POST /api/analyze/prop on prod returns p_win 0.523, ev_pct -10.4,
model_odds -109, confidence_basis grade_band, value false — every one of
which was absent on 100% of grades before this change. The value triplet
is whole (book -140 / fair -125 / model -109) and correctly refuses to
call a -140 price value when the model gives it 52.3%.
A-emission still pending the 01:00 UTC snapshot (opp_rank_stat populates
only when refreshTeamStats runs in a snapshot). MARKETING HOLD on A-RATED
copy stays until that passes. edge_pct scale remains broken (U-deg pt 2).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01SmNjJAwEnqHPtXbvSZR8kA
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
Completes the diagnosis. Report only; no grade logic or thresholds changed.
The grade is an integer index (GRADE_SCALE, NEUTRAL_INDEX 3) moved by a
flat sum of +/-1.0 and +/-0.5 factor deltas, then clamped and rounded.
grade_thresholds.json is NOT an input mapper in the JS path — engine1
reads it BACKWARDS, taking the letter the index already produced and
looking up that band's midpoint to manufacture `confidence`. So
confidence is a cosmetic re-encoding of the letter: zero information
beyond it, and it can never disagree with it. There is no
data-sufficiency penalty in the live path (the one CLAUDE.md describes is
in mlbGrader.js, which is dead code).
Six of thirteen factors are wired to features nothing populates —
verified: refreshTeamStats has ZERO production callers (so opp_rank_stat
is permanently null, killing a +/-1.0), teamId/season_type/
game_count_in_7d are never passed (gameContext is built as {home_away}
and nothing else), and MLB consistency starves on the same dead
gameLogService path as Finding 2. Also verified: BOTH l20 branches are
delta +1.0 — there is no negative L20 contribution at all.
Arithmetic: an A needs sum >= +4.5; the live maximum is +3.0 (+2.0 on a
back-to-back, and MLB rest_days is 0 most days). D needs <= -1.51; the
live minimum is -1.5 and Math.round(1.5)=2, so it misses by one rounding
tick. Reachable band is index 2..6 = {C-,C,C+,B-,B}, which the adapter's
FOUR_LETTER_MAP (a 3->1 collapse) renders as exactly {C,B} — the observed
output, derived from first principles. Reachable confidences {42,47,52,
57,63} match the live values {47,52,57,63} exactly; C- is truncated by
gradeSlateService keeping the higher-confidence side.
mlb-grade-degradation.md's "25/25 grade<->confidence agreement" is a
TAUTOLOGY, not a validation — confidence is derived from the letter, so
it would report 25/25 even if every grade were wrong.
Recommends feeding the starving factors (restores A/D on merit) and
explicitly REJECTS re-scaling thresholds, which would mint A's without
adding information — every "A" would be a relabelled B.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01SmNjJAwEnqHPtXbvSZR8kA
Kev's call: investigate the B/C grade collapse before building. Report
only — no grade logic, thresholds, or engine code touched.
FINDING 1 — the collapse is real, live and structural. Across 604 ledger
rows and both sports the engine has emitted exactly TWO grades (B, C) and
NINE confidence values (63/57/55/52/47/45/35/25/20), ceiling 63. Still
true today on both sports. Confidence does NOT determine the letter:
conf 45 -> B while 47 and 52 -> C (non-monotonic), so the surfaced
confidence is not the quantity the letter came from. Edge scale still
broken: 311/604 rows exceed the frontend's sane cap of 40, 39 exceed 100,
worst 620.
FINDING 2 (bigger) — the entire probability layer is DEAD in production.
Live /api/snapshot/mlb: p_win, kelly, ev_pct, model_odds and value are
absent on 0/8 grades, while alt_lines (Desk-gated) IS present 8/8 —
proving nothing is tier-stripped, they are simply never computed.
Root cause: gameLogService.pythonPath returns null for MLB by
construction and the Python service is offline for NBA/WNBA, so
meta.gameLogs is [] for every sport; estimateProbability returns
p_over null; every field guarded by `if (pWin != null)` is skipped.
This is the S46 bug in a second location — that fix added an MLB branch
to featureCache.gameLogFeatures (which is why grades/projections still
work) but never to the estimator path.
Consequences: EV — the Model Train's whole ranking signal — has never
been computed on a live prop. Hero v2 matches nothing and always falls
through to the recent-read fallback (live /api/hero-prop returns
is_recent:true). Quarter-Kelly, sold on the pricing page and listed BUILT
in PROMISE-AUDIT.md, never runs. The value triplet is a duet live.
Recommend re-sequencing: revive the probability layer BEFORE G-a and
C-led (C-led would persist a column of nulls; G-a's EV_FLEX_THRESHOLD
would gate on a permanently-null value — Kev's EV_FLEX_ENFORCE=0 ruling
accidentally prevented an outage). featureCache:206-226 already has both
adapter branches and is the template.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01SmNjJAwEnqHPtXbvSZR8kA
REPORT-FIRST per the arc order. G-a is HELD — the data changes the
recommended dials. No engine code touched.
