a8de6767564836d494d85ba89c76d9eedccaf2a0
21 Commits
| Author | SHA1 | Message | Date | |
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 builtbykev
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a8de676756 |
A probability is served because evidence supports it, not because nothing else answered
The band gate was blocked for its `else` branch. It read:
candidate = F(raw)
served = inCertifiedBand(candidate) ? candidate : RAW
and above raw 0.60 the model is measured overconfident — holdout raw 0.80-0.90
predicts 0.843 and realizes 0.639. So "the calibrator is not supported here" was
being answered with a number already proven wrong. Unsupported calibration does
not make raw true.
Four candidates were adjudicated on ONE split — fit on the earliest 60% of
train, decide support on the last 40%, evaluate on a holdout that saw neither:
A low-param 80.2% coverage 0.24374 REFUTED — its extra region
(raw 0.80-0.90) certified on cert (err +0.040, n=55) and
refuted on holdout (served 0.754 vs observed 0.639), and it
leaves a hole at 0.70-0.80 while serving the island above it
B isotonic 91.3% coverage 0.24337 CERTIFIED, contiguous raw [0.50,0.80)
C empirical band 91.3% coverage 0.24335 REFUTED — refitted point-in-time on
current-model hits the realized rates INVERT in grade order
(B+ 0.593 < B 0.614 < C+ 0.623), so the served function steps
down at raw 0.78. Its shipped constants come from 3,417 props
pooled across four batter stats and do not reproduce here
D raw identity 43.1% coverage 0.24866 certifies raw 0.50-0.60 and only there
Raw is candidate D, not a fallback. It earns exactly one region (holdout error
+0.010 on n=1,316), which is why the law is "raw must earn its region" rather
than "raw is never true". B already covers that region, so no hybrid is built.
Above raw 0.80 nothing is certified and nothing is served. That is the region
where raw is most wrong, isotonic over-corrects (cert err -0.093) and its LODO
mapping at 0.95 has spread 0.180. 8.7% of holdout rows land there.
The registry did not need changing. `serves(stat, p)` already tested certified
bands against the RAW p_win — support in the input domain, the correct question —
and returned {serve:false, reason}. It never said "serve raw". The output-space
gate and the raw fallback were both invented downstream in calibrationService.
ACTIVATION IS OFF. PROBABILITY_CONTRACT_SHADOW defaults to 0, CALIBRATION_DEPLOYED
stays frozen empty, and every served field is byte-identical. This releases the
support first, which is the required order. The shadow records raw belief, the
candidate served value, the state, the estimator identity, and what EV/Kelly/VALUE
would be under the actionability law — into its own column, read by nothing.
Migration 051 was applied to production BEFORE retentionService named the column.
PostgREST builds a bulk insert from the first row's shape, so a key whose column
does not exist 400s the whole batch silently — that is how migration 038 took
retention down for three days.
The user-facing contradiction is NOT fixed here. A B+ still says "realized about
66%" beside a confidence of 84. Fixing that is activation, and activation costs
32% of VALUE flags and 46% of Kelly recommendations on the holdout.
Suite 401/401, 5,580 passed, 4 skipped, deterministic across three runs.
