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

specs/audit-data/mlb-grade-degradation.md

@@ -30,6 +30,28 @@ bug, fixed at the source in the generic grade path (`engine1` +
    to any grade's displayed confidence resolves back to the same letter (proven
    for all 11 grades in `tests/unit/mlbGradeDegradation.test.js`).
 
+   > ### ⚠️ CORRECTION (Session 63, 2026-07-19) — THE "25/25 AGREEMENT" WAS A TAUTOLOGY
+   >
+   > **Do not cite the 25/25 grade↔confidence agreement below as validation of
+   > grade quality. It validates nothing.**
+   >
+   > The fix above made `confidence` a *deterministic function of the letter*:
+   > engine1 picks a letter via an additive factor index, then looks up that
+   > letter's band midpoint to produce the number (`engine1.js:29-36`). Feeding
+   > that number back through the same table can only ever return the letter it
+   > came from. **The round-trip would report 25/25 even if every grade were
+   > wrong.**
+   >
+   > It is a real fix for a real bug (the two encodings had drifted a sub-tier
+   > apart) — it is simply a *consistency* check, not an *accuracy* check.
+   > `confidence` carries ZERO information beyond the letter. The genuinely
+   > independent probability is `p_win` (the quantile estimate over real game
+   > logs), which Session 63 discovered had never been computed in production at
+   > all. Payloads now carry `confidence_basis: 'grade_band'` so no consumer can
+   > mistake the derived number for a model probability.
+   >
+   > Full diagnosis: `specs/audit-data/grade-collapse.md`.
+
 ## Blast radius (commit `9fc4edf`) — work-order #6
 The degraded grades (projection=0 → `model_value = 0`) are already settled in
 the append-only `ledger_entries` and are NOT deleted. Functional marking: