Prove both on total bases -- and find that my own fix destroyed the backtest

Nothing passed. Nothing promoted. Counter byte-identical. THE BLOCKER, which is the real finding. statcast_aggregates is upserted in place and holds exactly one as-of date. Yesterday's skill backtest was honest only by accident: the nightly refresh was unreachable code, so the profiles sat frozen at 2026-07-21 -- before the settled window. Repairing that cron was right for production and it refreshed them to today, destroying every prior version. Scoring a 2026-07-25 game now uses a season aggregate that contains that game. Point-in-time validation is structurally impossible from that table, so every number in this run is contaminated and directional, and none of it is a gate verdict. Fixed forward: statcast_history retains a dated snapshot on every refresh, so point-in-time becomes "as_of_date < game_date, most recent". Retention is best-effort and cannot fail the refresh; both properties are unit-tested. It has one day of data, which is not yet a window. SOLO BASELINE, n=383, Bonferroni across 12 tests (alpha 0.00417): nothing passes. hard_hit_pct is closest at marginal r 0.135 with p 0.0080, failing both the 0.15 effect bar and the corrected alpha. And it drifted DOWN from 0.153 at n=295 -- an estimate regressing as noise averages out, not an effect firming up. I called that number encouraging yesterday; on 88 more rows it is fading, and it should not keep being quoted at its best value. INTERACTIONS, each scored by partial correlation against the counter residual controlling for both of its own components: none pass. Only barrel x power archetype has an incremental exceeding its parts (-0.101 against 0.019) at n=260 -- the shape Discipline 2 predicts, but a lead, not a finding. A methodological catch worth keeping. The archetype conditioner was first built as barrel_pct over league barrel -- a monotone transform of one of its own components -- so the "interaction" was barrel squared, measuring nonlinearity in barrel rate rather than any archetype effect, and it produced this run's only positive result. A Gauss-Jordan pivot test does not catch that, because the two columns differ by a scale factor. Fixed with a scale-free collinearity check plus real archetype labels joined from model_snapshots. Without it this document would have reported a fabricated interaction as the session's finding. COMBINED vs COUNTER on total bases: 0.2718 against 0.2647, delta +0.0071, CI [-0.065, +0.079] -- inconclusive, and the first time a challenger has not lost. The same engine on hits was -0.116 with a CI excluding zero. That contrast is the whole argument for total bases, and it is what the physics said: contact quality governs extra bases, not whether a grounder finds a hole. Also built: the compound TB projection. skillProjection no longer refuses total bases -- a deterministic bases-per-hit multiplier had made P(TB>=2) exactly P(hits>=1), a relabelled hits curve. It is now a convolution over per-PA base outcomes with hit-type shares shifted by skill. Non-degeneracy is locked by test. 4,204 tests green (334 suites); web build exit 0. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01W1sivYNqY2TS5ftykmHBU9
2026-08-03 16:27:11 -04:00
parent c7cc8f5e52
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+#!/usr/bin/env node
+'use strict';
+
+/**
+ * tb-solo-and-interactions — PROVE BOTH, with the solo pass as the control.
+ *
+ * A feature can carry signal alone, only in combination, or both. Testing only
+ * interactions misses solo-real features AND cannot tell whether an interaction
+ * ADDS anything or merely re-encodes its own parts. So the solo result is the
+ * baseline every interaction has to beat.
+ *
+ * ── HOW "ADDS OVER ITS PARTS" IS MEASURED ────────────────────────────────
+ * Not by comparing two correlations by eye. The interaction's incremental
+ * signal is the PARTIAL correlation of the interaction term with the counter's
+ * residual, CONTROLLING FOR both component features:
+ *
+ *     resid_I = I  − OLS(I  ~ A, B)
+ *     resid_Y = Y  − OLS(Y  ~ A, B)
+ *     incremental r = corr(resid_I, resid_Y)
+ *
+ * If the interaction is just barrel-rate wearing a different hat, regressing out
+ * barrel rate removes it and the incremental r collapses to ~0. That is exactly
+ * the redundancy the order is guarding against, and it is the difference between
+ * PASSES-AND-ADDS and PASSES-BUT-REDUNDANT.
+ *
+ * ── WHY THE COUNTER'S RESIDUAL IS THE TARGET ─────────────────────────────
+ * Correlating with the raw outcome rewards a feature for knowing what the
+ * counter already knows. Only the part the counter MISSES is new information,
+ * and only new information can improve the product. Both are reported; the
+ * residual one is the one that decides.
