Files
vyndr/scripts/prove-hit-factors.js
T
builtbykev 6452926732 Retain raw weather, and record platoon severity 48 rows short
Two fixes in the weather path, and the second was hiding behind the first. The
scalar weather_mod cannot express a hit-TYPE conversion at all -- wind out and
warm turning fly balls into extra bases, and cold heavy air turning them into
outs, collapse to the same number once multiplied -- so the raw temperature,
wind speed and wind direction are now retained alongside it.

And the old guard only kept the environment when the multiplier was not 1,
which silently discarded the forecast for every ordinary night. That is the
majority of games, and precisely the rows a hit-type model would need in order
to learn what ordinary looks like.

Platoon severity is built and measured at n=452, which is 48 rows short of the
gate: CANDIDATE_PENDING, neither proven nor theatre. It moves less than flat
platoon (0.021 against 0.026), consistent with the pattern, and its Brier point
estimate is favourable but the corrected interval still spans zero.

Worth naming: the refusal costs sample, and that is the design working. Flat
platoon scores 741 rows because it will happily apply a boost to anyone;
severity scores 452 because the other 289 are hitters whose split we cannot
actually read at 60 plate appearances on the short side. Buying those rows back
by shrinking instead of refusing would have produced a number indistinguishable
from a measured league-average split, which is a different claim from the one
the data supports.

Park dimensions are ingested and verified in production across fifteen venues,
joined by the venue the game is actually at rather than inferred from the home
team -- neutral-site and international games break that assumption without
surfacing an error.

The park-and-weather-to-hit-type atom is NOT built. Its inputs landed this
session and carry a single as_of date, so testing it on total_bases would be
scoring games with inputs that postdate them. Building it now would produce
something plausible rather than something proven.

Proven factors for hits remain pitcher_contact_profile and
defense_by_direction. 4,307 tests green (344 suites); web build exit 0.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01W1sivYNqY2TS5ftykmHBU9
2026-08-04 20:40:56 -04:00