Replayed against live ledger_entries (576 rows, 6 game days, 470 settled)
because the "30 days of stored snapshots" does not exist: snapshot Redis
keys are latest/previous only at 24h TTL, and no backtest harness exists
anywhere in the repo.
Findings that change the plan:
- The -400 floor shipped this morning was the whole win: past -400 hit
80.3% against an 86.9% breakeven = -13.29u / -7.7% ROI on 173 settled.
- Arc 2's incremental cut over the live gate is ~11 props in 6 days. The
only material change is gating the flex band behind 2x EV.
- The flex band (-161..-250) is our BEST band (+2.2% ROI, n=70) and the
takeable band is flat (-0.3%, n=209) — the opposite of the assumption
behind EDGE_FLEX_WALL. Recommend shipping the knob with enforcement
OFF until EV is persisted and measured.
- ev_pct/p_win are on NO ledger row, so the EV half of the gate cannot be
replayed at all. C-led (persist EV) is now the highest-leverage item.
- Confidence is monotonic but understates hit rate by ~20-25 points, and
the entire public ledger contains only B and C grades — zero A/A+.
That breaks hero v2 (isAB) and undermines "A-RATED" copy. Escalated.
- L-a answered: alt_lines carry NO odds and the feed has no alternate
markets. L-b is blocked on a data source, not engine work.
- C-led needs no odds backfill (locked_odds 99.1% populated).
- U-deg: the projection==0 leak is already closed (0 since 07-18).
- C4 confirmed in data (359/376 MLB closes == the lock). Stays suppressed.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01SmNjJAwEnqHPtXbvSZR8kA
Kev's call: the 30D accuracy surfaces must read TRUTH, not a cache that can't be
filtered. My earlier degraded-row exclusion only touched getModelAggregate
(Postgres); the public buckets/badge still read outcomeService (Redis outcome
log), which counts degraded projection-0 outcomes and has no field to filter on.
- /api/accuracy (AccuracyBadge) + /api/ledger/accuracy (buckets/ModelRecord)
now source from the clean Postgres ledger aggregate via new
ledgerService.getAccuracyView + accuracyBucketsFromAgg (model_value > 0
excludes degraded rows). Same response shapes → no frontend change. Redis
outcome log is now read by nothing public; it can age out or be rebuilt.
- BEAT CLOSE is a MEASURED-WRONG ZERO: captureClosing re-records the locked line
as the "closing" line, so clv is flat on the whole sample and beat_close reads
0% (comparing a number to itself). Full write-up: specs/audit-data/
clv-capture-broken.md (the fix belongs to C4). Until then, beat_close_pct +
clv_distribution are SUPPRESSED at the source (getModelAggregate, gated by
clvCaptureReliable() / CLV_CAPTURE_RELIABLE=1). Every public surface already
renders BEAT CLOSE only when non-null, so they all hide it now — no wrong zero
anywhere. HIT RATE (real) is unaffected.
Suite 271/3261 green, web build exit 0.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Work-order #4 closed. First post-deploy snapshot (2026-07-17 14:00:53 UTC)
re-graded with the fix. Before → after:
- projection==0: 9/25 → 0/25 (the nine now refuse)
- grade<->confidence: mismatch → 25/25 agree
- edge_pct: {20,60,100,140} cluster → 7 continuous values, all-positive projections
The lone remaining edge=100 is a REAL projection (Abreu hits, line 0.5, proj 1.0
over = 100% by (model-line)/line), not the old proj=0 degeneracy. Verified.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
scripts/validate-grade-fix.js checks the live MLB snapshot for the three
degradation signatures (projection=0, edge=100 cluster, grade/conf disagreement)
— run after the next 14:00 UTC regrade to fingerprint the fix. The finding doc
now records root causes, fixes (commits 888d103/9fc4edf), the blast-radius SQL
(box can't reach Supabase directly), and the shared-path note for NBA/WNBA.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
DISPLAY FIX (shipped): the league leaderboard rendered raw snake_case
("stolen_bases U0.5", "earned_runs U2.5"). New canonical short-label lib
web/src/lib/statAbbrev.js (one source, CommonJS + unit-tested) maps stat_type
to SB/ER/TB/HR/K/PTS/… and ExploreHub routes through it. Unknown ids upper-case
their words so raw snake_case can never leak again.
FLAG (reported, NOT silently changed — per the audit's instruction): the "B at
45% confidence" is a BACKEND grading issue, diagnosed against live snapshot:
- 25/25 grades mismatch their own confidence vs grade_thresholds.json (B shown
at conf 55 = the B- band; a systematic one-sub-tier gap on every prop). The
surfaced `confidence` is not the probability that derived the letter (likely
the data-sufficiency penalty applied to display-only).
- 9/25 have projection=0 — the MLB feature path feeds 0 instead of refusing
(S58 insufficient_data), which also produces the P1-7 broken edge_pct.
Full write-up + do-not list: specs/audit-data/mlb-grade-degradation.md. NOT
re-lettering or shifting thresholds on the frontend — that would hide the bug.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
builtbykev