+ *
+ * ── THEORY FIRST ─────────────────────────────────────────────────────────
+ * Every interaction below is declared with a MECHANISM before it is measured.
+ * No blind pairwise search — with 8 features there are 28 pairs, and at α=.05
+ * roughly one in twenty returns "significant" from noise alone.
+ *
+ *   SUPABASE_URL=... node scripts/tb-solo-and-interactions.js
+ */
+
+require('dotenv').config();
+const { createClient } = require('@supabase/supabase-js');
+const cv = require('../src/services/model/correlateValidator');
+const sk = require('../src/services/model/skillProjection');
+const reg = require('../src/services/model/featureRegistry');
+const mlb = require('../src/services/adapters/mlbStatsAdapter');
+const { knownRate, knownNumber } = require('../src/utils/known');
+
+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 GAMES_SO_FAR = Number(process.env.STAGEA_GAMES_SO_FAR || 103);
+
+const r4 = (v) => (v == null || !Number.isFinite(v) ? null : Math.round(v * 10000) / 10000);
+const mean = (a) => (a.length ? a.reduce((x, y) => x + y, 0) / a.length : null);
+const brier = (ps, ys) => (ps.length ? ps.reduce((s, p, i) => s + (p - ys[i]) ** 2, 0) / ps.length : null);
+
+/** OLS residuals of y on the given predictor columns (with intercept). */
+function olsResiduals(y, Xcols) {
+  const n = y.length;
+  const p = Xcols.length + 1;
+  const X = [];
+  for (let i = 0; i < n; i += 1) {
+    const row = [1];
+    for (const c of Xcols) row.push(c[i]);
+    X.push(row);
+  }
+  // Normal equations (X'X) b = X'y, solved by Gauss-Jordan. p is 2-4 here.
+  const XtX = Array.from({ length: p }, () => new Array(p).fill(0));
+  const Xty = new Array(p).fill(0);
+  for (let i = 0; i < n; i += 1) {
+    for (let a = 0; a < p; a += 1) {
+      Xty[a] += X[i][a] * y[i];
+      for (let b = 0; b < p; b += 1) XtX[a][b] += X[i][a] * X[i][b];
+    }
+  }
+  const M = XtX.map((row, i) => [...row, Xty[i]]);
+  for (let col = 0; col < p; col += 1) {
+    let piv = col;
+    for (let r = col + 1; r < p; r += 1) if (Math.abs(M[r][col]) > Math.abs(M[piv][col])) piv = r;
+    if (Math.abs(M[piv][col]) < 1e-12) return null;   // singular → cannot control honestly
+    [M[col], M[piv]] = [M[piv], M[col]];
+    const d = M[col][col];
+    for (let k = col; k <= p; k += 1) M[col][k] /= d;
+    for (let r = 0; r < p; r += 1) {
+      if (r === col) continue;
+      const f = M[r][col];
+      for (let k = col; k <= p; k += 1) M[r][k] -= f * M[col][k];
+    }
+  }
+  const beta = M.map((row) => row[p]);
+  return y.map((v, i) => v - X[i].reduce((s, xv, j) => s + xv * beta[j], 0));
+}
+
+/**
+ * Partial correlation of a with b, controlling for the columns in ctrl.
+ *
+ * COLLINEARITY IS CHECKED FIRST, and this is not pedantry — it caught a real
+ * error in this very script. The archetype-power proxy was defined as
+ * `barrel_pct / LEAGUE.barrel_pct`, an exact linear function of barrel_pct, so
+ * "control for both components" was rank-deficient and the partial correlation
+ * it produced (-0.132, the only one that looked like an incremental finding) was
+ * an artifact of a singular design matrix. The Gauss-Jordan pivot test missed it
+ * because the two columns differ by a scale factor, which keeps the pivot well
+ * above an absolute epsilon. Scale-free pairwise correlation catches it.