Teeth 23/23, each independently injected and restored byte-identically.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CQJeAG8vcDoL5zkiaJyVb8
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builtbykev
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7efb04e280 |
Lineage family lookup: bound it to a slate, and say what an action is
TWO DEFECTS, one lookup. SCALE. The family lookup sent 100 natural keys as a PostgREST IN-list. `read_natural_key` has NO pg_stats row at all -- the table's last autoanalyze (2026-08-26) predates the column ever being populated -- so the planner used a default per-value selectivity, estimated 172,409 rows and chose a sequential scan of 344,818: 8.5s, then 57014. At 50 keys the same shape returned in ~357ms. The cliff is a statistics artifact, not a volume one, which is why the repair does not depend on the estimate improving and is not CH=50. `readNaturalKey` builds `sport|game_date|player_key|stat|side|line[|#event]`, so SPORT AND GAME_DATE ARE COMPONENTS OF THE KEY. Two rows sharing a key necessarily share both, and scoping the lookup to the (sport, game_date) pairs present in the requested keys is LOSSLESS BY CONSTRUCTION. One index-backed range per date, walked with safePaginate; cost is bounded by ONE SLATE however long the chronology gets. Measured: 5,000 keys -> 1 scope, and the plan is `Index Scan using model_snapshots_lineage_family_idx, cost 0.28..1.92`. VALIDITY. A row carrying `read_natural_key` is not history: the key is stamped on every candidate BEFORE the lookup, so a failure leaves it on a row that never became an action. Proven this was not cosmetic -- fed the raw rows the old lookup returned, the resolver produced a REVISION with a NULL read_id (an orphaned chain node) and labelled a brand-new Read LEGACY_UNVERIFIED. `isValidLineageAction` states what a completed action IS: all nine fields, in the query and again in code. ATOMICITY. A failed attempt now leaves NO lineage-specific state. `publication_id`/`published_at` are untouched -- the slate really was published, and erasing a true fact to tidy a false one is the wrong repair. Replayed the exact failed 19:00Z cohort through the real resolver, side-effect free: 119 NEW / 379 CHANGED / 621 UNCHANGED -> ORIGIN 119 / REVISION 379 / RECAPTURE 621, 0 wrong parent, 0 wrong ordinal, 0 null read_id, 0 forks -- byte-identical with all 1,119 failed partial rows present. Clean-head parity 1,024/1,024. Migration 050 is CONCURRENTLY + IF NOT EXISTS, drops nothing, rewrites nothing. Lineage stays OFF. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01CQJeAG8vcDoL5zkiaJyVb8 |
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builtbykev
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048e4eaa3f |
Event-aware retention identity: two games, two receipts
One player prop in Game 1 and the same-looking prop in Game 2 are two different
historical claims. The retention conflict identity did not know that.
SEMANTIC IDENTITY FIRST. Two outbound rows are the same retention proposition
within one cycle when they share the cycle, the EVENT, the participant, the
stat, the line and the side. Book is deliberately absent — collapsing books is
dedupeProps's actual job and the price anchor is chosen later. The database
index is enforcement of that answer, never the definition of it.
THE EVENT COMPONENT NEVER FABRICATES. canonical_event_id where a sport has a
resolver — MLB's admission gate rejects unresolved/ambiguous/contradicted props
BEFORE grading, so every row that can reach retention has one — and game_id
otherwise, which is NOT NULL in the schema and is the only event label sports
without a resolver possess. Both are in the identity, so the weaker label still
discriminates where the stronger is absent.
NULLS NOT DISTINCT IS LOAD-BEARING, NOT STYLISTIC. canonical_event_id is NULL
for every non-MLB row. Measured on a disposable PG17: under PostgreSQL's default
semantics the same NBA proposition inserted twice produced TWO rows — every
retry duplicating for ever. With NULLS NOT DISTINCT the same test yields one.
That measurement is what rejected the plain composite option.
MIXED-FLEET BRIDGE. A rollout serves both builds at once (measured 11/12 new,
1 old). Old and new writers need different indexes and NO schema state satisfies
both: with the legacy index present a new writer fails 23505 on a doubleheader;
with it gone an old writer fails 42P10. A bare ON CONFLICT DO NOTHING would have
bridged this, and PostgREST does not emit one — `ignoreDuplicates` WITHOUT
`onConflict` was measured raising a real duplicate-key error, so that bridge does
not exist through this client.
So the writer bridges it. It targets the event-aware identity and, on exactly
the two errors meaning "the schema is not in the state I expect" (42P10, or
23505 NAMING the legacy index), retries the SAME chunk on the legacy target. A
failed chunk rolls back atomically — measured 0 rows — so the retry cannot
double-write. Correct in every schema state: legacy-only and both-present
degrade to legacy semantics with no outage; new-only keeps both games.
The bridge is deliberately narrow. A supersedes conflict is ALSO a 23505, and
swallowing it would destroy the forked-history guard, so the legacy index must
be named. All three model_snapshots writers (persist, commitPublication,
recoverFromFork) go through it; no hardcoded legacy target survives.
MEASURED, through the real supabase-js -> PostgREST -> Postgres path on
production-shaped PG17:
* 1,000 REAL propositions from the verified 2026-08-17 STL@CIN doubleheader
(1,738 retained rows under ONE game_id), replayed across both real gamePks:
OLD index materialized 1,000 of 2,000 — 1,000 LOST. NEW index materialized
2,000 of 2,000 — 0 lost.