257 lines
12 KiB
JavaScript

#!/usr/bin/env node
'use strict';
/**
* prove-hit-factors — does the hit grade read tonight's game, or say "he's due"?
*
* Each factor is conditioned against the player's OWN base rate and put through
* the two-part gate: it must MOVE the prediction and the moved prediction must
* be MORE ACCURATE out-of-sample. Movement alone is THEATER — a grade that
* swings on park and platoon looks like it read the matchup, and a user cannot
* tell the difference from outside.
*
* The baseline is deliberately the honest null this order describes: the
* player's base rate, i.e. "he's due" with no reading of tonight at all. A
* factor earns its place only by beating that.
*
* SUPABASE_URL=... node scripts/prove-hit-factors.js
*/
require('dotenv').config();
const { createClient } = require('@supabase/supabase-js');
const fg = require('../src/services/model/factorGate');
const sk = require('../src/services/model/skillProjection');
const tl = require('../src/services/model/testLedger');
const mlb = require('../src/services/adapters/mlbStatsAdapter');
const { knownNumber, knownRate } = require('../src/utils/known');
const { nameKey } = require('../src/utils/playerName');
const sd = require('../src/services/model/sprayDefense');
const pss = require('../src/services/model/platoonSeverity');
const SB_URL = process.env.SUPABASE_URL;
const SB_KEY = process.env.SUPABASE_SERVICE_ROLE_KEY || process.env.SUPABASE_SERVICE_KEY;
const PAGE = 1000;
const ARCHS = (process.env.HF_ARCHETYPES || 'BOMBER,GHOST,ALL').split(',');
async function page(sb, table, select, apply) {
const out = [];
for (let from = 0; ; from += PAGE) {
const { data, error } = await apply(sb.from(table).select(select)).range(from, from + PAGE - 1);
if (error) throw error;
if (!data || data.length === 0) break;
out.push(...data);
if (data.length < PAGE) break;
}
return out;
}
/**
* THE FACTORS. Each returns a MULTIPLIER on the base rate, or null when the
* input is absent — an absent factor must leave the baseline untouched rather
* than nudge it toward some default.
*/
const FACTORS = [
{
key: 'defense_by_direction',
needs: ['spray_multiplier'],
mechanism: 'CAUSALLY-CORRECT DEFENCE. Where the hitter puts the ball (pull/straight/oppo x ground/air) crossed with the OAA of the fielders actually standing in those zones, joined by handedness. Team-average failed the gate because it averages in five fielders who will never touch his ball.',
apply: (r) => r.spray_multiplier,
},
{
key: 'defense',
needs: ['team_defense'],
mechanism: 'A ball in play becomes a hit or an out partly by who is standing behind the pitcher. Should matter most where contact stays in the park.',
// More outs converted above average -> fewer hits.
apply: (r) => 1 - Math.max(-0.12, Math.min(0.12, r.team_defense / 250)),
},
{
key: 'pitcher_contact_profile',
needs: ['pitcher_hard_hit_allowed'],
mechanism: 'A contact-allowing arm concedes better contact than a bat-misser; hit probability should follow the quality of contact he permits.',
apply: (r) => 1 + Math.max(-0.15, Math.min(0.15, (r.pitcher_hard_hit_allowed - 0.389) * 1.2)),
},
{
key: 'park_hits',
needs: ['park_factor'],
mechanism: 'Some parks turn outs into hits without producing runs — big outfields, high walls, deep gaps.',
apply: (r) => r.park_factor,
caveat: 'STAT_BASE maps hits -> run_base, so this is a RUN factor standing in for a HITS factor. A park that converts outs to hits without scoring is invisible to it.',
},
{
key: 'platoon_severity',
needs: ['platoon_severity_mult'],
mechanism: "CAUSALLY-CORRECT PLATOON. The advantage is worth only what THIS hitter's measured split is worth, shrunk toward league by the smaller side's PA and refused outright below a floor. Flat handedness applies the same boost to a 63-point split and to none.",
apply: (r) => r.platoon_severity_mult,
},
{
key: 'platoon',
needs: ['platoon_edge'],
mechanism: 'Handedness advantage — a hitter facing the opposite hand sees the ball better and hits it harder.',
apply: (r) => (r.platoon_edge > 0 ? 1.06 : 0.96),
},
];
async function main() {
if (!SB_URL || !SB_KEY) throw new Error('SUPABASE_URL / service key required');
const sb = createClient(SB_URL, SB_KEY, { auth: { persistSession: false } });
const statcast = await page(sb, 'statcast_aggregates', '*', (q) => q.eq('sport', 'mlb'));
const batters = new Map(); const pitchersById = new Map();
for (const r of statcast) {
const prof = sk.fromStatcastRow(r);
if (r.role === 'pitcher' && r.source_id != null) pitchersById.set(Number(r.source_id), prof);
if (r.role === 'batter' && r.player_key) batters.set(r.player_key, prof);
}
const sprayRows = await page(sb, 'batter_spray', '*', (q) => q.eq('sport', 'mlb'));
const sprayByKey = new Map();
for (const r of sprayRows) {
if (!r.player_key) continue;
const prev = sprayByKey.get(r.player_key);
if (!prev || String(r.as_of_date) > String(prev.as_of_date)) sprayByKey.set(r.player_key, r);
}
const platRows = await page(sb, 'platoon_splits', '*', (q) => q.eq('sport', 'mlb'));
const platByKey = new Map();
for (const r of platRows) {
if (!r.player_key) continue;
const prev = platByKey.get(r.player_key);
if (!prev || String(r.as_of_date) > String(prev.as_of_date)) platByKey.set(r.player_key, r);
}
const defRows = await page(sb, 'team_defense', '*', (q) => q.eq('sport', 'mlb'));
const defByTeam = new Map();
for (const d of defRows) defByTeam.set(d.team, d);
const snaps = await page(sb, 'model_snapshots', 'player_key, game_date, archetype, stat',
(q) => q.eq('sport', 'mlb').eq('stat', 'hits').not('archetype', 'is', null));
const archOf = new Map();
for (const s of snaps) archOf.set(`${s.player_key}|${s.game_date}`, s.archetype);
const led = await page(sb, 'ledger_entries',
'id, player_key, player_name, line, side, outcome, game_date, p_win, quarantine_reason, env_park_base',
(q) => q.eq('sport', 'mlb').is('user_id', null).eq('stat', 'hits')
.in('outcome', ['hit', 'miss']).not('p_win', 'is', null));
const clean = led.filter((r) => !(r.quarantine_reason || '').startsWith('nontakeable_book'));
// Opponent faced, from each hitter's own game log.
const names = new Map();
for (const r of clean) if (!names.has(r.player_key)) names.set(r.player_key, r.player_name);
const oppBy = new Map(); const startersBy = new Map();
const dates = [...new Set(clean.map((r) => r.game_date))].sort();
for (const d of dates) {
try {
const games = await mlb.getScheduleWithPitchers(d);
for (const g of games) {
if (!g.home || !g.away) continue;
if (g.home.probablePitcher) startersBy.set(`${d}|OPP:${g.home.team}`, g.home.probablePitcher.id);
if (g.away.probablePitcher) startersBy.set(`${d}|OPP:${g.away.team}`, g.away.probablePitcher.id);
}
} catch { /* absent slate */ }
}
for (const [key, name] of names) {
try {
const found = await mlb.searchPlayer(name);
if (!found || !found.id) continue;
const log = await mlb.getPlayerGameLog(found.id);
for (const g of log || []) if (g && g.date && g.opponent) oppBy.set(`${key}|${String(g.date).slice(0, 10)}`, g.opponent);
} catch { /* no log */ }
}
// Per-player base rate — the honest null: "he's due", no reading of tonight.
const byPlayer = new Map();
for (const r of clean) {
const cur = byPlayer.get(r.player_key) || { n: 0, w: 0 };
cur.n += 1; cur.w += r.outcome === 'hit' ? 1 : 0;
byPlayer.set(r.player_key, cur);
}
const rows = [];
for (const r of clean) {
const bat = batters.get(r.player_key);
const bp = byPlayer.get(r.player_key);
if (!bp || bp.n < 3) continue;
// Leave-one-out so a row never contributes to its own baseline.
const baseline = (bp.w - (r.outcome === 'hit' ? 1 : 0)) / (bp.n - 1);
const faced = oppBy.get(`${r.player_key}|${r.game_date}`) || null;
const nick = faced ? String(faced).split(' ').pop() : null;
const def = faced ? (defByTeam.get(faced) || defByTeam.get(nick)) : null;
const starterId = faced ? startersBy.get(`${r.game_date}|OPP:${faced}`) : null;
const pit = starterId != null ? pitchersById.get(Number(starterId)) : null;
rows.push({
id: r.id,
archetype: archOf.get(`${r.player_key}|${r.game_date}`) || null,
won: r.outcome === 'hit' ? 1 : 0,
baseline,
team_defense: def ? knownNumber(def.oaa_sum) : null,
pitcher_hard_hit_allowed: pit ? knownRate(pit.hard_hit_pct) : null,
park_factor: knownNumber(r.env_park_base),
platoon_severity_mult: (() => {
const sp = platByKey.get(r.player_key);
if (!sp || !bat || !bat.bats || !pit || !pit.throws) return null;
const out = pss.platoonRead({
splits: {
vl: { pa: sp.vl_pa, atBats: sp.vl_ab, hits: sp.vl_hits },
vr: { pa: sp.vr_pa, atBats: sp.vr_ab, hits: sp.vr_hits },
},
bats: bat.bats, throws: pit.throws,
});
return out && out.readable ? out.multiplier : null;
})(),
spray_multiplier: (() => {
const sp = sprayByKey.get(r.player_key);
const posOaa = def && def.position_oaa ? def.position_oaa : null;
if (!sp || !posOaa || !bat || !bat.bats) return null;
const out = sd.sprayDefenseMultiplier({ spray: sp, bats: bat.bats, positionOaa: posOaa });
return out ? out.multiplier : null;
})(),
platoon_edge: (bat && pit && bat.bats && pit.throws)
? (String(bat.bats)[0] !== String(pit.throws)[0] ? 1 : -1) : null,
});
}
// Cumulative Bonferroni across the programme lifetime.
const store = tl.supabaseStore(sb);
const mc = await tl.recordAndCount(store, FACTORS.flatMap((f) =>
ARCHS.map((a) => ({ sport: 'mlb', stat: 'hits', archetype: a === 'ALL' ? null : a, interaction: `factor:${f.key}`, target: 'outcome' }))));
const results = [];
for (const arch of ARCHS) {
const slot = arch === 'ALL' ? rows : rows.filter((r) => String(r.archetype || '').toUpperCase() === arch);
for (const f of FACTORS) {
const usable = slot.filter((r) => f.needs.every((k) => knownNumber(r[k]) !== null));
const paired = usable.map((r) => {
const mult = f.apply(r);
const cond = mult === null ? null : Math.min(0.99, Math.max(0.01, r.baseline * mult));
return { baseline: r.baseline, conditioned: cond, won: r.won };
});
const v = fg.adjudicate(paired, {
factor: f.key, archetype: arch, stat: 'hits',
cumulativeTests: mc.cumulative_tests, // native cumulative correction
});
results.push({
archetype: arch, factor: f.key, n: v.movement.n,
mean_abs_shift: v.movement.mean_abs_shift,
brier_delta: v.improvement ? v.improvement.brier_delta : null,
ci: v.improvement ? v.improvement.ci : null,
ci_level: v.improvement ? v.improvement.ci_level : null,
verdict: v.verdict,
reason: v.reason,
...(f.caveat ? { input_caveat: f.caveat } : {}),
});
}
}
console.log(JSON.stringify({
baseline: "each row scored against the player's OWN leave-one-out base rate — the honest 'he's due' null",
total_rows: rows.length,
cumulative_bonferroni: mc,
gate: 'a factor must MOVE the prediction AND improve out-of-sample Brier; movement alone is THEATER',
results,
proven: results.filter((r) => r.verdict === 'PROVES'),
theater: results.filter((r) => r.verdict === 'THEATER'),
}, null, 2));
process.exit(0);
}
main().catch((e) => { console.error(e); process.exit(1); });