+ */
+function partialCorr(a, b, ctrl) {
+  for (let i = 0; i < ctrl.length; i += 1) {
+    for (let j = i + 1; j < ctrl.length; j += 1) {
+      const rr = cv.pearson(ctrl[i], ctrl[j]).r;
+      if (rr !== null && Math.abs(rr) > 0.999) return null; // same variable twice
+    }
+  }
+  const ra = olsResiduals(a, ctrl);
+  const rb = olsResiduals(b, ctrl);
+  if (!ra || !rb) return null;
+  return cv.pearson(ra, rb).r;
+}
+
+/** Rows where every named key is known — the honest common sample. */
+function completeRows(rows, keys) {
+  return rows.filter((r) => keys.every((k) => knownNumber(r[k]) !== null));
+}
+
+function makeRnd(seed) {
+  let s = seed >>> 0;
+  return () => { s ^= s << 13; s >>>= 0; s ^= s >>> 17; s ^= s << 5; s >>>= 0; return s / 4294967296; };
+}
+function bootstrapDiff(rows, keyA, keyB, iters = 4000, seed = 20260804) {
+  if (rows.length < 30) return null;
+  const rnd = makeRnd(seed);
+  const n = rows.length;
+  const diffs = [];
+  for (let it = 0; it < iters; it += 1) {
+    const ys = []; const a = []; const b = [];
+    for (let i = 0; i < n; i += 1) {
+      const r = rows[Math.floor(rnd() * n)];
+      ys.push(r.won); a.push(r[keyA]); b.push(r[keyB]);
+    }
+    const ca = cv.pearson(a, ys).r; const cb = cv.pearson(b, ys).r;
+    if (ca == null || cb == null) continue;
+    diffs.push(ca - cb);
+  }
+  if (diffs.length < 100) return null;
+  diffs.sort((x, y) => x - y);
+  const q = (pp) => r4(diffs[Math.floor(pp * (diffs.length - 1))]);
+  const ci = [q(0.025), q(0.975)];
+  return {
+    point: r4(cv.pearson(rows.map((r) => r[keyA]), rows.map((r) => r.won)).r
+      - cv.pearson(rows.map((r) => r[keyB]), rows.map((r) => r.won)).r),
+    ci95: ci, ci_excludes_zero: ci[0] > 0 || ci[1] < 0,
+  };
+}
+
+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;
+}
+
+async function opposingStarters(dates) {
+  const m = new Map();
+  for (const d of dates) {
+    let games = [];
+    try { games = await mlb.getScheduleWithPitchers(d); } catch { games = []; }
+    for (const g of games) {
+      if (!g.home || !g.away) continue;
+      if (g.home.probablePitcher) m.set(`${d}|OPP:${g.home.team}`, g.home.probablePitcher.id);
+      if (g.away.probablePitcher) m.set(`${d}|OPP:${g.away.team}`, g.away.probablePitcher.id);
+    }
+  }
+  return m;
+}
+async function opponentByPlayerDate(players) {
+  const map = new Map();
+  for (const [key, name] of players) {
+    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) map.set(`${key}|${String(g.date).slice(0, 10)}`, g.opponent);
+      }
+    } catch { /* no log → no pitcher */ }
+  }
+  return map;
+}
+
+const SOLO = ['batter_barrel_pct', 'batter_hard_hit_pct', 'batter_exit_velo',
+  'batter_launch_angle', 'batter_k_pct', 'batter_bb_pct',
+  'pitcher_k_pct', 'pitcher_hard_hit_allowed'];
+
+/** STEP 2 — theory first. Every interaction declares its mechanism. */
+const INTERACTIONS = [
+  {
+    key: 'launch_x_exit_velo',
+    components: ['batter_launch_angle', 'batter_exit_velo'],
+    mechanism: 'Extra bases need BOTH conditions: hit hard AND hit in the air. A 105-mph ground ball is an out; a 25-degree popup is an out. Neither factor alone predicts bases, which is precisely why each may fail solo and the product may not.',
+    build: (r) => r.batter_launch_angle * r.batter_exit_velo,
+  },
+  {
+    key: 'exitvelo_x_pitcher_suppression',
+    components: ['batter_exit_velo', 'pitcher_hard_hit_allowed'],
+    mechanism: 'A hitter only realises his contact quality against a pitcher who permits contact quality. Elite suppression should attenuate a power bat; a contact-permitting arm should amplify it. The effect is conditional by construction.',
+    build: (r) => r.batter_exit_velo * r.pitcher_hard_hit_allowed,
+  },
+  {
+    key: 'barrel_x_power_archetype',
+    components: ['batter_barrel_pct', 'archetype_power'],