* retry idempotency, over/under, line, stat, player, non-MLB same-game and
non-MLB different-game all behave correctly under the new index.
* ORDINARY-SLATE PARITY over ALL 434 real cohorts / 328,262 retained rows:
old identities 328,262, new identities 328,262, delta 0, cohorts changed 0.
The index is therefore guaranteed creatable and nothing historical splits.
CONFLICT_IDENTITY is now DERIVED from RETENTION_CONFLICT rather than restated —
a test caught them silently disagreeing, which is exactly how the materialization
check could have expected an identity the database no longer enforced.
EXPAND/CONTRACT are separate files on purpose. 048 is additive and retires
nothing; 049 drops the legacy index and must not be applied until fleet
convergence is proven by sampling, never assumed from a fast rollout.
NO BACKFILL. Legacy rows keep NULL canonical_event_id and remain LEGACY
EVENT-AGNOSTIC RETENTION, which is what that NULL truthfully says.
The materialization defence is untouched and now reports the bridge honestly:
while the legacy index still collapses a doubleheader, expected 4 vs actual 2
yields MATERIALIZATION_MISSING and the cohort is refused.
Nine teeth, injections verified present, against a green baseline of 97:
1 event distinction removed (10) · 2 phases collapsed (2) · 3 bridge swallows
everything (6) · 4 NULLS NOT DISTINCT removed (1) · 5 old-container error as
success (3) · 6 semantic/DB identity disagree (8) · 7 collision detector removed
(2) · 8 partial transport usable (3) · 9 collision unannounced (1).
Restored byte-identically.
Model and product untouched: gradeSlateService (event-aware dedupe), event
identity, ledger, calibration, chain, lineage config and the status route all
UNCHANGED. Zero cacheSet changes, zero web paths, schema contract unchanged (no
new columns). Lineage stays OFF.
385 suites / 5,178 tests pass. web tsc exit 0.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CQJeAG8vcDoL5zkiaJyVb8
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builtbykev
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352016790a |
MLB canonical event identity, impossible-binding refusal, event-aware dedupe, publication commit
Release-isolated slice built from
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builtbykev
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6c34af3414 |
checkpoint: chain shadow, WNBA possession feed, baseball chain
Backup commit of uncommitted working-tree state found during Legion recon (Tony resurrection, STEP 0). This work existed only on the laptop disk. - chain shadow accrual + probe script (038_chain_shadow.sql) - WNBA possession feed: ESPN adapter, usage service, verify script (039_wnba_player_game.sql) - baseball chain - retention/snapshot service updates, tableKeys, matchupKeys - specs: chain-v1, wnba-possession-feed, wnba-source-survey - unit tests for the above Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01QnvJAkC3h5QGmb6dipoiWn |
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builtbykev
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f61ec6b391 |
Read integrity, as-of context, and the shadow matchup resolve (A1-A7)
Seven orders of measurement-first repair. The served grade does not move. A0/A1 — the unordered page walk returned the right COUNT and the wrong ROWS: 410-617 of 2,490 duplicated with an equal number never returned, while rows.length matched the server exactly. safePaginate orders on a real unique key, verifies the tuple at runtime, and THROWS on a query error instead of treating it as end-of-data. Both hits PROVES are withdrawn: they were drawn through that reader, and defense_by_direction's distinct-n was likely below the gate floor all along. A2/A2b — rolled across every reader: 11 FAIL -> 0. Composite keys pulled from pg_index (the context tables are dated-composite and had no single unique column). The unordered helper is deleted, not parked. A3 — ledgerService and retentionService defaulted the SAME env var to DIFFERENT versions, so no ledger row ever carried the marker eligibility requires. One source now. model_snapshots settlement moved onto the cron: 15,484 -> 28,894 settled, repaired-champion 0 -> 7,556. A4 — hitsFactorContext takes an as-of cutoff. Refusal over reconstruction: no row at-or-before the date means the factor does not apply, never the nearest row. Live path unchanged, proven 400/400 on real rows. A5 — factor_inputs freezes what the factor READ, never the multiplier, so an audit can recompute and check. It also recorded the finding: the three hits factors have NEVER fired. prop.opponent and prop.opposing_pitcher are read by the resolver and written by nothing. A6/A7 — matchupKeys resolves those keys from the posted lineup plus the schedule's probable pitchers, and fires the factors into a SHADOW freeze: 248 fires on 308 props, 245 of which would move the grade. The served forecast is untouched. specs/a8-shadow-factor-gate.md pre-registers the test that decides whether they ever go live. Nothing is turned on. CALIBRATION_DEPLOYED stays []. Both verdicts stay withdrawn. 4,772 tests / 371 suites green, web build exit 0, read-integrity harness 34/34. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> |
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builtbykev
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7c6fd95e68 |
Build 2 Phase A: real founder cap — atomic claim, race PROVEN, flags collapsed
DB only. No Stripe call, no checkout/webhook rewire (Phase B). Migrations 035,
036, 037 applied to prod and tracked; repo files added.
