494c83cf7628afe24c4c0326bfd4c94b1614c34e
482 Commits
| Author | SHA1 | Message | Date | |
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 builtbykev
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b8ee216c62 |
docs: CLV instrument repair + the straight finding (unders lag the close)
closing_prob 59 -> 406 (MLB 248, WNBA 158). Root cause was attachClosingProb's truncated read + write-once market_unavailable, not capture or the join. CLV measured: MLB unders lag the close (mean -9.1 prob-pts, 74% lose), MLB overs +2.0, WNBA flat -> the +4.57% MLB-C and over/under asymmetry are substantially stale-line artifacts. Unblocks the proj-v1.1 proof order. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01VsztNChZ7vEvSR61AuMhD1 |
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builtbykev
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6552281661 |
CLV instrument repair: fix attachClosingProb read + recoverable market_unavailable
The closing_prob funnel collapsed 100k priced captures -> 59 usable. Root cause (VERIFIED against prod, join key is PERFECT with 0 mismatches): - attachClosingProb read closing_captures with .limit(50000) and NO ORDER BY on a 730k-row table that is 86% refusal rows -> saw ~7% for MLB, missed most priced closes and declared 200+ rows closeless that HAD a capture. - market_unavailable_reason was write-once/terminal, so a row wrongly declared (truncated read / premature declaration before the capture was visible) could never recover even once its genuine capture existed. 298 rows (204 MLB + 94 WNBA) were stuck this way. Fix (CLV computation only — no grade/locked_odds/outcome touched): - Read ONLY priced captures (missed_reason IS NULL, both odds NOT NULL), scoped to the candidate rows' game_dates -> small AND complete, no arbitrary truncation. - Drop the market_unavailable exclusion from candidates; make it a re-checkable absence: a genuine close now UPGRADES the row (writes closing_prob, clears the verdict). closing_prob stays write-once (first true close wins). No capture + past game -> still declared absent (honest). No churn on already-absent rows. - New internal trigger POST /api/internal/ledger/attach-closing[/:sport] for backfill + verification (scheduler already runs attach per tick). Recovers ~312 usable closes (59 -> ~371), MLB included. Capture itself was healthy all along (94.9% MLB / 95.8% WNBA per-prop coverage). Full suite 3835 green (17/17 instrument tests incl. 2 new recovery cases), web build exit 0. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01VsztNChZ7vEvSR61AuMhD1 |
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builtbykev
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afb56b144b |
NexaPay purge: VYNDR is Stripe-only — remove all NexaPay traces
NexaPay was cross-project contamination (from another venture) — never a real VYNDR payment path. Purged; Stripe path untouched. Removed: - web/src/services/nexapay.ts (createPaymentLink/getTransaction/HMAC verify) - web/src/app/api/webhook/nexapay/route.ts (the only importer; Next-registered, reachable — now gone) - NexaPay comments in email.ts + checkout/route.ts - Active NexaPay entries in docs/SYSTEM-MANIFEST.md (route list, NEXAPAY_* env table, service row) + stale claim in wiring-data-train.md - sw.js precache entry for the deleted webhook chunk Verified: ZERO NexaPay in code (web/src, src, tests). Full suite 3833 green (count unchanged — nothing depended on it, confirming it was dead). Web build exit 0. sw.js parses clean. Stripe checkout untouched (Next→Express→Stripe). FLAGGED FOR KEV (a repo delete cannot close these): - Coolify env: remove NEXAPAY_API_KEY / NEXAPAY_WEBHOOK_SECRET / NEXAPAY_API_URL - Revoke the NexaPay API key + webhook secret at NexaPay's dashboard; de-register the webhook if an account was ever configured - DB column user_profiles.nexapay_customer_id is orphaned (no reader/writer) — drop via a follow-up migration (migration 011 left as history) Cross-project check: ZERO Noctem-Supabase refs; VYNDR references only its own Supabase (zmdnczhtdxcddsxzttub). NexaPay was the sole contamination found. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01VsztNChZ7vEvSR61AuMhD1 |
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builtbykev
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3592aba8d5 |
docs: log honesty pass in completion matrix + STATE (rows 19/20/24 HONEST fixed)
Records the six live fabrications removed/hidden, keeps media/newsletter/WIRE on the board as real work, logs the news/line-movement signal as a future model input, and logs the known honesty gaps (hit-rate-without-ROI, CLV starved). Honest state: "no KNOWN live fabrications," not "provably none." Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01VsztNChZ7vEvSR61AuMhD1 |
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builtbykev
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6bc18d823c |
Honesty pass: remove every live fabrication (REMOVE/HIDE only, no feature cut)
Six live untruths corrected — no grade/snapshot/scorer/pipeline touched: 1. /compare — hardcoded Jokic A+/Wembanyama A + fake VERDICT replaced with an honest in-development state; removed from Nav + BottomTabBar (route still resolves, never the sample). Real two-player build is later. 2. Pricing — founder Desk $34.99→$44.99 (matches lib/checkout.js), Analyst $14.99; removed the struck $19.99/$44.99 "regular" numbers and DeskShowcase's stale $34.99. First-100 counter is real (ClaimMeter → Stripe countFounderSeats); no fake "first 50" desk claim added (no such counter exists). 3. FAQ "NexaPay" → Stripe (verified: live checkout is Next→Express→checkout.stripe.com). 4. FAQ + Features "Brier/CLV published from day one" removed (not surfaced yet) — returns when real. Backend Brier compute untouched. 5. MobileEdgeBoard removed from the Slate — its edge% feed was a miscalibrated placeholder (masked >40% as "—"); phones now show the real game cards. 6. Price triplet — never-computed model/EV now derives NO_MODEL (honest absent, MODEL "—" / "NOT PRICED", no verdict) instead of QUARANTINE's false "we suppressed our price / a leg is poisoned" copy. Fixes grade card + LiveHeroProp. Full suite 3833 green, web build exit 0. Tests updated to the new honest contracts. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01VsztNChZ7vEvSR61AuMhD1 |
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builtbykev
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be6b4a2849 |
inventory: VYNDR-COMPLETION-MATRIX (5-part DONE map of every surface + model)
Read-only inventory order — no code built/wired/fixed/deployed. Maps every
user-facing surface and model component against DESIGNED·BUILT·WIRED·LIVE·HONEST,
re-derived from repo
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builtbykev
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b0a51c8a0d |
docs: /api/books contract + crown gate (Book Comparison order)
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01VsztNChZ7vEvSR61AuMhD1 |
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builtbykev
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e81c9b8c51 |
Book Comparison Phase 1-3(backend): fenced per-book store + honest gated crown
Per-book prices existed only transiently (odds cache, ~1h, raw names, grade-path
input); every grade-path persistence point collapses to one book. The
/api/books feature was built+mounted but non-functional (fed FLAT rows to a
GROUPED comparator -> always empty).
Phase 1: bookPriceStore captures per-book prices from `props` BEFORE dedupeProps,
keyed nameKey|stat, into bookprices:{sport} (SNAP_TTL) in snapshotService. Fenced:
reads props, writes its own key, read by nothing on the grade path. Grade proven
byte-identical (test + no-grade-path-reference grep test).
Phase 2: scripts/measure-book-spread.js reports same-line best-vs-worst spread
(cents + implied-prob pts), per sport, never pooled. Pre-registered crown
threshold: median >=8c OR >=2pp. Runs post-deploy on real data.
Phase 3 (backend): compareProp is honest-absent (single-book/flat -> no crown)
and the crown is gated (BOOK_CROWN_ENABLED, default OFF until Phase 2 clears).
/api/books repointed to the snapshot-locked store (fallback odds cache),
nameKey-matched; `source` field is the deploy fingerprint.
HELD unchanged: dedupeProps, snapshot dedup, selector, grade, champion,
challengers, ranking, edge_pct/ev_pct. UI routing of BookComparison + crown
treatment deferred to post-measurement (gated on Phase 2). Full suite 3834 green,
web build exit 0.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01VsztNChZ7vEvSR61AuMhD1
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builtbykev
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914a057611 |
proj-v1 book-implied: raw odds → de-vigged FAIR (fix self-flattering basis)
proj_book_implied derived from raw book_odds — VIG-INCLUSIVE. A -110/-110 market
implies 52.4%/side (104.8% sum); fair is 50%. Comparing our P against raw book
overstates the book on both sides, biasing the handicapper test IN OUR FAVOR; on
juiced longshots (the Judge HR -18.5pt case) much of that "edge" was vig, not
disagreement.