+    mechanism: 'ARCHETYPE-CONDITIONAL. Barrels convert to extra bases for hitters whose lane is power; for a speed/contact profile the same barrel rate is a rarer event on a swing built for something else. This is Discipline 2 stated as a testable interaction. NOTE: it is currently UNTESTABLE — statcast rows carry no archetype label, and the barrel-relative proxy is an exact linear function of barrel_pct, so controlling for both components is rank-deficient. It needs a real archetype classification joined in.',
+    build: (r) => r.batter_barrel_pct * r.archetype_power,
+  },
+  {
+    key: 'batterK_x_pitcherK',
+    components: ['batter_k_pct', 'pitcher_k_pct'],
+    mechanism: 'Strikeout risk compounds multiplicatively (log5 is exactly this shape). A high-K bat against a high-K arm loses plate appearances to strikeouts, and a PA lost is a base opportunity that never happens — so it suppresses total bases through OPPORTUNITY, not contact quality.',
+    build: (r) => r.batter_k_pct * r.pitcher_k_pct,
+  },
+];
+
+/** Latest settled game date in the pull — used to detect that the profile
+ *  freeze now sits AFTER the data, i.e. no clean out-of-sample window exists. */
+function clean0Max(rows) {
+  return (rows || []).reduce((mx, r) => (String(r.game_date) > mx ? String(r.game_date) : mx), '');
+}
+
+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 freezeDate = statcast.reduce((mx, r) => (String(r.updated_at) > mx ? String(r.updated_at) : mx), '').slice(0, 10);
+  const batters = new Map(); const pitchersById = new Map();
+  for (const r of statcast) {
+    if (r.role === 'pitcher' && r.source_id != null) pitchersById.set(Number(r.source_id), sk.fromStatcastRow(r));
+    if (r.player_key && r.role === 'batter') {
+      const prev = batters.get(r.player_key);
+      if (!prev || Number(r.sample_pa || 0) > Number(prev.rawPa || 0)) {
+        batters.set(r.player_key, Object.assign(sk.fromStatcastRow(r), { rawPa: Number(r.sample_pa || 0) }));
+      }
+    }
+  }
+
+  // REAL ARCHETYPE LABELS. The barrel-relative proxy was a clipped monotone
+  // transform of barrel_pct, so `barrel x proxy` measured NONLINEARITY IN BARREL,
+  // not an archetype interaction — it could never have tested Discipline 2.
+  // model_snapshots carries the actual classification per prop, so the
+  // conditioning variable is now a genuine BOMBER indicator, which is
+  // categorical and therefore not a transform of barrel at all.
+  const snaps = await page(sb, 'model_snapshots', 'player_key, game_date, archetype',
+    (q) => q.eq('sport', 'mlb').eq('stat', 'total_bases').not('archetype', 'is', null));
+  const archetypeBy = new Map();
+  for (const r of snaps) if (r.player_key && r.game_date) archetypeBy.set(`${r.player_key}|${r.game_date}`, r.archetype);
+
+  const led = await page(sb, 'ledger_entries',
+    'player_key, player_name, stat, line, side, outcome, game_date, p_win, quarantine_reason',
+    (q) => q.eq('sport', 'mlb').is('user_id', null).eq('stat', 'total_bases')
+      .in('outcome', ['hit', 'miss']).not('p_win', 'is', null));
+  // POINT-IN-TIME IS NO LONGER AVAILABLE FROM THIS TABLE.
+  //
+  // `statcast_aggregates` is upserted in place and keeps one as-of date. The
+  // first skill backtest was honest only by accident: the nightly refresh was
+  // unreachable code, so the table sat frozen at 2026-07-21 — BEFORE the settled
+  // window. Repairing that cron (correct for production) refreshed it to today,
+  // and every prior version is gone.
+  //
+  // So scoring a 2026-07-25 game now uses a season aggregate that CONTAINS that
+  // game. `statcast_history` (added this session) fixes it going forward; it has
+  // one day of data, which is not yet a window. Until it fills, results here are
+  // DIRECTIONAL AND CONTAMINATED, labelled as such, and are NOT gate verdicts.