035 SCHEMA TRUTH — user_profiles gains stripe_customer_id and
stripe_subscription_id (G3 proved the webhook stores neither today, yet
finalize and grandfather reconciliation both key off the subscription id), plus
a partial unique index so a subscription id resolves to exactly one profile.
036 THE MECHANISM — founder_slots is a real TABLE replacing the decorative view.
The claim is a single UPDATE whose target row is chosen FOR UPDATE SKIP LOCKED;
no count is read in the decision path. UNIQUE(slot_number) plus a PARTIAL
UNIQUE(user_id) WHERE status <> 'free' (one live slot per user). Seeded 100 free.
Q1 global pool: the slot travels with the user, so analyst->desk keeps founder
with no second claim. Q2: release_expired_slots handles TTL abandonment ONLY —
cancelled slots retire, so the counter only rises. A6 redirects
founder_pricing_seats to count claimed slots, capped 100.
PRICE IDS ARE NOT IN SQL. claim_founder_slot returns a price KEY
(analyst_founder / analyst_standing / desk_founder / desk_standing) and the Node
layer maps it to STRIPE_PRICE_* env with a boot assertion — adopted over
hardcoding so a typo fails at boot instead of becoming a permanent mis-charge.
A7 FLAG COLLAPSE — finalize_founder_slot is now the SINGLE writer of both
founder flags in ONE transaction: user_profiles.founder_pricing is canonical and
users.founder_status mirrors it. founder_status is NOT dropped (G5 proved it
live: written at stripeService:163, served at routes/stripe:95, loaded in
middleware/auth:24 PROFILE_COLUMNS). Only the independent write is retired —
the two flags had already drifted in prod (1 vs 0).
A9 RACE TEST, run in Supabase before any Stripe:
- pool squeezed to ONE free slot; three distinct users claimed concurrently
-> EXACTLY ONE is_founder=true on slot 100, two returned analyst_standing,
zero double-allocation.
- idempotency: the winner claiming again returned the SAME slot 100 and still
held exactly 1 live slot (two tabs cannot take two seats).
- constraint layer proven directly: a raw UPDATE granting that user a SECOND
live slot was REJECTED by the partial unique index, and verify-after-write
confirmed state unchanged (1 live slot, target row untouched).
HONEST LIMIT: the three claims contend within one transaction via LATERAL, so
this proves the claim logic, the SKIP LOCKED path and the constraint that makes
parallel safe — but it is not N genuinely parallel backend sessions. True
multi-session concurrency is not drivable through this SQL interface and should
be exercised once in Phase B against the test key.
037 NEXAPAY DROP — own migration, evidence-led (G4: zero code refs, column
empty). VYNDR is Stripe-only.
CLEAN BASELINE (Q3) verified after the test: 100 free slots, 0 non-free, counter
0/100, and BOTH founder flags cleared to 0 across user_profiles and users — the
inconsistent test record is no longer enshrined as a founder.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01QJs13VsyiSKYQP6rj3NNmc
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builtbykev
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2bfaeff572 |
Ledger takeable tagging (deferred C2); efficiency challenger BLOCKED
Champion grade UNCHANGED. Push scoring untouched. Additive tags only — nothing
deleted, nothing re-settled.
PART A — THE EFFICIENCY CHALLENGER: BLOCKED, NOT BUILT.
Review Zero came back ABSENT on all three inputs:
0.1 efficiency scores DO NOT EXIST (zero occurrences of market_efficiency /
marketEfficiency / efficiency_score in src/ or web/src/).