Fix (fenced to proj-v1's stored comparison basis): proj_book_implied now derives
from DE-VIGGED FAIR via the grade's g.fair_prob — the SAME multiplicative de-vig
the triplet uses (utils/devig.js), so the basis matches the product's shown fair.
Expressed on the OVER basis (under props → 1 - fair) to match our stored P(≥rung);
traded-rung ladder book_implied likewise. HONEST-NULL where fair is uncomputable
(one-sided market, ~14%) — NEVER a raw-book fallback (that would recreate the vig
bias on a subset and mix two bases in one ledger). proj_factors records
book_implied_basis ('fair_multiplicative'|'none').
Phase 0 (prod-verified): fair reachable at store point (g.fair_prob on the grade,
no threading); 86% batting coverage; method = multiplicative/proportional.
Phase 2 FLAG: multiplicative de-vig mis-splits vig on juiced longshots (favorite-
longshot bias), so a longshot fair still carries known method bias — flagged
per-row (longshot_devig_caveat); a better de-vig (Shin/power) is a separate item.
Phase 3: version bumped proj-v1 → proj-v1.1 so pre-fix (raw-book) and post-fix
(fair) rows never silently mix — the projection model is byte-identical, only the
basis changed; pre-fix rows can't be recomputed (only the graded side's odds were
stored). Champion + arch-v1 + contact-v1 + proj-v1's other columns untouched.
proj suites 26/26.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj
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builtbykev
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e96b0dbb6d |
proj-v1: book-implied from book_odds (grades carry odds, not fair_prob)
The live fingerprint showed proj_book_implied null on every real row: grades carry book_odds/locked_odds (e.g. -264) but NOT a de-vigged fair_prob, so keying the book comparison off fair_prob yielded null. The book ODDS are exactly "the book's implied probability" the handicapper test needs. Now proj_book_implied + the traded rung's book_implied derive from americanToImplied(book_odds), expressed on the OVER basis (under props → 1 - implied) so it's directly comparable to our P(≥rung). Vigged (a known offset the ledger measures both sides of). proj-v1 suites 24/24. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj |
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builtbykev
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316b79733e |
proj-v1 sanity fixes (caught in the real-data induction)
1. matchupRead fly-ball signal: the batter metrics `gb_pct_bb`/`fb_ld_pct` are MISLABELED — they're exit velocities by batted-ball type (Judge fb_ld_pct = 100.3 mph, not a rate), not ground/fly RATES. Switched fly-ball lean to avg_launch_angle (league p10/p50/p90 = 7.1/13.9/20.1°), the correct signal. 2. Absolute rate now fits the FULL season (recency-weighted), not a 20-game window: the window under-sampled rare stats — Judge HR projected 0.11 vs his 0.28 season rate (a fake -32pt edge). Now point=0.27 (matches season); the last-5-2x recency lean is preserved. Post-fix induction (real statsapi logs + real statcast): Judge HR 0.27 (P>=1 0.235 vs book 0.42 -> flags the juiced over), Judge TB P>=2 0.548 vs 0.48 (+6.8pt), thin-hot 3-game P>=1 0.726 / P>=3 0.164 (credible low, thin high), .300 hitter != 3.0. proj-v1 suites 23/23. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj |
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builtbykev
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6386e737b9 |
proj-v1: absolute matchup projection challenger (distribution + full ladder)
A THIRD challenger (after arch-v1, contact-v1), MLB batting v1. Champion is market-relative P(stat>LINE); proj-v1 is ABSOLUTE — what the hitter will DO — emitted as a full distribution from which the WHOLE LADDER (P≥1,P≥2,P≥3) derives. Champion untouched; nothing claimed; the ledger decides per rung, per stat. - projection/distribution.js — Bayesian Gamma-Poisson → negative-binomial predictive. Admits over-dispersion; under-dispersion → Poisson approx (conservative, documented). Uncertainty scales with sample by construction (r=α): thin → WIDE (real mass on P≥1, honestly thin P≥3), thick → tight. NEVER abstains — width carries the honesty. - projection/matchupRead.js — the input the book doesn't use. HONEST FIDELITY: pitcher repertoire is rich (97% pitch-mix) but hitters have NO pitch-type performance, so TRUE repertoire-vs-profile is impossible today. This is the COARSE version (arsenal buckets fastball/sinker/breaking + whiff/hard-hit tendency × hitter whiff/chase/gb-fb/hard-hit) — beats generic L/R, derived + documented + TESTED two-sided. A hitter pitch-type feed unlocks the true form. - projectionChallenger.js — park RELATIVE to the player's own log exposure (isHome→own park, away→opp park; Phase B's raw-multiply bug solved), recency- weighted fit, per-factor breakdown (form/park/weather/platoon/matchup — show your work), full rung set + book-implied per rung. Combined non-form multiplier bounded. - Wired after contact-v1, own try, flag PROJ_V1_ENABLED, reusing arch-v1's already-computed park/weather/platoon (no duplicate env I/O). Own ledger columns (migration 032, applied to prod): distribution, ladder, point, line, our-P, book-implied, factor breakdown — measurable per rung/stat after settle. Phase 0 (prod-verified): venue join via isHome; NB family; uncertainty-as-width; coarse matchup honest fidelity; no lineup-slot (per-game rate, volume implicit). Sanity: thin-hot → wide (credible low rung, thin high rung); .300 hitter ≠ 3.0; matchup two-sided; champion byte-identical. proj-v1 suites 23/23; snapshot/ ledger/siblings 74 green. Forward-only, version-stamped, PROJ_V1_ENABLED kill. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj |
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builtbykev
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b6f12daa98 |
Contact-quality challenger (contact-v1) — nominate, don't swap
Phase A #2: the champion grade (l5/l20 result-based form) is a HYPOTHESIS that contact quality predicts better — unmeasured on our props, with zero settled p_win yet. Swapping l5/l20 (the champion's two heaviest ±1.0 factors) blind could degrade the core grade undetectably for weeks. So this NOMINATES contact quality as a second challenger, records what it WOULD project per prop, and lets the settled ledger decide. Nothing users see changes; the champion is untouched. - src/services/contactChallenger.js — pure, mirrors challengerProjection. Log- odds lean (capped, never a re-forecast) from SEASON contact quality vs league percentiles. Metric→prop mapping is the whole game: barrel_pct→HR, hard_hit_pct→TB/doubles, k_pct-INVERSE→hits (singles resolve on contact frequency, not barrels), k_pct→batter K. rbi/runs/walks ABSTAIN (opportunity/ discipline — no clean contact predictor). Honest-absent: thin (<50 PA)/absent/ unmapped/non-batter → p_win_contact NULL (no projection), never a fallback; "measured but unremarkable" is distinct (equals champion, delta 0). - Wired in snapshotService AFTER arch-v1, reusing the already-loaded statcast rows; its own try so a second challenger can't break the pipeline. Reads g.p_win, never writes it. - Retained SEPARATELY on the ledger (p_win_contact/contact_delta/ contact_adjustments/contact_version='contact-v1') so each challenger's marginal contribution is measured independently; ledger_entries.stat gives per-prop-type segmentation. Migration 031 (applied to prod). Phase 0 (prod-verified): statcast_aggregates is SEASON cumulative (not rolling), 48h stale now but season-scoped so ~8 PA/600 is negligible; 100% of graded hitters covered, 92% at ≥50 PA; no xBA/xwOBA in the feed. Forward-only, version-stamped (contact_version null on pre-nomination rows). Promotion is a LATER decision on settled evidence, per prop type — never asserted here. contactChallenger 14/14; snapshot/ledger/arch-v1 suites 80 green. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj |
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builtbykev
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125919f86a |
Scanner reskin: amber → blue boundary channel + build never-built S6/S7 states
Semantic COLOR fix, not cosmetic. The S6/S7 build predated the current Scanner
States spec: it used AMBER (the quarantine / model-suppressed channel) for the
"no market / line not priced" case, telling users "model suppressed" when the
truth is "the board never priced this." Corrected to the HANDOFF Session-3
blue-boundary law: BLUE (--priced-out #8FB2DE) = no-market boundary; amber stays
QUARANTINE; red stays REFUSAL.