+  const contaminated = String(freezeDate) >= String(clean0Max(led));
+  const clean = led.filter((r) => !(r.quarantine_reason || '').startsWith('nontakeable_book')
+    && (contaminated ? true : String(r.game_date) > freezeDate));
+
+  const dates = [...new Set(clean.map((r) => r.game_date))].sort();
+  const starters = await opposingStarters(dates);
+  const players = new Map();
+  for (const r of clean) if (!players.has(r.player_key)) players.set(r.player_key, r.player_name);
+  const oppByPlayerDate = await opponentByPlayerDate(players);
+
+  if (process.env.TB_DEBUG === '1') {
+    console.error(`[debug] statcast rows=${statcast.length} freeze=${freezeDate} batters=${batters.size} pitchers=${pitchersById.size}`);
+    console.error(`[debug] ledger tb rows=${led.length} clean(after freeze)=${clean.length}`);
+    const sampleKeys = clean.slice(0, 5).map((r) => r.player_key);
+    console.error(`[debug] sample ledger player_keys=${JSON.stringify(sampleKeys)}`);
+    console.error(`[debug] sample statcast keys=${JSON.stringify([...batters.keys()].slice(0, 5))}`);
+    console.error(`[debug] matches in sample=${sampleKeys.filter((k) => batters.has(k)).length}/5`);
+  }
+  const allowed = reg.candidateFeaturesForStat('mlb', 'total_bases');
+  const rows = [];
+  for (const r of clean) {
+    const bat = batters.get(r.player_key);
+    if (!bat) continue;
+    const faced = oppByPlayerDate.get(`${r.player_key}|${r.game_date}`) || null;
+    const pit = faced ? pitchersById.get(Number(starters.get(`${r.game_date}|OPP:${faced}`))) || null : null;
+    const paRate = bat.rawPa > 0 ? Math.min(5.2, Math.max(2.0, bat.rawPa / GAMES_SO_FAR)) : null;
+    const under = String(r.side).toLowerCase() === 'under';
+    const won = r.outcome === 'hit' ? 1 : 0;
+    const champ = Number(r.p_win);
+
+    const proj = sk.projectSkill({
+      batter: bat, pitcher: pit, park: 1, archetype: null,
+      statType: 'total_bases', line: Number(r.line), expectedPa: paRate, allowed,
+    });
+
+    // The REAL archetype for this prop — a 0/1 power indicator, categorical and
+    // independent of barrel_pct by construction.
+    const arch = archetypeBy.get(`${r.player_key}|${r.game_date}`) || null;
+    const archetypePower = arch == null ? null : (String(arch).toUpperCase() === 'BOMBER' ? 1 : 0);
+
+    rows.push({
+      won, champ, residual: won - champ,
+      skill: proj ? (under ? 1 - proj.p_over_line : proj.p_over_line) : null,
+      had_pitcher: !!pit,
+      batter_barrel_pct: knownRate(bat.barrel_pct),
+      batter_hard_hit_pct: knownRate(bat.hard_hit_pct),
+      batter_exit_velo: knownRate(bat.avg_exit_velo),
+      batter_launch_angle: knownRate(bat.avg_launch_angle),
+      batter_k_pct: knownRate(bat.k_pct),
+      batter_bb_pct: knownRate(bat.bb_pct),
+      pitcher_k_pct: pit ? knownRate(pit.k_pct) : null,
+      pitcher_hard_hit_allowed: pit ? knownRate(pit.hard_hit_pct) : null,
+      archetype_power: archetypePower,
+      archetype: arch,
+    });
+  }
+
+  // Bonferroni denominator = every test in this family (solo + interaction).
+  const TESTS = SOLO.length + INTERACTIONS.length;
+
+  // ── STEP 1 — SOLO PASS (the control) ────────────────────────────────────
+  const solo = {};
+  for (const f of SOLO) {
+    const rs = completeRows(rows, [f]);
+    solo[f] = {
+      n: rs.length,
+      vs_outcome: cv.validateFactor(rs.map((r) => r[f]), rs.map((r) => r.won), TESTS),
+      vs_counter_residual: cv.validateFactor(rs.map((r) => r[f]), rs.map((r) => r.residual), TESTS),
+    };
+  }
+
+  // ── STEP 3 — INTERACTIONS, each against its own solo baseline ───────────
+  const interactions = {};
+  for (const ix of INTERACTIONS) {
+    const keys = [...ix.components];
+    const rs = completeRows(rows, keys);
+    if (rs.length < 30) { interactions[ix.key] = { mechanism: ix.mechanism, n: rs.length, verdict: 'UNTESTABLE — no common sample' }; continue; }
+    const I = rs.map(ix.build);
+    const Y = rs.map((r) => r.residual);
+    const ctrl = keys.map((k) => rs.map((r) => r[k]));
+
+    const gate = cv.validateFactor(I, Y, TESTS);
+    const incremental = partialCorr(I, Y, ctrl);
+    // The best solo |r| among its own components, on the SAME rows.
+    const componentSolo = keys.map((k) => ({
+      feature: k, r: r4(cv.pearson(rs.map((r) => r[k]), Y).r),
+    }));
+    const bestComponent = Math.max(...componentSolo.map((c) => Math.abs(c.r ?? 0)));
+
+    let verdict;
+    if (incremental === null) verdict = 'UNTESTABLE — controls are collinear';
+    else if (gate.validated && Math.abs(incremental) >= cv.VALIDATION_REQUIREMENTS.min_pearson_r) verdict = 'PASSES-AND-ADDS';
+    else if (gate.validated) verdict = 'PASSES-BUT-REDUNDANT';
+    else if (rs.length < cv.VALIDATION_REQUIREMENTS.min_historical_instances) verdict = 'UNDERPOWERED — n below the gate';
+    else verdict = 'FAILS';
+
+    interactions[ix.key] = {
+      mechanism: ix.mechanism,
+      components: keys,
+      n: rs.length,
+      raw_r_vs_residual: gate.pearson_r,
+      gate: { validated: gate.validated, reason: gate.reason, p_value: gate.p_value, corrected_alpha: gate.corrected_alpha, underpowered: !!gate.underpowered },
+      component_solo_r_same_rows: componentSolo,
+      best_component_abs_r: r4(bestComponent),
+      INCREMENTAL_partial_r: r4(incremental),
+      adds_over_components: incremental !== null && Math.abs(incremental) > bestComponent,
+      verdict,
+    };
+  }
+
+  // ── STEP 4 — COMBINED vs COUNTER (valid at this n; the gate is not) ─────
+  const h2h = rows.filter((r) => r.skill != null);
+  const ys = h2h.map((r) => r.won);
+  const bs = bootstrapDiff(h2h, 'skill', 'champ');
+
+  console.log(JSON.stringify({
+    stat: 'total_bases',
+    VALIDITY: contaminated
+      ? 'CONTAMINATED / DIRECTIONAL ONLY — statcast_aggregates now carries a single as-of date (' + freezeDate + ') that is AFTER the settled games, so season profiles contain the games being predicted. These are NOT gate verdicts. statcast_history (new) makes point-in-time possible from tomorrow.'
+      : `CLEAN out-of-sample: profiles frozen ${freezeDate}; only game_date > ${freezeDate} scored`,
+    contaminated,
+    rows_scored: rows.length,
+    gate_spec: cv.VALIDATION_REQUIREMENTS,
+    bonferroni_tests: TESTS,
+    n_gap_note: `the gate needs ${cv.VALIDATION_REQUIREMENTS.min_historical_instances} rows; this run has ${rows.length}`,
+    archetype_coverage: {
+      labelled: rows.filter((r) => r.archetype).length,
+      bomber: rows.filter((r) => r.archetype_power === 1).length,
+      other: rows.filter((r) => r.archetype_power === 0).length,
+    },
+    step1_solo_baseline: solo,
+    step3_interactions: interactions,
+    step4_combined_vs_counter: {
+      n: h2h.length,
+      pitcher_coverage: r4(mean(h2h.map((r) => (r.had_pitcher ? 1 : 0)))),
+      base_rate: r4(mean(ys)),
+      resolution: { skill_tb: r4(cv.pearson(h2h.map((r) => r.skill), ys).r), counter: r4(cv.pearson(h2h.map((r) => r.champ), ys).r) },
+      brier: { skill_tb: r4(brier(h2h.map((r) => r.skill), ys)), counter: r4(brier(h2h.map((r) => r.champ), ys)) },
+      delta: bs,
+      verdict: !bs ? 'N-BLOCKED'
+        : (bs.ci_excludes_zero && bs.point > 0) ? 'SKILL TB BEATS THE COUNTER'
+          : (bs.ci_excludes_zero && bs.point < 0) ? 'LOSES to the counter'
+            : 'INCONCLUSIVE',
+    },
+  }, null, 2));
+  process.exit(0);
+}
+
+main().catch((e) => { console.error(e); process.exit(1); });