7b85934dc3
The platoon test's n=452 described how much of the JOIN survived, not how much data exists. There are 1,266 clean settled hits rows and zero quarantined ones. platoon_splits had been ingested from tonight's lineups only (315 players), so any hitter who settled a prop without appearing in an ingest-day lineup was silently absent from every test. Backfilled all 380 hitters (81 fetched, 0 unresolved). Re-ran on 1,059 rows, up from 452. THE DEMOTION IS THE HEADLINE. pitcher_contact_profile, the strongest proven factor in the programme (-0.0064, CI [-0.0113,-0.0014]), roughly halved to -0.0034 on more than double the sample and its corrected interval now spans zero. The Bonferroni denominator also rose to 55, which widens every interval -- but a denominator cannot move a point estimate, and that halved on its own. platoon and platoon_severity now clear the bar and are NOT promoted. Upper bound -0.0001, on season-to-date splits that contain the games they predict: measured contamination is 4.5% median, 12.4% at p90, 137% worst. I had assumed ~1%. They stay CANDIDATE pending point-in-time splits. GAME-LEVEL IS A DIFFERENT PROBLEM. game_context held zero weather rows ever -- not because the fetcher was wrong (it correctly targets Open-Meteo's archive) but because ledger_entries keys a game as mlb:2026-08-03:Away@Home and game_context keys it as mlb:823437. Every lookup missed and NULL columns read as honest absence. Third occurrence of that class. Fixed the join: 96/101 settled games now carry actual archived weather, park dimensions backfilled 15 -> 30 venues. But 928 total_bases rows sit on 47 games at 17.6 rows per game. Park and weather assign one value per game, so resampling rows would have manufactured a pass. factorGate now resamples clusters when rows carry one and judges sample against effective_n; unclustered rows keep the original path byte-for-byte. Verdict: 47 clusters < 500, and the point estimate is +0.0011 -- worse, not merely unproven. Weather needs ~57 more days. Park dimensions need never: there are 30 ballparks in MLB, so a venue-constant factor can never reach 500 independent units. That bar was built for player-level factors and does not transfer. Wind is refused. We have speed and bearing for all 96 games; we lack park orientation, and 220 degrees is blowing out at one park and in at another. Using speed alone would assert an effect while discarding the sign that decides what it is. Counter and frozen clusters untouched. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01W1sivYNqY2TS5ftykmHBU9
104 lines
4.4 KiB
JavaScript
104 lines
4.4 KiB
JavaScript
#!/usr/bin/env node
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'use strict';
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/**
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* backfill-context — WERE WE WAITING, OR UNDER-QUERYING?
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*
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* The platoon test ran on 452 rows against 1,266 clean settled hits rows in the
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* ledger, so "48 short of the gate" was never a statement about how much data
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* exists. It was a statement about how much the JOIN survived — and the join was
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* losing rows to inputs we simply had not fetched for every player.
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*
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* This backfills the inputs (pure sample, zero waiting) and reports exactly
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* where each row is lost, so the next "we need more data" claim is a measured
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* one rather than an inherited one.
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*
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* ── THE ONE HONEST CAVEAT, STATED UP FRONT ───────────────────────────────
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* Platoon splits from statsapi are SEASON-TO-DATE as of the moment they are
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* fetched. Applying today's split to a 2026-07-15 game means the split contains
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* that game. For a ~400-PA season line one game is roughly a quarter of one
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* percent, so the contamination is small — but it is real, it runs in the
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* flattering direction, and it is why this is labelled a reconstruction rather
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* than a clean point-in-time backtest.
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*
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* SUPABASE_URL=... node scripts/backfill-context.js
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*/
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require('dotenv').config();
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const { createClient } = require('@supabase/supabase-js');
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const ctx = require('../src/services/lineupContextService');
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const mlb = require('../src/services/adapters/mlbStatsAdapter');
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const { knownNumber } = require('../src/utils/known');
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const SB_URL = process.env.SUPABASE_URL;
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const SB_KEY = process.env.SUPABASE_SERVICE_ROLE_KEY || process.env.SUPABASE_SERVICE_KEY;
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const SEASON = Number(process.env.BF_SEASON || 2026);
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const PAGE = 1000;
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async function page(sb, table, select, apply) {
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const out = [];
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for (let from = 0; ; from += PAGE) {
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const { data, error } = await apply(sb.from(table).select(select)).range(from, from + PAGE - 1);
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if (error) throw error;
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if (!data || data.length === 0) break;
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out.push(...data);
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if (data.length < PAGE) break;
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}
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return out;
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}
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async function main() {
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if (!SB_URL || !SB_KEY) throw new Error('SUPABASE_URL / service key required');
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const sb = createClient(SB_URL, SB_KEY, { auth: { persistSession: false } });
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// Every hitter who appears on a CLEAN settled row — the true denominator.
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const led = await page(sb, 'ledger_entries', 'player_key, player_name, stat, outcome, quarantine_reason',
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(q) => q.eq('sport', 'mlb').is('user_id', null).in('stat', ['hits', 'total_bases'])
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.in('outcome', ['hit', 'miss']));
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const need = new Map();
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for (const r of led) {
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if ((r.quarantine_reason || '').startsWith('nontakeable_book')) continue;
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if (!need.has(r.player_key)) need.set(r.player_key, r.player_name);
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}
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const have = new Set((await page(sb, 'platoon_splits', 'player_key', (q) => q.eq('sport', 'mlb')))
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.map((r) => r.player_key));
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const missing = [...need.entries()].filter(([k]) => !have.has(k));
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console.error(`[backfill] hitters on clean settled rows: ${need.size}; splits already held: ${have.size}; to fetch: ${missing.length}`);
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const asOf = ctx.dateET();
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const rows = [];
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let unresolved = 0;
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for (const [key, name] of missing) {
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let found = null;
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try { found = await mlb.searchPlayer(name); } catch { found = null; }
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if (!found || !found.id) { unresolved += 1; continue; }
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const sp = await ctx.fetchPlatoonSplits(found.id, SEASON, {});
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if (!sp) continue; // absent, never a symmetric guess
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rows.push({ player_key: key, player_name: name, source_id: found.id, ...sp });
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}
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let written = 0;
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for (let i = 0; i < rows.length; i += 200) {
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const batch = rows.slice(i, i + 200).map((r) => ({ ...r, sport: 'mlb', season: SEASON, as_of_date: asOf }));
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const { error } = await sb.from('platoon_splits')
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.upsert(batch, { onConflict: 'as_of_date,sport,season,player_key' });
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if (!error) written += batch.length;
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else console.error('[backfill] write failed:', error.message);
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}
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console.log(JSON.stringify({
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hitters_on_clean_settled_rows: need.size,
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splits_held_before: have.size,
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attempted: missing.length,
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unresolved_by_name: unresolved,
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no_splits_available: missing.length - unresolved - rows.length,
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written,
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caveat: 'season-to-date splits applied to past games contain those games — small (~0.25% of a 400-PA line) but real and flattering',
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}, null, 2));
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process.exit(0);
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}
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main().catch((e) => { console.error(e); process.exit(1); });
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