Phase 1 (reskin): NoMarketState → dashed BLUE void box + blue header/copy; the
S7 rows → spec format (o 27.5 · BK −114 · ◆ −105 · OPEN READ ▸) at 44px,
390-legible. Input-area surfacer pills reskinned to the blue channel too.
Phase 2 (never-built states, only those Phase 0 confirmed against live data):
- GREEN CTA with LIVE player count ("PLAYER · N PRICED PROPS ▸"), degrading
honestly to the board path ("N PROPS LIVE · TONIGHT'S BOARD ▸") at 0 — count
from the SAME fresh index as the rows (pricedCountForPlayer), can't disagree.
- CASE A none-priced DEFAULT: "WE PRICE THESE FOR [player]" — the player's other
priced stats (pricedStatsForPlayer, filter by nameKey).
- Typed-line-mismatch blue fact line ("o X ISN'T PRICED · NEAREST ↓").
FLAGGED / not built (no shells): Case C off-slate quiet-stop needs schedule/
roster membership the pricedLines index doesn't carry (out of the presentation
fence). Spec CONTRADICTION: Case B says "fair previews amber," but the law
reserves amber for quarantine — fair renders NEUTRAL ◆ (blue-dim), not amber, to
avoid blurring the channel.
Free-tier gate VERIFIED before rendering FAIR: fair_odds is the de-vigged MARKET
price (valueState: "never hide the honest fair number"), NOT the gated
model_odds — no paid leak. Carried through indexPricedLines (additive; keying/
refresh/onPick/stale-tap all unchanged — the proven S7 data path is untouched).
Scan A byte-identical; PRICED_NUDGE_ENABLED still the kill switch; reversible.
Build exit 0; priced + parity suites green (67).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj
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builtbykev
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83e9da3663 |
Consistency classifier: CV → index of dispersion for low-mean counts
The A/D investigation found CV (std/mean) is scale-broken on count data —
for a Poisson-ish stat cv ≈ 1/sqrt(mean), so EVERY stat with mean < 4 blew
past the boom_bust cutoff regardless of behavior. The S63 stopgap made those
return 'unknown', which silently ate a real +1.0 consistency signal on every
MLB batting prop — steady low-mean hitters never got their earned factor.
Fix, fenced to the low-mean branch of consistencyScore (the only branch that
was returning 'unknown'): classify with the index of dispersion (variance/mean,
Poisson baseline 1.0) — the scale-appropriate, UNBIASED statistic for counts.
mean ≥ 4 keeps the NBA-calibrated CV path BYTE-IDENTICAL (zero NBA blast
radius). This is a bug CORRECTION, not threshold loosening: the CV thresholds
and the engine1 ±1.0 delta are unchanged.
Bands (asymmetric around Poisson 1.0, since counts are naturally mildly
over-dispersed): iod<0.60 elite / <0.85 reliable (+1.0) / ≤1.30 volatile
(neutral) / >1.30 boom_bust (−1.0). Sample floor MIN_GAMES_FOR_IOD=8 so a
thin sample abstains ('unknown') — no small-sample guess.
Validated on real 10-game logs (two-sided): Kwan hits 0.67 / Alonso hits
0.78 → reliable (RECOVERED); Alonso TB 2.57 / Henderson hits 1.33 → boom_bust
(no false consistency); HR mean 0.1 → 1.0 → neutral. Direct engine1 proof: a
strong steady prop that grades B+ today reaches A- once the +1.0 fires; a
boom-bust bat stays B (no inflation). A- now emerges NATURALLY from a real
recovered factor. Standing two-sided test pins all three directions.
Forward-only (settled grades are locked in the ledger, never re-graded).
Emitting A- ≠ proving A- — the A-tier record accrues from emission, still
measurement-gated. Full unit suite green (4 pre-existing redis/timing flakes
pass in isolation); web build exit 0.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj
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builtbykev
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3440738d9e |
Landing hero → bundle visual system; claims filtered to earned only
Migrate the Landing hero (Landing-only component; LiveHeroProp/triplet untouched) to the design bundle's visual language: mono "SPORTS INTELLIGENCE TERMINAL" eyebrow, tightened 56px/800 headline "Every line, graded before you bet it.", dual mono CTAs (OPEN THE TERMINAL / SEE THE PUBLIC RECORD), proof chips. Claims audited against the held list — the bundle's marketing copy carries claims we have not earned; those did NOT ship: - "CLV-VERIFIED" chip + "verified against closing lines" — HELD (C4 broken) - "312 props / 47 games" count — fabricated demo → ABSENT (no count) Shipped copy is earned only: pre-graded, edge-ranked, settled in public, misses included; PUBLIC LEDGER / MISSES INCLUDED / 5 FREE READS chips. HELD + FLAGGED for a design pass (fabrication-backed, no honest designed state — check-don't-freelance): the edge-board demo (A+/A don't emit), the "grades calibrate · A+ hit 80%" claim (calibration unmeasured), and the tier-record band (real data is B/C-only, no ROI). Not built with fake data. Tokens via var(--g-a/--void/--border/…) with bundle-hex fallbacks (documented-intentional pattern). Build exit 0; parity QA green. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj |
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builtbykev
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d879a10dd3 |
Design bundle (2): current source of truth — Scanner States + blue-boundary law
Reference material only, ZERO product code. Adds Vyndr Scanner States.dc.html (S6/S7 spec) + HANDOFF Session 3 blue-boundary-channel law (#8FB2DE = the honesty channel: priced-out / no-market / line-not-priced). This is the diff baseline for the design-migration arc. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj |
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builtbykev
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9a91837f63 |
STATE: Session 80 — S7 nudge freshness completed; premise corrected report-first
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj |
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builtbykev
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4f3f433aae |
Complete S7 priced-line nudge: freshness on a long-open page + reversible gate
REPORT-FIRST correction. This order's premise — "S7 is a shell that doesn't update per selection" — is not what the code does. pricedForSelection is a useMemo on [pricedIndex, selectedPlayer, stat] and setSelectedPlayer/setStat fire on every user pick, so the chips already update per selection, and the prior session's verification of that stands. The genuine gap was FRESHNESS: the snapshot fetch depended on [sport] only, so pricedIndex was fetched once per sport-change and never refreshed. The pricing cron re-prices at five UTC hours, so a scanner left open across a cron boundary surfaced hour-stale priced lines. That is the real defect, and the only one fixed. FRESHNESS. The fetch is now a refreshPriced callback re-run when the held snapshot is older than PRICED_STALE_MS (30s, matching the /api/snapshot cache) at the moment of use — on selection change and on window focus — so a long-open page never shows a stale line. Sport change still clears the index first, so the old sport's lines never flash. STALE-TAP was already safe and is unchanged: the scan submit re-fetches the live snapshot server-side, so a chip that's gone stale between render and tap either lands on a real triplet (still priced) or degrades to the honest empty state (rotated away) — proven in the prior session and re-confirmed here (an off-snapshot line returns no market and shows the empty state). REVERSIBLE GATE. The whole nudge sits behind one PRICED_NUDGE_ENABLED flag: false empties the surfaced set, so the scanner falls back to S6's link-only empty state with the chips gone. Shipping enabled only after the cases are proven this session; the flag is the instant revert lever. DISPLAY-LAYER ONLY. Only scan/page.tsx changed. GradeResultCard, PriceTriplet, gradeAdapter, valueState, both scan routes and the pure pricedLines helper are byte-identical — Scan A and the scan-submit resolution are untouched, and the change is independently revertible. Tests 3765 passed / 303 suites, web build exit 0. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj |
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builtbykev
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33d72e38f9 |
STATE: Session 79 — read-card no-market empty state + priced-line surfacer, live
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj |
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builtbykev
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e311f53738 |
Read-card scan: honest no-market empty state + surface real priced lines
The Session-78 diagnosis stands: the join works, and a marketless scan rightly
shows no triplet. This makes that absence legible and points the user at what IS
priced, without fabricating a market.
PHASE 0 gate — design-check, reachability, timing, all clear. Design-check: the
bundle has the triplet's own REFUSAL language ("we'd rather show nothing than a
number we can't stand behind") as the honesty precedent, and a designed
EmptyState component whose actions give a path forward — so the empty state is
built in the established visual language, not freelanced. Reachability: the
scanner already fetches games/odds/search per selection; the snapshot is one
more public, 30s-cached fetch per sport, re-run when the sport changes.
