Revive the dead probability layer + restore grade range ON MERIT

Folds re-sequenced steps 1+2 into one change (Kev's call): same bug
family — features wired to sources that return null.

THE PROBABILITY LAYER WAS DEAD IN PRODUCTION. p_win/ev_pct/kelly/
model_odds/value were absent on 0/8 live grades because
gameLogService.getGameLogs returns null for MLB by construction and
depends on the offline Python service for NBA/WNBA, so meta.gameLogs was
[] for every sport. This was the S46 bug in a second location — that fix
gave featureCache an MLB branch (why grades still worked) but never the
estimator. featureCache.getStatRows now supplies normalized rows
([{date,[statType]:v}], most-recent-first) for every sport, feeding the
estimator AND consistency AND game_count_in_7d from one fetch.
VERIFIED on real props: p_win 25/25 WNBA, 8/8 MLB (was 0).

GRADE RANGE, ON MERIT — never by rescaling (permanent founder ruling:
minting A's without new information is a relabelled B sold as an A and
corrupts an append-only ledger).
- refreshTeamStats wired into runSnapshot — it had ZERO production
  callers, so opp_rank_stat was permanently null and a +/-1.0 factor
  could never fire. Test-env no-op (opsNotify precedent).
- L20 made SYMMETRIC: both branches were delta +1.0, so the season
  baseline could only ever ADD. No negative path was a structural reason
  D was unreachable. New l20_contradicts_* carries -1.0.
- game_count_in_7d derived from real logged dates (heavy_workload_7d).
- NOT wired, deliberately, with reasons inline: teamId (no team_id
  column; getFeatures reads it top-level; factor also needs a starter-id
  list) and season_type (ESPN 2 = REGULAR season; threading it raw would
  fire veteran_in_playoffs in July). Dead code dressed as a fix is the
  thing we are removing, not adding.

CALIBRATION GUARD (found by verifying, not assuming): consistency CV is
NBA-tuned; for a Poisson-ish stat cv ~ 1/sqrt(mean), so any stat with
mean < 4 auto-classifies boom_bust. First verification run showed 8/8 MLB
props boom_bust — a blanket -1.0 that dropped the board to all-C. Floored
at CONSISTENCY_MIN_MEAN=4 -> 'unknown' below. Absent beats wrong. MLB
low-count stats therefore still get no consistency factor: honest, not
fixed. Scale-free index-of-dispersion classifier is the open follow-up.

CONFIDENCE IS NOT A PROBABILITY: payloads carry confidence_basis:
'grade_band'. Corrected mlb-grade-degradation.md — its "25/25
grade<->confidence agreement" is a TAUTOLOGY (confidence is derived FROM
the letter, so it would report 25/25 even if every grade were wrong), not
a validation. Removed dead mlbGrader.js (referenced only by its own test)
and the stale computeFeatures comment claiming a penalty that never ran.

VERIFICATION (scripts/verify-grade-range.js, real props/logs/engine):
WNBA 25 props B 68%->32%, C 32%->64%, D 0->1 (4%); 11-step spread went
from 2 steps to 5 (C/C+/B-/D). The D is earned: Angel Reese assists o2.5,
p_win 0.365. Nothing flooded — grades got HARDER. A did not emit locally
because opp_rank_stat needs the Redis cache only prod populates (local
ceiling +3.0 vs the +4.5 A needs); reachability is proven arithmetically
and locked in tests. Prod A-emission is the outstanding fingerprint.

MARKETING HOLD: "A-RATED" (AccuracyBadge, TopSignals) is unsupported
until that fingerprint. Confirmed honest fallbacks render today —
/api/ledger/accuracy has B and C buckets only, so the badge shows
"MODEL · 63% HIT" and TopSignals self-hides. Nothing fabricated ships.

Suite 276/3286 green, web build exit 0.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01SmNjJAwEnqHPtXbvSZR8kA

src/services/snapshotService.js

@@ -228,6 +228,13 @@ async function runSnapshot(sport, opts = {}) {
     // pipeline already calls (schedule + summary). Fills the NBA/WNBA espnId gap
     // when the stats-resolve fallback misses. Returns {} for MLB / errors.
     buildEspnIndex: opts.buildEspnIndex || require('./espnAthleteIndex').buildEspnAthleteIndex,
+    // Session 63 — the opponent-rank feed. Injectable so tests never hit ESPN;
+    // under NODE_ENV=test it defaults to a no-op (the opsNotify precedent) so a
+    // suite that doesn't know about this dep can never make a live ESPN call.
+    refreshTeamStats: opts.refreshTeamStats
+      || (process.env.NODE_ENV === 'test'
+        ? async () => null
+        : require('./intelligence/teamStatsCache').refreshTeamStats),
   };
   const start = deps.nowMs();
   const ts = deps.now();
@@ -255,6 +262,22 @@ async function runSnapshot(sport, opts = {}) {
     return { sport: sp, status: 'skipped', reason: 'no props', gradeCount: 0 };
   }
 
+  // Session 63 — REFRESH TEAM STATS BEFORE GRADING.
+  // `refreshTeamStats` is the ONLY writer of `team_stats:{sport}:{abbr}`, which
+  // is the ONLY source of `opp_rank_stat` — and it had zero production callers,
+  // so that feature was permanently null and engine1's ±1.0 opponent-defense
+  // factor could never fire. It is 24h-cached and rate-limited, so this is one
+  // cheap ESPN pass per snapshot. Best-effort: a failure here must never break
+  // the snapshot — the features simply stay absent, as before.
+  try {
+    const summary = await deps.refreshTeamStats(sp);
+    if (summary && summary.captured != null) {
+      console.log(`[snapshot] team stats refreshed for ${sp}: ${summary.captured} captured, ${summary.errored ?? 0} errored`);
+    }
+  } catch (e) {
+    console.warn(`[snapshot] team stats refresh failed for ${sp} (grading continues):`, e.message);
+  }
+
   // Grade the slate via the existing service; capture the envelope instead of
   // letting it write (we re-write an ENRICHED version below).
   let envelope = null;