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/model-train.md

@@ -176,6 +176,33 @@ Full arc definitions live in the Session-63 order. Status only here; update as e
 | **U-deg** MLB degradation | ✅ **STATUS REPORTED** | `projection==0` leak **already closed** (0 occurrences since 07-18). `edge_pct` scale still broken. |
 | **U-fp** Arc 1 fingerprint | open | Do it on the first deploy this train ships. |
 
+### ✅ SESSION 63 — PROBABILITY LAYER + GRADE RANGE RESTORED (shipped)
+
+The re-sequenced step 1+2, folded into one change. Full write-up:
+`specs/audit-data/grade-collapse.md`.
+- **The probability layer was DEAD in production** — `p_win`/`ev_pct`/`kelly`/
+  `model_odds`/`value` were absent on 0/8 live grades because `gameLogService`
+  returns null for MLB by construction and the Python service is offline for
+  NBA/WNBA. `featureCache.getStatRows` now supplies normalized rows for every
+  sport. **Verified: `p_win` 25/25 on real WNBA props, 8/8 MLB (was 0).**
+- **Hero v2 had never once selected on EV** (it requires a finite `ev_pct`) and
+  silently fell through to the recent-read fallback every time.
+- **Grade range:** `refreshTeamStats` wired into `runSnapshot` (it had ZERO
+  callers, so `opp_rank_stat` was permanently null), `game_count_in_7d` derived
+  from real logs, and **L20 made symmetric** (there was no negative branch at
+  all). D now emits on merit (WNBA 1/25, an earned `p_win` 0.365); A is proven
+  reachable arithmetically but **has not yet emitted in production — that is the
+  outstanding fingerprint**.
+- **Calibration guard:** consistency CV was NBA-tuned; for any stat with mean < 4,
+  `cv ≈ 1/√mean` forces `boom_bust`. It would have stamped a blanket −1.0 on
+  nearly every MLB prop. Floored at `CONSISTENCY_MIN_MEAN=4` → `unknown` below it.
+- **Confidence is NOT a probability** — payloads now carry
+  `confidence_basis: 'grade_band'`. The real signal is `p_win`.
+- **`mlbGrader.js` REMOVED** (dead; referenced only by its own test).
+- 🔴 **MARKETING HOLD:** "A-RATED" copy (AccuracyBadge, TopSignals) is unsupported
+  until a production fingerprint shows real A grades. Honest fallbacks confirmed
+  rendering ("MODEL · 63% HIT"); nothing fabricated ships.
+
 ### 🔶 OPEN DECISION — FLEX BAND ENFORCEMENT (Kev, 2026-07-19)
 
 **Ruling:** build `EDGE_FLEX_WALL` (−250) + `EV_FLEX_THRESHOLD` (default **4 %**, = 2×