Staleness: the snapshot rotates 5x/day and every scan re-validates the market
server-side at submit time, so a surfaced line that goes stale degrades to the
empty state on tap rather than a vanishing triplet — the stale-tap guard is
inherent, not bolted on.
Reversibility was the design constraint. The working card, price triplet, grade
adapter, valueState and the scan route are BYTE-IDENTICAL — a test asserts none
of them even reference the new empty state. Everything new lives in two added
files (lib/pricedLines.js, components/vyndr/NoMarketState.tsx) and additive
blocks in the scan page. Removing them leaves the Scan-A path untouched.
Non-fabricating by construction: indexPricedLines only keeps snapshot rows that
carry a real book price, keyed by exact player+stat via nameKey. A different
stat priced for the same player surfaces nothing for the picked stat; an
off-slate player surfaces nothing; nothing is suggested, interpolated, or
rounded to a nearest line. The empty state shows no market numbers of its own —
only real priced lines as one-tap chips, or a link to the live board when there
are none.
Framing is help, not restriction: a "PRICED TONIGHT" chip row sits under the
free-typed line input, and the scanner still accepts any player, stat and line.
Tapping a chip pre-fills the priced line and re-scans it — the market is
re-resolved server-side, so the tap either yields a real triplet or degrades to
the honest empty state.
Path forward, not a wall: a marketless scan no longer dead-ends in blank space.
It states truthfully that the board didn't price that line, keeps the grade, and
routes the user to the priced lines for that exact player+stat or to tonight's
board.
Tests 3760 passed / 303 suites, web build exit 0.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj
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builtbykev
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4c9707ffbb |
Platoon polarity: VERIFIED correct, pinned by a standing test
Report-only verification of the two unproven claims from the Session-77 wiring, which fired platoon on synthetic split-less hitters where the K=600 regression zeroed the multiplier and masked both direction and resolution. No product code changed — this adds one standing regression test. FIXTURE — Yordan Alvarez (LHB), real 2026 splits, deep both hands: 115 PA vs LHP at .529 slg, 327 PA vs RHP at .695, overall .652. The regression leaves a material multiplier both ways (0.97 vs LHP, 1.023 vs RHP), so unlike the last test this fixture can actually reveal direction. RESOLUTION — verified on the live slate that the pitcher-hand attached to a hitter is the OPPOSING team's probable, not his own. CLE (home) resolved to Minnesota's away starter 696070; MIN (away) resolved to Cleveland's home starter 800048. The chain — hitter's team, the game, the other team, that team's probable, that pitcher's hand — is correct, and it is pinned independently of direction because a backwards resolution is invisible on a neutral hitter. DIRECTION — deterministic L-vs-R on the frozen Alvarez fixture. Facing RHP nudges UP (1.023) because he slugs .695 there, above his .652 overall — a favorable opposite-hand matchup, exactly what platoon theory predicts for a left-handed bat. Facing LHP nudges DOWN (0.97). The two move opposite directions, and crucially the SPECIFIC sides are asserted, not merely "opposite" — a mirrored-but-inverted implementation would put RHP below 1 and fails here. Both- backwards is ruled out. The test also pins a REVERSE-split hitter, Brandon Nimmo, who hits better vs LHP than RHP. His multiplier goes up vs LHP, following his real numbers rather than a hardcoded LHB-vs-RHP assumption — proof the sign is data-driven, which is the correct design. VERDICT: PASS. Resolution correct, direction correctly signed against both the real split and platoon theory. Pinned by tests/unit/platoonPolarity.test.js so the polarity cannot silently regress — the opp_rank_stat lesson applied. Tests 3750 passed / 302 suites. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj |
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builtbykev
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535a7b70ea |
STATE: Session 77 — dormant adjusters wired; env non-null proven, ledger row pending
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj |
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builtbykev
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7b25d97891 |
Wire the four dormant adjusters live — pure input-wiring
Verified state going in: parkBase, weatherMod and platoonSplits were called by nothing, and env_multiplier was non-null on zero rows across four orders. The adjusters were correct in isolation and starved of inputs. This gives them their inputs and changes none of their internal logic — the five adjuster files are byte-identical after this commit. PHASE 0 GATE — all three inputs are available at snapshot build, and the two join keys already existed. Venue: always, on every schedule game object. First-pitch: always, gameTime on the same object. Opposing-pitcher hand: present once the probable is declared, via the pitchers endpoint's pitcherId joined to statsapi handedness — 15 of 15 games declared this afternoon, though morning locks precede declaration and those props honest-absent on platoon, correctly. The batter-handedness join (statcast bats) and the MLBAM id were already on each grade from earlier sessions. environmentContext.js is the wiring, kept separate from the adjusters so they stay pure. It fetches once per snapshot: the schedule (team to venue, gameTime), probable pitchers (team to opposing pitcher id), one batched handedness call, one Open-Meteo forecast per home park, and batter splits per graded hitter. Park coordinates for 30 parks live here as public geometry, the same class as the dome list and centre-field bearings already in weatherMod, rather than inside an adjuster. Everything is best-effort: a missing venue drops park and weather, an undeclared pitcher drops platoon, and any fetch failure degrades that prop to archetype-only rather than breaking the pipeline the adjusters are measured inside. attachChallenger becomes async and takes a per-grade contextFor that returns the environment coefficient (park_base x weather_mod, composed) and the matchup (platoon). Point-in-time holds: the weather is a forecast for first pitch fetched now, and the split is the hitter's line entering the game — neither reads a settle-time value. Attribution is independent. env_multiplier, env_park_base, env_weather_mod and env_weather_state land in their own ledger columns, and challenger_adjustments keeps every axis — archetype, environment, matchup — as a separate entry, so when volume accrues each of the four can be measured for its own marginal contribution rather than as one blended delta. The combined move stays bounded, tested on the worst case: a Coors slugger with wind out and a favourable platoon, all at once, still moves under 12 percent, because every layer is capped and the total nudge is clamped. Stacking leans, it does not compound into a re-forecast. Non-MLB honest-absents entirely — park, weather and platoon are MLB-only today, so a WNBA prop gets no environment and no matchup. The champion is untouched throughout: p_win is read, never written, the served snapshot payload is still the enriched object, and a test confirms p_win passes through byte-for-byte while the challenger moves. Tests 3741 passed / 301 suites, web build exit 0. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj |
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builtbykev
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2adf192d98 |
STATE: Session 76 — platoon regressed; plumbing gap now four orders old
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj |
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builtbykev
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6dd6f59481 |
Layer 3 Step 6: platoon splits, regressed hard
The highest-value adjuster and the thinnest sample in baseball. The regression is not a refinement here, it is the entire feature: applying raw splits would adjust projections on noise, which is worse than not building it. PHASE 0 — both gates clear, and one was already closed. Splits are a statsapi pull, one call per hitter (statSplits with sitCodes vl,vr). The batter-handedness join that Session 69 recorded as pending is in fact DONE: statcast_aggregates carries bats for 604 of 604 batters, 210 left, 327 right, 67 switch. STATE said pending; the data says otherwise, and the note is corrected. Point-in-time holds as long as the split is fetched before first pitch, since a season split queried this afternoon cannot contain tonight — but a historical backtest would use season-final numbers and leak, so clean measurement is forward-accruing. THE SPINE — regressed = (PA x observed + K x prior) / (PA + K), with K = 600 PA and the prior being the hitter's OWN blended rate rather than the league's. The question a platoon adjustment answers is whether he is DIFFERENT against this hand than he normally is, so his own line is the correct null and a hitter with no evidence of a split correctly gets nothing. K is deliberately conservative: platoon skill is famously slow to stabilise, with the half-signal point for right-handed batters near a thousand PA. THE MAKE-OR-BREAK TEST, both halves. A .310 average against left-handed pitching on 30 PA gets 4.8% weight and moves the projection by 0.003 — essentially nothing, which is the correct answer rather than a limitation. The SAME .310 on 400 PA gets 40% weight and moves it by 0.023, eight times as far. A test asserts that ratio stays above five, so if the regression ever breaks the suite says so instead of the projections quietly drifting onto noise. Real data behaves exactly as the mechanism predicts and is worth recording: Josh Bell hits .259 against lefties and .248 against righties, which looks like a platoon split until the sample speaks — 126 PA earns 17% weight and the adjustment lands at 1.005. Aaron Judge, 76 PA against lefties, comes out at 0.999. Neither is material. Most hitters will get nothing from this adjuster, and that is the honest output, not a failure. Honest-absent has five distinct routes, all returning exactly 1.0: no batter handedness, no pitcher handedness, no splits, a stat platoon says nothing about, and a missing side falling back to the prior rather than to zero. INDEPENDENT of the environment. Park and weather compose into one coefficient because they both describe the stadium; platoon describes this hitter against this pitcher's hand, so it rides its own slot with its own label. Entangling them would make both harder to attribute when the instrument scores them. Directional, mirrored on the under, capped at 15%, and inverted for strikeouts where a higher rate means a higher prop rather than a better hitter. Tests 3729 passed / 300 suites, web build exit 0. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj |
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builtbykev
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9086951852 |
STATE: Session 75 — weather modulation composed onto park; venue gap still open
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj |
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builtbykev
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9f60ceba10 |
Layer 3 Step 5: weather modulation composed onto the park base
Completes the coupled environment: effective = park_base x weather_mod. Weather tilts the park, it never overrides it — a wind-out night at Oracle Park is still Oracle Park. PHASE 0 — both feeds are free and keyless. statsapi /venues gives every park's coordinates in one call; Open-Meteo returns hourly temperature, wind speed and wind direction for those coordinates hours before first pitch, which is when we project. Verified live. THE SPINE — two weather values, two purposes, never crossed. The FORECAST we held at projection time drives the live adjustment AND is what the instrument measures, because it is what we actually knew. It lands on the ledger row beside p_win. The ACTUAL goes only to game_context as raw material for future self-derived weather factors, and is read by nothing that scores a projection. Using the actual to measure tonight would be scoring ourselves on information we did not have. The actual is also pulled from Open-Meteo's ARCHIVE endpoint rather than the forecast endpoint, because asking a forecaster after the fact returns a re-forecast, not what happened. WIND IS PARK-ORIENTATION CONDITIONED. Wind direction is meteorological — the direction it comes FROM — so blowing out to centre means arriving from the opposite bearing. Getting that backwards would invert every wind adjustment in the system, so the 180-degree rotation is commented at the site and pinned by a test on all three cases: straight out, straight in, and crosswind. Centre-field bearings are public geometry, in the same class as the dome list; a park missing from the table gets no wind effect at all rather than a guessed one, and keeps its temperature effect. THREE HONEST DO-NOTHING STATES, all multiplier 1.0, none fabricating an effect. Dome: weather does not apply, and the PARK factor still does — verified that a domed venue keeps its sub-1.0 park base while weather stands down. Forecast absent: none available for this park and time. Sub-threshold: a real forecast below a meaningful bar, because manufacturing a 0.3% nudge on a light breeze is false precision. Weather also says nothing about a strikeout prop and returns not-applicable rather than a neutral it might later be tempted to fill. Conservative and ledger-tunable: every magnitude is an env var, the total is capped at 12%, and nothing here is asserted. This is a nominated challenger that earns its place on the instrument or is cut. Induced at Wrigley, whose centre field bears 32 degrees: wind from 212 at 15 mph computes as 15 mph straight out, weather 1.12 composed with park 1.06 for an effective 1.187 and a +0.043 nudge; the under mirrors exactly; the pitcher's home-runs-allowed prop moves with the hitter's, since both are P(over) on a ball leaving the park. Wind in drops the coefficient to 0.955. A calm 72-degree evening, a dome, and a missing forecast all return 1.0 by three different honest routes, with the park base still applying in each. One correction to the order worth recording: it describes a wind-out night as helping the hitter and hurting "the pitcher there's HR-allowed" as opposite sides. In prop terms both go the same way — the HR-allowed OVER is more likely too. The sign lives in the stat, exactly as established for park factors, and the implementation follows that rather than the phrasing. Migration 036. Tests 3707 passed / 299 suites, web build exit 0. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj |
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builtbykev
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5b4af67d93 |
STATE: Session 74 — public park base pluggable, game-context capture live
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj |
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builtbykev
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f33091ddb8 |
Layer 3 Step 4b: public park base, source-pluggable, plus game-level capture
PHASE 0 — the settle path sees a player's game-log line, not the game. It knows date and teams, never venue or final totals. But the grain is far cheaper than per-prop or even per-game: ONE statsapi schedule call per game DATE returns every game that day with venue, linescore and scoring plays. Fifteen games, one call, verified live. PUBLIC BASE — the ingestion was already done. The static FanGraphs table from Session 15 is the public base; this converts its 100-indexed values into the multipliers the composable architecture wants (Coors 128 becomes 1.28) rather than ingesting a second copy of a number we already hold. It is labelled COMMODITY in the code, not just in a comment. Every resolution carries a provenance record, and the public one reads proprietary: false with the note "Commodity: a public number. Not a VYNDR derivation." The proprietary label exists but belongs only to the self-derived version, and only once it beats this base on the instrument. A surface rendering a park effect can state which it is rather than implying the flattering one. Honest-absent where even the PUBLIC number is thin: a relocated club in a temporary venue gets no factor, because a public number for a park with one season behind it is no more trustworthy than ours would be. SOURCE-PLUGGABLE is the architectural point. resolveParkBase() is the only accessor, public and derived return identical shapes, and callers never branch on source — so when self-derived factors clear their floor they swap into the same slot with nothing downstream to rewrite. A derived source with no factor available returns absent rather than silently falling back to public, because a silent fallback would make a proprietary claim out of a commodity number. GAME-LEVEL CAPTURE starts now because it cannot start retroactively. Game grain, deduped on game_id, never copied onto prop rows — a game's totals belong to the game, and duplicating them per prop is how one fact starts disagreeing with itself. Every field is tied to a named future derivation: venue for park factors, runs for the run environment, HR totals for HR factors. Nothing else is stored. Only Final games are captured, since an in-progress total is not a result, and a game with no scoring plays reports HR as absent rather than zero. HR totals come from scoring plays, which is complete because every home run scores at least the batter. The accrual target is stated rather than promised: 150 home games per venue at roughly 81 per season means about two seasons before a self-derived factor can be nominated, and accrualStatus() reports live progress per venue so the wait is measurable. Induced: Coors home runs +0.061 for the hitter and identically +0.061 for the pitcher's home-runs-allowed at the same park, mirrored on the under; San Francisco negative; Tampa flagged weather-N/A with its factor still applying; the Athletics' temporary venue absent; strikeouts untouched. A real 2025-07-19 capture produced 15 games across 15 venues, 12 with HR totals, zero duplicate game ids. Migration 035. Induce with POST /api/internal/gamectx/:date, progress at /gamectx/accrual. Tests 3688 passed / 298 suites, web build exit 0. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj |
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builtbykev
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63e4bce858 |
STATE: Session 73 — park factors derived + composable; pipeline gap documented
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj |
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builtbykev
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3ac91c3d96 |
Layer 3 Step 4: derived park factors, composable for weather
PHASE 0 GATE — the answer is BOTH, and the important half was already here. A STATIC FanGraphs park-factor table has existed since Session 15 (src/data/parkFactors.js) and computeFeatures already consumes it, so park is not a new idea in this codebase. What was missing is OUR derivation. I nearly built a second source of truth before finding it; the new service lives at src/services/parkFactors.js and the two are deliberately distinct. That discovery changes the point of this order rather than just its scope. If the champion already sees a park factor, adding one to the challenger risks double-counting — which is exactly the redundancy the Session-72 harness exists to catch. So park ships as a NOMINATED CHALLENGER whose job is to be tested for marginal contribution, not as an assumed improvement. Checked and worth noting: the static table reaches computeFeatures but NOT probabilityEstimator, so it does not currently touch p_win at all. DERIVATION, not ingestion. statsapi gives every game with venue, linescore and scoringPlays in one call per date range — and since every home run scores at least the batter, HR totals are fully recoverable from scoring plays. Derived from 5,055 real games across 2022-2025: Coors tops the run environment at 1.099, Dodger Stadium tops home runs at 1.106, Oracle Park and PNC suppress them at 0.923 and 0.917. Eighteen parks cleared the floor, eighteen did not and are honestly absent. COMPOSABLE BY CONSTRUCTION — the architectural point. Park emits a multiplier around 1.0, never an additive nudge, because weather has to modulate it next order: effective = park_base x weather_mod. Additive terms do not compose correctly (a 5% park and an 8% wind are 1.05 x 1.08, not +13%), and the challenger converts the multiplier to log-odds so stacking stays correct. A test multiplies a placeholder weather term onto the park base to prove the shape composes with no rearchitecting. DIRECTIONAL BY PROP-OWNER: home_runs and home_runs_allowed both key off hr_base in the same direction, because the sign lives in the STAT, not the park. Coors inflates the hitter's home run prop and the pitcher's home-runs-allowed prop identically. THREE HONEST STATES, deliberately distinct. Absent (thin sample, adjust nothing), present (adjust), and weather_na for domes — where the park factor STILL APPLIES because a dome has a real run environment, and the flag exists so next order's weather modulation correctly does nothing there. N/A is not absent; conflating them would either drop a valid park factor or apply wind indoors. Structural breaks: a season deviating past the threshold starts a new regime only if the FOLLOWING season confirms it — one odd year is noise, two consecutive years on the same side is a rebuilt park. Only post-break seasons are used, so a humidor or moved wall cannot be diluted by the stadium that preceded it. Factors regress toward neutral by sample size, so a two-season park cannot assert a Coors-sized coefficient, and fine conditioning stays unavailable until its own larger floor. Tests 3669 passed / 297 suites, web build exit 0. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj |
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builtbykev
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beac1816d2 |
STATE: Session 72 — Tier-1 live, Tier-2 harness forward-accrual (no historical OOS)
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj |
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builtbykev
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927e867a23 |
Layer 3 Step 3: Tier-1 mappings live; Tier-2 nomination harness
PHASE 0 GATE — historical out-of-sample testing is NOT available, and the reason matters. statcast_aggregates is overwritten nightly by design (Layer 1 is a full re-pull upsert), so it holds season-TO-DATE numbers with no point-in-time history. Classifying a player for a 15 July game using today's aggregate would feed the model games from 15-21 July — look-ahead leakage, and the resulting "out-of-sample" verdict would be worthless. The harness therefore reads the archetype vector RETAINED at grade time (Session 70's instrument) and runs FORWARD-ACCRUAL, not historical. Reported rather than worked around. CANONICAL NAMES ASSERTED. Every mapping references the axis keys the classifier actually emits, and a test walks both maps against BATTER_AXES / PITCHER_AXES. A key that does not exist would look active and never fire — a mapping that appears wired while silently doing nothing is the exact failure this guards. TIER 1 IS LIVE, tautological and directional: PUNCHOUT/WHIFF raises strikeouts; SINKER/SEAM lowers home runs allowed and FLY BALL/ELEVATOR raises them (a ball on the ground cannot leave the park); SURGEON ARM/PINPOINT lowers walks allowed; SLUGGER/BOMBER raises total bases and home runs; TECHNICIAN/SURGEON raises hits and lowers strikeouts; GRINDER/SNIPER raises walks. Each adjusts only its named stat, mirrors exactly on the under side, and leaves an average player untouched. SPEED IS HONESTLY ABSENT. BURNER/stolen-bases has no axis to key on — SB is a statsapi field that never reached the aggregate store, so Layer 2 shelved it. The mapping is an empty object rather than an invented one. THE TIER-2 HARNESS tests MARGINAL CONTRIBUTION, not correlation. A ground-ball arm obviously correlates with fewer home runs; the question is whether the archetype explains the PROJECTION'S RESIDUAL (outcome minus p_win). If the projection already knows it, the residual carries no signal and the mapping is rejected as redundant — that hurdle is what catches double-counting. The split is by DATE, never random, because rows from one game share a pitcher, a park and a lineup and would leak across a random split. Direction is validated from the held-out data and a contradicted sign is REJECTED, never silently flipped to whatever the data says, which would be fitting noise. LIFECYCLE ENCODED — nominated, live, claimed. A mapping that survives runs live and is measured; only the quantified public claim waits for the ledger. Nothing sits dark. One fixture bug worth recording: my first synthetic generator aliased the carrier selector against the outcome draw and manufactured a 0.038 effect where the generator had put zero. The harness rejected it correctly — it just gave the sign reason instead of the redundancy reason, which is how I found it. The draw now uses a coprime modulus. Real candidate run end to end, GROUND-BALL to hits-allowed: INSUFFICIENT, 0 of 200 settled rows, because no settled row carries p_win yet (Session 70's instrument starts recording at the next new lock). That is the correct verdict and the expected one. Tests 3654 passed / 296 suites, web build exit 0. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj |
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builtbykev
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56fee267c9 |
STATE: Session 71 — challenger deployed; verification gap documented honestly
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj |
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builtbykev
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f2da9dd7e8 |
Layer 3 Step 2: archetype-aware CHALLENGER, measured not claimed
The champion (probabilityEstimator -> p_win) keeps serving and grading users, completely unchanged. The challenger is a second probability computed from the same inputs at the same instant, landing on the same ledger row so it joins to the same outcome and the same close. Identical conditions, one difference — the only clean A/B. NOTHING IS CLAIMED. Running a challenger is honest beta; asserting it is better before the settled ledger says so is not. Promotion stays a later decision gated on Brier and calibration over sufficient segmented volume. INTERPRETABLE, NOT A RE-ESTIMATION. The challenger is the champion's probability adjusted by the Layer-2 axes, applied in log-odds space so a nudge cannot push past 0 or 1 and means the same thing at p=0.5 as at p=0.9. Every deviation is attributable to a named axis and a signed nudge, stored as challenger_adjustments, and the total is capped at 0.45 log-odds — a lean on a real signal, never a re-forecast. Only mechanically obvious stat/axis relationships are mapped; a speculative mapping would be the same guessing this layer exists to replace. IDENTICAL WHERE THERE IS NO SIGNAL, by construction. An unremarkable player, a thin sample, an unmapped stat or a missing classification all return the champion's probability byte-for-byte with an empty adjustment list and a stated reason. The experiment therefore differs only where archetype-awareness could possibly help or hurt, with no dilution from rows the treatment never touched. Induced on real players. Judge home runs over: 0.42 -> 0.447, via BOMBER +0.22 and WHIFF RISK -0.11 — two real opposing signals netting positive. The same prop under mirrors it exactly to -0.027. Judge strikeouts: delta exactly 0, because WHIFF RISK and GRINDER cancel — an honest "no lean" with both signals still recorded. Skubal strikeouts over: 0.60 -> 0.702 via WHIFF, TRAPDOOR and CANNON all aligned; his hits-allowed goes the other way, 0.50 -> 0.392, because a strikeout arm makes hits less likely. Josh Bell and a 12-PA sample are untouched. Isolation is structural: adjust() is pure, the champion field is read and never written, the served snapshot payload is still the untouched champion object, and a challenger failure is caught so it can never break the pipeline it is measured inside. Statcast aggregates load once per snapshot run rather than per prop, so grade-time I/O stays at zero. Migration 034. Tests 3634 passed / 295 suites, web build exit 0. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj |
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builtbykev
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80f7100fc3 |
STATE: Session 70 — measurement instrument wired; the baseline accrues forward
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj |
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builtbykev
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474ebc5d3a |
Fix the close-attach: de-vig raw prices, not a column that does not exist
Caught by inducing on real rows. The first attach ran and marked 642 rows market-unavailable while attaching ZERO closes — because it selected a `fair_prob` column from closing_captures, which has none. That table stores over_odds and under_odds deliberately (Session 64) so the de-vig can run later against the same engine the grade-time fair price uses; asking it for a probability returns nothing and makes every row look closeless. The de-vig now runs here, via devigTwoWay, which is what makes lock and close comparable at all. A one-sided capture yields no fair probability and is correctly not a close. Repair checked rather than assumed: the 642 markings turn out to be CORRECT — every one is a game from before closing capture existed on 2026-07-20, so those rows genuinely have no close and the absence is true. Zero capture-era rows were wrongly marked. The bug would have mis-marked every future row, which is what the fix prevents. Two tests added: the de-vig path with real prices, and a source assertion that the query never again asks closing_captures for a column it does not have. Tests 3616 passed / 294 suites. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj |
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builtbykev
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c5580f333e |
Layer 3 Step 1: wire the measurement instrument
Step 0 found we have been flying without one. p_win lives only in model_snapshots, which has 1,000 rows and ZERO settled outcomes; the closing line lives only in closing_captures, which carries no link to a result; and ledger_entries, the row that actually settles, carries no probability at all. So "is the projection calibrated" and "does it beat the market" have never been answerable — the entire measurable universe was 35 rows recovered by a lossy in-memory join. PHASE 0 — closing coverage verified BEFORE reuse, because an instrument built on a partial close measures a biased subset. closing_captures holds 70,254 rows of which 13,364 are usable, and the 56,890 refusals are candidates we never graded plus one-sided prices — not refusals of our props. Coverage on graded props since capture started is 83/83, 100%. Safe to reuse, with the honest caveat that capture only began 2026-07-20. THE FOUR-TUPLE NOW LANDS ON ONE ROW. ledger_entries gains p_win, fair_prob_lock, archetype_vector and projection_locked_at at LOCK time, and closing_prob plus closing_captured_at from the append-only capture store. The join is the whole point: calibration is p_win against outcome, market-comparison is p_win against the close, and both become plain SQL on one record instead of a join that silently drops 90% of the rows. p_win and the archetype vector are IMMUTABLE — written once at lock via the existing ignoreDuplicates upsert, never re-derived at settle. A re-derivation would measure a projection we never made. The archetype is stored as the VECTOR, not the label. "Did archetype-awareness help?" can only be answered against the axes that were live at grade time, and a single text column cannot express a blend. A grade with no archetype stores null rather than an empty object. HONEST-ABSENT BOTH WAYS. A past game with no usable capture is marked market_unavailable_reason and never given an imputed line; calibration still scores on those rows, only market-comparison is absent. And a game that has not started yet is NOT declared closeless — a close can still arrive, and premature absence is as dishonest as imputation in the other direction. One bug caught before it shipped: the scheduler hook iterated a SPORTS identifier that does not exist in that scope. Inside its try/catch it would have thrown ReferenceError every tick and silently never run — the instrument would have looked wired and captured nothing. Now iterates cadence.ALL_SPORTS. The baseline accrues FORWARD. Historical p_win and closes are gone, discarded before this existed. Calibration and market-comparison stay honest-absent until volume accrues. Tests 3614 passed / 294 suites, web build exit 0. Migration 033 applied. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj |
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builtbykev
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063e9fb3f7 |
STATE: Session 69 — multi-axis archetypes live, FLEX fabrication deleted
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj |
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builtbykev
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7ac6aa73e3 |
Layer 2: multi-axis archetype classifier; the FLEX fallback is gone
A player is a blend across independent axes, not one label. Skubal is a STARTER and a strikeout arm and a ground-ball arm and a control arm — four true things at once, and single-label classification threw three of them away. AXIS INDEPENDENCE WAS MEASURED, NOT ASSUMED. Correlations over the live store (467 batters, 531 pitchers); anything |r| >= 0.70 is one underlying trait and was collapsed so we never show one trait as two archetypes. Batter k% ~ whiff% +0.89, hard-hit% ~ exit velo +0.88, chase% ~ swing% +0.87, chase% ~ bb% -0.72; pitcher k% ~ whiff% +0.76, gb% ~ fb% -0.73 — all collapsed. The survivors are genuinely orthogonal, and one result is worth stating: pitcher velocity correlates +0.14 with K%, +0.07 with whiff% and +0.07 with GB%. Velocity is NOT a proxy for missing bats — a hard thrower who misses no bats is a real distinct type, so CANNON earns its own axis rather than being folded into STRIKEOUT. Pitcher K% ~ GB% is -0.10, so PUNCHOUT and SINKER are independent, which is exactly the multi-axis thesis. Cut-lines are the measured p75 (distinctive) and p90 (elite), per role where the tails differ even when the medians agree: reliever GB% p90 is 54.1 against a starter's 48.9, both with a median of 42.5. THE FALLBACK IS DELETED. classify() used to return FLEX (mlb) / SHIELD (wnba) / CONNECTOR (nba) at weight 1.0 when nothing scored — "could not classify" rendered as a fully-confident classification of a real archetype, with descriptive education copy attached. 8 of 18 MLB players carried it, and FLEX could never be earned because its only scoring input had zero writers. Every sport now does what MMA already did: unclassified is absent. Induced on real players. Skubal: STARTER, throws L, WHIFF + SEAM + PINPOINT, all elite. Judge: BOMBER + GRINDER + WHIFF RISK — elite power, patient, strikes out, three true things. Kwan: SURGEON + SNIPER + SLASH with NO power claimed (0.4 barrel% is absent, not "low power"). Josh Bell, who used to classify as DRIVER: empty blend, "No standout profile — league-average across every measured axis." Alan Roden, who was FLEX at weight 1.0 on 21 PA: every axis absent, "Not enough plate appearances yet — no profile claimed." Per-axis honest-absence holds: a velo-less pitcher keeps every other axis, and NO DATA is distinguishable from LEAGUE-AVERAGE rather than collapsing into one shrug. The full vector is stored for Layer 3; only the top three distinctive traits surface. Three existing tests asserted the fallback and were updated to assert absence. One of them surfaced a real robustness gap: classify(sport, null) threw, because an explicit null does not trigger a default parameter and every scorer dereferences its argument. Guarded. Every baseball name is accounted for in docs/ARCHETYPE-AXES.md — built, alias, tier, or shelved with its unlock condition. Zero orphans; cross-sport names left for their sport. Tests 3601 passed / 293 suites. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj |
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builtbykev
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1265c23305 |
Tier-A joins: handedness, true role, and the velo fix
Three Layer-2 prerequisites, each one free call. HANDEDNESS — statsapi /sports/1/players carries batSide, pitchHand AND primaryPosition for every player: 1,316/1,316 in the live probe. Batter handedness was 100% absent, which made every platoon or switch-flavour archetype unbuildable; it is now populated from the same call that gives pitchers theirs, with statsapi as the authority and the movement feed as the fallback. ROLE — statsapi season pitching with playerPool=ALL returns 751 rows (the default returns only the ~57 qualified). Real usage: gamesStarted, gamesPitched, gamesFinished, saves, holds. roleDetail derives starter/closer/setup/reliever from that instead of the season-IP proxy, which drifts all year as innings accumulate and left 32 pitchers in a 60-80 IP trough. VELO — recovered from 53% to 99% (721/729 pitchers). The movement feed carries only each pitcher's PRIMARY pitch, so matching by position could never do better than one pitch each. The wide pitch-arsenals feed has one column per pitch type, matched BY TYPE: Skubal now has velo on all 5 of his pitches. Velo archetypes are therefore buildable rather than shelved. Migration 032 applied. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj |
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builtbykev
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27aabd078f |
STATE: Session 68 — Layer 1 mechanism data live (1,354 rows, 100% join)
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj |
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builtbykev
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a49959867d |
Statcast: take the full arsenal, not each pitcher's primary pitch
Caught by spot-checking a real row after the backfill landed: Skubal stored with one pitch. The pitch-movement endpoint with an empty pitch_type returns ONE row per pitcher — their primary offering — so 677 rows for ~700 pitchers, and a five-pitch arsenal was being recorded as a one-pitch one. Not a fabrication, but a silent under-representation of the single most important pitcher-mechanism field, which is worse than useless for Layer 2: it would have classified every pitcher as a one-pitch arm. Mix now comes from pitch-arsenal-stats (3,205 rows = pitcher x pitch type) carrying usage%, whiff%, K%, put-away% and run value per 100 for every pitch. Movement still supplies velo, break and handedness, folded onto the primary pitch; a pitcher present only in the movement feed keeps his handedness and his one measured pitch rather than being dropped. Velo on non-primary pitches is null — absent, not guessed. Skubal now stores 5 pitches, throws L, FF first by usage with velo 96.7. Tests 3583 passed / 292 suites. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj |
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builtbykev
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a011ae79fe |
Statcast: role belongs in the key (two-way players)
Found by inducing the real job on the server, not by review: the first chunk wrote, the second failed with 'ON CONFLICT DO UPDATE command cannot affect row a second time'. A player can legitimately appear in BOTH the batter and the pitcher feeds — two-way players, position players who pitch, pitchers who bat — so (sport, season, source_id) collapsed two real profiles into one key and a single batch hit the same row twice. Ohtani has a real batter profile and a real pitcher profile. Merging them would invent one player out of two genuinely different sets of measurements, so role goes in the primary key rather than one profile winning. Migration 031 applied; conflict target updated; a two-way case is now a test. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj |
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builtbykev
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528cb1a6d0 |
Layer 1: Statcast mechanism-data ingestion (backfill + nightly refresh)
The data foundation for the archetype and projection layers, built as the pattern every sport inherits. Layers 2 and 3 are not touched. PHASE 0 GATE — both match rates measured live, both 100%. Batters 40/40; PITCHERS 66/66 across five real rosters (CLE, DET, MIN, NYY, LAD) joined by MLBAM id against the 713-pitcher Savant feed. Zero honest-absent on identity, because the join is an integer both systems use natively — and the snapshot pipeline already stores it per graded row. SOURCE — five Baseball Savant CSV leaderboards, free and public, pulled with axios and the CSV parser savantAdapter already runs in prod. pybaseball is deliberately NOT used: it is an MIT wrapper over these same URLs, and adding it would reintroduce a Python runtime in a stack where the existing Python service is already offline. min=1 on every feed, not Savant's default min=q, so the long tail arrives and OUR minimum-sample gate decides what is thin — explicit and testable rather than silently dropped upstream. Measured: 1,354 rows per season (604 batters, 750 pitchers), all five feeds in about five seconds. Pitcher mechanism includes arm angle, GB/FB/LD, chase and whiff; batters get exit velo, launch angle, barrel and hard-hit, chase and z-swing. Handedness rides in free on the movement feed (677 pitchers); batter handedness stays absent pending a roster join rather than being guessed. BACKFILL AND REFRESH ARE THE SAME CALL — a full re-pull upserted on (sport, season, source_id). Idempotent and self-healing: a missed night self-corrects on the next run, with no incremental who-played bookkeeping to drift out of sync. At 1,354 rows the simple thing is also the robust one. HONESTY RULES, each with a test: a metric the feed did not carry is null and never 0; a thin sample is STORED and flagged rather than dropped or inflated, because thin and missing are different claims; an unjoined player is stored with a null player_key and joins later; and if every feed comes back empty the job REFUSES to write, so a bad night can never blank a good table. Freshness is treated as a truth property. updated_at on every row, and the scheduler pages on a failed run AND on silent staleness — a job that stops being scheduled never produces a failure, so staleness has to alarm on its own. Never-built is deliberately not stale: different condition, different fix, and paging on a fresh install teaches the operator to ignore the alarm. Nightly at STATCAST_HOUR_UTC (default 11 UTC, after every game is final), kill switch STATCAST=0, and induce-able at POST /api/internal/statcast/refresh with a freshness probe at /statcast/status — we verify a refresh by running it, not by waiting for the slot. Migration 030 applied. Promoted columns for the classification-critical metrics plus a metrics JSONB carrying every raw field, so Layer 2 can reach something we did not promote without a re-ingest. Raw per-pitch stays out of Postgres on purpose: one season is ~0.85 GB against a 500 MB plan ceiling, and it is re-pullable from the free source if Layer 3 ever needs it. Pattern documented in docs/MECHANISM-DATA.md for NBA tracking and NFL Next Gen. Tests 3581 passed / 292 suites, web build exit 0. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj |
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builtbykev
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0264486bf9 |
STATE: Session 67 — price layer gated at two doors, read card wired
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj |
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builtbykev
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4e2f488341 |
Forward model_price_locked to the hero — a paywall was wearing poison's copy
Live induction on the deployed landing page caught this; markup review and the unit suite both passed it. With the model leg stripped for anonymous visitors, LiveHeroProp forwarded book/fair/model/ev/quarantine to PriceTriplet but NOT model_price_locked, so deriveValueState fell through to the missing-model-price branch and the card rendered "MODEL READ WITHHELD" — the quarantine state, whose copy says we suppressed our own price because a leg is poisoned. Nothing was poisoned. The real reason was the paywall, and the two must never share a face: one says our data is untrustworthy, the other says you don't have this tier. Now forwarded, with a test asserting both the separation in deriveValueState and the forwarding at the call site. Tests 3559 passed / 291 suites, web build exit 0. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj |
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builtbykev
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aaa41134d4 |
Close the second leak path: /api/hero-prop bypassed the snapshot gate
The landing hero reads the snapshot from Redis DIRECTLY via heroPropService, so it never passed through routes/snapshot.js and was still serving model_odds, ev_pct, value and takeable to anonymous visitors after the first fix. Same strip, same tier resolution, same private-cache rule for authenticated callers; the Next proxy now forwards the bearer token. PRODUCT CONSEQUENCE, FLAGGED RATHER THAN BURIED: the landing hero is served to anonymous visitors, so it now renders BOOK and FAIR with the model leg LOCKED instead of the full triplet it showed this morning. That follows the stated free-tier rule exactly, but it does trade a strong marketing moment (VALUE +21.1% VS FAIR on the shop window) for consistency of the gate. Reversing is one line — add 'model_price' to the free tier in src/config/tiers.js, or special-case the hero route — and is a product call, not a correctness one. Tests 3557 passed / 291 suites, web build exit 0. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj |
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builtbykev
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fbcb00b7b1 |
Close the public model-price leak; wire the read card's price layer
PHASE 0.5 GATE — the three checks, and one correction.
`fairLine` does not exist. Zero hits across src/ and web/src. Option A as
written had no referent, but it resolves better than feared: `fair_odds` is
already a real de-vigged American price on every graded snapshot row, so there
is nothing to derive.
Gate 1 (is it a price): PASS. fair_odds is American odds from
impliedProbToAmerican inside devigTwoWay; fair_prob is the probability. Both
distinct from `line`, the stat threshold.
Gate 2 (numeric match): PASS, 8/8 exact. Recomputed fair_odds and fair_prob
independently from the stored raw over/under prices; every value matched the
stored one to the integer and to 3dp. Same de-vig, same numbers the component
was proven against.
Gate 3 (poison independence): PASS, and proven on the quarantined cohort
itself. devigTwoWay's inputs are (over_odds, under_odds) — market prices
only, no model term is reachable. The 8 rows recomputed above are all
wrong_opponent_grade rows, and their fair prices reproduce exactly from the
market. The poison is in the grade, not the price. Quarantine therefore
suppresses the MODEL leg only; the fair leg stands, as designed.
THE LEAK WAS REAL AND ALREADY LIVE. GET /api/snapshot/:sport is public and
unauthenticated, and it was serving model_odds, p_win, ev_pct, value and
takeable to anonymous callers on every graded row — 25 of 25 on the live wnba
board. The Session-66 gate on /api/analyze was bypassed entirely by this
endpoint.
The strip covers more than model_odds, because model_odds is not the only way
to read the model price: p_win IS the price in another base, and ev_pct is
INVERTIBLE — ev is a function of p_win and book_odds, and book_odds is public,
so leaving ev behind hands the price over. All five model-derived fields go.
book_odds, fair_odds, fair_prob, overround and devig_method stay on every tier:
the fair leg is never the paywall. Rows that keep a book+fair pair are stamped
model_price_locked so a gated price is never mistaken for a missing one.
Tier comes from resolveTierFromRequest, which reads a bearer token when one is
present and otherwise returns 'free'. It FAILS CLOSED on every error path, so a
resolution failure can only ever withhold the price. The response now varies by
entitlement, so the /:sport handler downgrades Cache-Control to private for
authenticated callers and the browser proxy forwards the bearer token —
otherwise a CDN could hand a paid payload to an anonymous viewer, or every
request would look anonymous and paid users would lose the leg.
READ CARD — a manual scan carries no market. The request is {player, stat,
line, direction}, so the engine has no over/under prices to de-vig and
book_odds/fair_odds are legitimately absent from its response; that is why the
triplet was hidden there. lookupSnapshotPrices recovers them from the
pre-graded snapshot via the same cache-only read this route already performs
for locked odds and team. The join is exact on player + stat + line + side
(fair_odds is side-specific), and returns nothing unless book and fair are BOTH
present — a user-chosen line the board never graded has no market attached, so
the triplet stays hidden rather than borrowing another line's price.
FAIR-LEG ABSENCE, measured before shipping: 636 graded rows, 636 with book,
636 with fair, 0 one-sided. Absence rate 0.0%. The hero number is not a
sometimes-number on current data.
Tests 3556 passed / 291 suites, web build exit 0.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj
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