0.2 base thresholds DO NOT EXIST (engine1.js has zero `edge` references — the
grade is not an edge-vs-threshold comparison; grade_thresholds.json holds
PROBABILITY bands).
0.3 the +/-0.05 additive efficiency nudge DOES NOT EXIST. The only 0.05s on
the grade path are featureCache.teammate_absence_bump, a bvp_advantage
cutoff, and p*0.9+0.05 inside probabilityEstimator (the 0.5*0.1 term of
the shrink-toward-0.5). There is no additive scaling to replace.
So a challenger differing from the champion in EXACTLY ONE thing cannot be
constructed: there is no additive scaling to swap, no base threshold to
multiply, and engine1.js has zero `sport` references so market cannot reach the
grade. A threshold must exist first — that is R1 of
specs/full-output-grade-mapping.md, an explicitly held separate order. Shipping
R1+R4 together would make the Phase-3 delta report misleading: the re-letter
would be driven mostly by switching to probability grading while being
presented as the efficiency fix.
0.4 coverage: the spec names 5 scores; the live ledger has 11 markets and only
MLB total_bases maps to one. 9 of 11 have no score, so "all scored markets"
cannot be satisfied without inventing 9 numbers.
PART B — LEDGER TAKEABLE TAGGING: BUILT (the deferred C2).
New src/config/takeableStandard.js: floor on the minus side, UNCAPPED plus.
Deliberately NOT valueEngine.isTakeable (the -160..+200 PROMOTION band) — a
+400 prop is not promotable but IS takeable; a test asserts the two diverge on
the plus side and agree at the floor so they can never quietly merge. Absent
price returns null, never false (Number(null) === 0 would tag a missing price
takeable). The floor is POLICY not derived (C1 could not derive one) and is
labelled so; each row records takeable_floor so a re-derivation can re-tag.
Migration 034 (applied + tracked): ledger_entries.takeable boolean +
takeable_floor numeric, nullable, partial index. Forward tagging in
ledgerService at row build; backfill in one statement.
Result: 1254 rows, 1246 tagged (781 takeable / 465 below floor), 8 NULL with
null_despite_price = 0 (the NULLs are genuinely priceless rows). Settled 1163
and graded 1254 unchanged.
PART C — the model-version boundary tag is DELIBERATELY NOT APPLIED: no scaling
change shipped, so no boundary exists, and stamping one would mark a model
transition that never happened. modelEras.js is its home when a real one lands.
Floor: 312 suites / 3890 tests green (8 new), web build exit 0.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01QJs13VsyiSKYQP6rj3NNmc
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builtbykev
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c7067c80c4 |
Persist lock-time multi-book lines to lock_lines (unblocks the staleness audit)
The over-side skew audit's confirming check — was our locked line stale-high vs consensus AT LOCK — was BLOCKED because multi-book lines at lock were never persisted (bookprices is Redis current-only). This persists them. - migration 033: lock_lines table (tracked + applied to prod). One row per (graded prop × book) with both odds + a lock timestamp. RLS enabled, NO policies -> service-role only (fence). UNIQUE key -> idempotent re-runs. - lockLineCapture.js: buildLockRows (pure, graded-props only, honest-absent single-book) + idempotent upsert persist. Built from the in-memory props at the LOCK moment (ts) -> no Redis re-read, no TTL race. - snapshotService: persist right after `enriched` (the lock moment; gradedAt uses the same ts). Best-effort + fenced. FENCE (measurement-only): lock_lines is read by NOTHING on the grade path (gradeSlateService, snapshot dedup/indexOdds, challengers, selector, ledger) — a grep test asserts it, and RLS locks it to the service role. Grade byte- identical proven: runSnapshot grades are identical with persist on/off (test). Volume ~1.5-3k rows/day (graded props x books x 5 snapshots); weeks retained, no pruning needed short-term. Does NOT retroactively fix the existing 62 rows — future accrual only; confirmation still needs weeks of settled rows. Full suite 3842 green, web build exit 0. No grade/locked_odds/outcome/served surface changed. 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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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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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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d3ffa1b8c2 |
Retention: model_snapshots live + base64 SSH key support
