side, entry: +row.entry.toFixed(4), won: row.won, netReturn: +row.netReturn.toFixed(4) }))