Session 46: Grade card intel + name normalization + pitchers (2122 tests)
Three focused P1 fixes on the Session-45 snapshot model.
- Grade card intel ROOT CAUSE: gameLogService is NBA/WNBA-only (offline Python),
so MLB props never got l5_avg/l20_avg and buildIntelFields returned {}. Wired
MLB game logs into featureCache.gameLogFeatures via mlbStatsAdapter.getPlayerStats
(pure mlbGameLogFeatures + MLB stat_type->field map). buildIntelFields gained
playerStats/projection fallbacks for partial intel.
- Player name normalization: src/utils/playerName.js (+ web/src/lib copy):
normalizeName -> {display,key}. Strips periods, de-dots suffix, accent-folds
the key. Applied in snapshotService grouping, slateAdapter grade index +
player-strip merge (variants collapse, longest name shown), and
playerIntelService. "A.J. Ewing"/"AJ Ewing" + "Jazz Chisholm"/"Jr." now merge.
- MLB starting pitchers: new GET /api/schedule/:sport/pitchers (probablePitchers
service wrapping mlbStatsAdapter.getScheduleWithPitchers + best-effort ERA).
Slate fetches it, builds a team->pitcher map (full name + mascot match),
attaches pitchers to MLB GameCardData. + Next proxy.
Backend 2100 -> 2122 tests (+22), 176 suites. Web build clean (exit 0).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
This commit is contained in:
@@ -296,18 +296,31 @@ function matchupGradeFromRank(rank) {
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* yield the fallback. The archetype strip lights up once the snapshot pipeline
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* (Session 44) feeds per-player season lines into the grade response.
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*/
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function buildIntelFields(features = {}) {
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const firstFinite = (...vals) => vals.find((v) => Number.isFinite(v));
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function buildIntelFields(features = {}, opts = {}) {
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const out = {};
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const round1 = (n) => Math.round(n * 10) / 10;
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if (Number.isFinite(features.l20_avg)) out.season_avg = round1(features.l20_avg);
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else if (Number.isFinite(features.season_avg)) out.season_avg = round1(features.season_avg);
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if (Number.isFinite(features.l10_avg)) out.last10_avg = round1(features.l10_avg);
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else if (Number.isFinite(features.l5_avg)) out.last10_avg = round1(features.l5_avg);
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// Resilience (Session 46): fall back to a caller-supplied playerStats bundle
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// and the model projection when the feature vector is sparse. Partial intel
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// beats none — we add only the fields we can actually back with a number.
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const ps = opts.playerStats || {};
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const proj = Number.isFinite(opts.projection) ? opts.projection : undefined;
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const form = computeFormScore(features);
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const seasonAvg = firstFinite(features.l20_avg, features.season_avg, ps.season_avg, proj);
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if (seasonAvg != null) out.season_avg = round1(seasonAvg);
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const last10 = firstFinite(features.l10_avg, features.l5_avg, ps.last10_avg);
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if (last10 != null) out.last10_avg = round1(last10);
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let form = computeFormScore(features);
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if (form == null && Number.isFinite(ps.form)) form = Math.round(ps.form);
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if (form != null) out.form = form;
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if (Number.isFinite(features.usage_rate)) out.usage = `${round1(features.usage_rate)}%`;
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else if (Number.isFinite(features.minutes_per_game)) out.usage = `${Math.round(features.minutes_per_game)} min`;
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else if (ps.usage) out.usage = String(ps.usage);
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const matchup = matchupGradeFromRank(features.opp_rank_stat);
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if (matchup) out.matchup_grade = matchup;
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if (Number.isFinite(features.rest_days)) out.rest = `${features.rest_days}d rest`;
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@@ -76,7 +76,66 @@ function daysBetween(aIso, bIso) {
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return Math.floor(ms / (1000 * 60 * 60 * 24));
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}
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// MLB stat_type → the per-game field name in a statsapi.mlb.com game-log row.
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const MLB_LOG_FIELD = {
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total_bases: 'totalBases', home_runs: 'homeRuns', hits: 'hits', rbi: 'rbi',
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runs: 'runs', stolen_bases: 'stolenBases', walks: 'baseOnBalls',
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strikeouts: 'strikeOuts', earned_runs: 'earnedRuns', hits_allowed: 'hits',
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innings_pitched: 'inningsPitched',
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};
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function mlbStatValue(statObj, statType) {
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const f = MLB_LOG_FIELD[statType];
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if (!f || !statObj) return null;
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const n = parseFloat(statObj[f]);
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return Number.isFinite(n) ? n : null;
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}
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/**
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* Session 46 — derive recent/season averages from a real MLB game log
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* (mlbStatsAdapter.getPlayerStats result). PURE so it's unit-testable without
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* the network. Produces l5_avg / l10_avg (recent form) + l20_avg (the season
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* per-game reference) — exactly the fields buildIntelFields consumes, which the
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* NBA/WNBA-only Python game-log path never populated for MLB.
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*/
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function mlbGameLogFeatures(res, statType) {
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if (!res || !res.found) return {};
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const out = {};
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const logs = Array.isArray(res.last10) ? res.last10 : [];
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const vals = logs.map((g) => mlbStatValue(g.stat, statType)).filter((v) => v != null);
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if (vals.length) {
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const m5 = avg(vals.slice(-5)); // game logs are chronological (recent last)
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const m10 = avg(vals.slice(-10));
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const s10 = stddev(vals.slice(-10));
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if (m5 != null) out.l5_avg = m5;
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if (m10 != null) out.l10_avg = m10;
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if (s10 != null) out.l10_stddev = s10;
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}
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const seasonTotal = mlbStatValue(res.season, statType);
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const games = parseFloat(res.season && (res.season.gamesPlayed ?? res.season.gamesStarted ?? res.season.gamesPitched));
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if (seasonTotal != null && Number.isFinite(games) && games > 0) {
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out.l20_avg = seasonTotal / games;
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} else if (out.l10_avg != null) {
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out.l20_avg = out.l10_avg; // baseline so form has a reference
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}
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return out;
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}
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async function gameLogFeatures(playerName, sport, statType) {
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// MLB game logs come from the FREE statsapi.mlb.com (Session 46) — the Python
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// gameLogService only covers NBA/WNBA, so MLB props had no recent/season
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// averages and the grade card's intel sections stayed empty.
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if (sport === 'mlb') {
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try {
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const mlbStats = require('../adapters/mlbStatsAdapter');
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const res = await mlbStats.getPlayerStats(playerName);
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return mlbGameLogFeatures(res, statType);
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} catch (e) {
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console.warn('[featureCache] MLB game-log features failed:', e.message);
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return {};
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}
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}
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const logs = await gameLogs.getGameLogs(playerName, sport, 20);
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if (!logs || logs.length === 0) return {};
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@@ -261,6 +320,8 @@ module.exports = {
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coachFeatures,
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lineupFeatures,
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statFromGameLog,
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mlbGameLogFeatures,
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mlbStatValue,
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avg,
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stddev,
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daysBetween,
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