RETENTION (Phase 2, priority zero). History starts compounding tonight. migration 025 model_snapshots — APPLIED to prod. Append-only, one row per graded prop PER SIDE PER CYCLE, with a unique index on (snapshot_id, player_key, stat, line, side) so a retried cycle cannot duplicate. RLS on, service-role writes only. What it captures that the ledger never did: - features jsonb — the model's INPUTS. Without these a backtest can only grade our own homework; with them any future model can be replayed against the exact conditions this one faced. - REFUSALS (refused + refusal_reason). The ledger drops them, so a gate refusing props that would have WON is invisible — unmeasurable lost edge. Captured via a new onGraded hook in gradeSlateService that fires with BOTH sides before any filtering. - grade_11, the pre-collapse grade. The 4-letter map throws away the entire live C-/C/C+/B- range. - model_version + code_sha on every row. ledger_entries mixes pre/post-fix grades with no marker and cannot be separated retroactively. - p_win / ev_pct / fair_odds / takeable / value — none of which any permanent store held. Wiring: analyzeViaEngine1 attaches _features/_grade_11 (underscore = internal); gradeSlateService fires onGraded then STRIPS them so they never reach a cache or API payload; snapshotService builds rows and persists best-effort. Retention reuses the LEDGER's dateET/gameIdFor helpers so rows share the ledger's natural key exactly — otherwise the settle pass could never join outcomes onto them. Rows are written BEFORE the empty- slate early return: a slate that refused everything is exactly the case worth recording. CONTRACT HELD: retention is injectable and every path is caught. persist() returns errors, never throws; a missing Supabase client is SKIPPED, not an error. A retention failure can never break a snapshot. BACKUP: backup-db.sh now accepts BACKUP_SSH_KEY as base64 (recommended — survives env-var newline mangling, which is how injected SSH keys usually break silently) OR raw PEM, detected by decoding and looking for the PEM header. Verified both forms detect correctly against a real generated key. Suite 279/3325 green, build exit 0. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01SmNjJAwEnqHPtXbvSZR8kA |
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builtbykev
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219167eebf |
A1: migration 021 — partner attribution (pre-apply commit, per docs/PARTNERS.md)
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> |
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builtbykev
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b20145c215 |
S10 (a1): public ledger profiles v1
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> |
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builtbykev
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c96e74c54b |
Session 59: migration 020 — ledger team/opponent (pre-apply commit)
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> |
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builtbykev
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2c79373a3b |
Session 58: Phase 1 spec + ledger_entries migration (pre-apply commit)
Migration 019: the truth-infrastructure table. Committed BEFORE it runs, per the Phase 1 GO instructions. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> |
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builtbykev
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1fa04dc776 | Sessions 5-7a: 955 tests, deployment ready | ||
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builtbykev
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2366660f5e |
feat: Feature 2.2 — Line Movement + Cascade Detection
Line movement system: - Baseline capture on first odds fetch of the day - Movement detection >= 0.5 points with direction (up/down) - Sharp money heuristic (sharp_action/public_action/unknown) - GET /api/movements with player, stat_type, min_movement filters - Movements included in GET /api/odds/nba live responses Cascade detection system: - Scratch detection: player props disappear from 2+ books - Affected user lookup via scan_sessions + picks - Parlay re-grade without scratched legs - cascade_alerts created for affected users - GET /api/alerts (Analyst/Desk only), PATCH /api/alerts/:id/read Zero extra Odds API credits — all detection piggybacks on existing fetches. Migration 002: line_baselines, line_movements, cascade_alerts tables. 30 new tests, 188 total (161 Node.js + 27 Python), all passing. Phase 2 Core Product COMPLETE. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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builtbykev
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3da1b4242c |
feat: Feature 1.2 (NBA stats FastAPI service) + Feature 1.4 (database schema)
Feature 1.2: Python FastAPI microservice wrapping nba_api - GET /stats/season-avg, /stats/last-n, /stats/splits, /players/search - Redis caching (24hr/1hr/6hr/7day), 0.6s rate limiting, PRA derived stat - 27 Python tests passing Feature 1.4: Complete Supabase database schema - 6 tables: users, picks, scan_sessions, bets, outcomes, performance - RLS enabled on all tables with auth.uid() policies - 3 triggers: auto-create user, updated_at, scan count reset - 37 schema validation tests passing - Migration SQL ready, pending manual apply (WSL2 DNS blocker) Total: 92 tests (65 Node.js + 27 Python), all passing Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |