b06a84af80bdc58ef7029d034ada3b14d304beb7
30 Commits
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 builtbykev
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b06a84af80 |
Settlement has been dead since 2026-08-01: a 500-id filter overflowed the URL
The self-learning loop stopped two days ago and reported success the whole
time. 1,444 ledger rows from 2026-08-01 sit unsettled with settle_attempts=0
-- never even attempted -- and every accruing challenger has been starved of
settled sample as a result.
ROOT CAUSE. settleLedger fetched open ids, then REFETCHED the full rows with
.in('id', ids). PostgREST puts filters in the URL, so 500 UUIDs became an
18,499-character request that the fetch layer rejects with "TypeError: fetch
failed". The result was destructured as `const { data: rows } = ...` with NO
error binding, so rows came back null, the loop body never executed, and the
function returned {settled:0, voided:0, unrecoverable:0, pending:0} --
byte-identical to a clean "nothing to settle". Reproduced against prod before
changing anything.
WHY IT HID FOR TWO DAYS. It is volume-triggered. Daily volume ran 20-260 rows
and settled perfectly for weeks; 2026-08-01 was the first day past the 500-row
fetch limit. And the zero-settle ops alarm reads these very return values, so
pending:0 told the watchdog the backlog was empty -- the alarm built to catch
exactly this could not see it.
THE FIX. The refetch existed only to add game_date/settle_attempts/
dclv_computed_at. Selecting them in the first query removes the id list
entirely, so there is no URL to overflow at any volume. A failed fetch now
surfaces its error instead of being reported as an empty backlog.
captureClosing carried the same shape one level down -- .in('id', g.ids) on an
UPDATE, which fails identically once a single line|odds group gets large on a
big slate. Its id filters are now chunked at 100 (~3.7 KB).
Tests: the regression is locked by asserting settlement issues NO id-list
filter at 500 rows, and that a failed fetch is never reported as an empty
backlog -- the two properties that would have caught this. Two existing
suites asserted the old two-query shape and were updated to the real one.
4,159 tests green (332 suites); web build exit 0.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01W1sivYNqY2TS5ftykmHBU9
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builtbykev
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07626de3de |
hits-v1: built on the right structure, measured honestly, REFUTED
Hits was diagnosed as a family mismatch: 84% of hits rows trade at 0.5, so the stat rides on P(0), and a negative binomial has unbounded support and no notion of opportunity at all. hits-v1 models it as the bounded conversion it is -- N ~ the player's empirical at-bat distribution, hits|N ~ Binomial(N,q), with the multiplier scaling q (conversion) and never N (opportunity). STEP 0 confirmed the inputs before the model existed: 30/30 real ledger players, 100% combined-input coverage. Every read goes through knownRate -- a row with no atBats is dropped, never counted as a 0-at-bat game. It FIRES: 158/159 hits props (99.4%) on the live production snapshot, through the real attachProjection path. Scoping by book IDENTITY rather than price shape kept 94 out-of-promotion-band props on the board, 93 of them modelled -- 59% that a price rule would have deleted. And it LOST. Point-in-time replay (game log truncated strictly before each row's game_date, real grade-time multiplier), hits-only, direction-aligned, n=242: resolution champion 0.195 / ladder 0.048 / hits-v1 0.026. Paired bootstrap on the same rows: hits-v1 - ladder = -0.022, CI95 excluding zero. Not promoted. The value is in what it eliminates. The family was wrong AND the mean was not the constraint -- hits-v1 moved the line-0.5 mean 0.554 -> 0.581 toward a 0.598 base rate while resolution fell. What is left is per-prop discrimination: the ladder's inputs, not its distribution. The pre-registered fallback is recorded as WRONG rather than deleted. It said hits might be genuinely low-resolution for anyone; the champion scores 0.276 on the identical 189 rows, so there is real signal and the ceiling claim was the comfortable reading, not the honest one. Its own control refuted it, and that control was already in hand when the branch was written. hits-v1 stays wired as a challenger writing its own ledger columns so the forward accrual can confirm the backtest. Champion, ladder, ranking, calibration, reference ruler and the four accruing verdicts are byte-identical -- the diff has zero deleted lines. Tests 4,156 green (332 suites); web build exit 0. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01W1sivYNqY2TS5ftykmHBU9 |
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builtbykev
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d103ecf4c3 |
Disambiguate takeable: THREE questions shared one word, now three names
BYTE-IDENTICAL. The audit found no consumer getting the wrong axis, so this is a disambiguation, not a bug fix. 4,131 tests / 331 suites green. STEP 1 AUDIT -- and the order's premise was wrong in a useful way: the four accruing challengers read the flag ZERO times (not four) the ranking gate wants PROMOTION, gets promotion [correct] the ledger column holds the LEDGER band, consumed as such the UI (LiveHeroProp) TYPES a `takeable` field it never renders THERE ARE THREE DEFINITIONS, NOT TWO -- and I only found the third by tracing the ranking gate: 1. IDENTITY can it be bet? book identity (takeability) 2. LEDGER BAND worth recording? odds >= -160, UNCAPPED plus 3. PROMOTION worth crowning? -160..+200, i.e. band PLUS a ceiling (2) and (3) genuinely disagree, and I measured it rather than asserting it: 439 rows -- 28.2% of all takeable=true ledger rows -- carry prices above +200, up to +1300. A +1300 longshot is a real bet worth RECORDING and not one worth CROWNING. Both are correct for their own purpose. THE DANGER WAS NEVER THE LOGIC. It was that three questions shared one word, so a reader could not tell which answer they held -- and hits, which must model thin/juiced/one-sided REAL markets, would have been the next reader to guess wrong. RESOLUTION: all three now have distinct names in config/takeability.js; gradeRanking calls isWithinPromotionBand so its intent is self-evident (a test pins it byte-identical to the old valueEngine call across the whole price range); the ledger dual-writes within_price_band with `takeable` kept as a documented DEPRECATED MIRROR so nothing breaks. Column comments in the database now say what each column actually holds. I did NOT redefine `takeable` in place. Four readers and a ranking gate sit on it, and silently changing its meaning under cover of a naming change is exactly the class of move this session keeps removing. Gates: 4,131 tests / 331 suites green; next 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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5de464330c |
URGENT: anchor the ledger price/book/takeable to TAKEABLE books
Ships before tonight's settle. Served path, champion, ranking and the
reference ruler are untouched.
TWO leaks, not one. The audit found ledgerService.indexProps; tracing the
lock price found that snapshotService.indexOdds has the SAME defect -- it
also indexed the full props list, so gradedAt.odds (the price a grade is
locked at) could itself be a DFS or exchange price. Fixing only the ledger
would have left the contamination flowing in through the lock.
Both now gate on TAKEABLE_BOOKS -- deliberately NOT MODEL_BOOKS. pinnacle
is model-eligible and correctly not takeable, so a MODEL gate would
re-break this the moment pinnacle's feed recovers. A test asserts pinnacle
cannot anchor a price.
TWO INDEXES, TWO ROLES, because the row needs two different things from a
prop and they have different correctness rules:
PRICE / BOOK / TAKEABLE -- takeable books only.
GAME FACTS (game_time, game_date, team/opponent) -- book-INDEPENDENT.
First pitch is first pitch whichever book listed it, so these still
come from any book. Gating them too would drop otherwise-valid rows
for no gain.
Collapsing those roles into one index is precisely the bug.
No takeable quote leaves the key ABSENT and the price null. An honest
missing price beats a price from a book you cannot bet -- and it keeps the
takeable flag from being computed off a DFS number, which is what made it
wrong on its own terms rather than merely mislabelled.
Gates: 4,111 tests / 330 suites green; next 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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eabf3b5bcf |
tb-v1: model total_bases as a compound outcome (challenger)
Current ladder (proj_p_over_line) and champion p_win are BYTE-IDENTICAL. tb-v1 writes alongside them, on total_bases props only. STEP 0 -- components confirmed on real data, not assumed. statsapi has no singles field, but hits - doubles - triples - homeRuns reproduces stored totalBases EXACTLY on a real 10-game log. So the decomposition is exact, not an approximation. THE MODEL. Each component gets its own per-game Poisson rate; TB is their weighted sum, and the PMF is built by exact convolution rather than simulated (TB support is small). It inherits the SAME combined multiplier proj-v1.1 computes, so the two models differ only in STRUCTURE. Why this is the fix: with identical mean TB of 1.0, a pure-HR hitter and a pure-singles hitter get P(TB>=4) of 0.221 vs 0.019 -- a 12x difference an NB on TB alone cannot express, because it treats one home run as four events. A test asserts that separation, and asserts P(TB>=4) for a pure-HR hitter equals P(at least one HR) exactly. INDEPENDENCE IS AN APPROXIMATION AND IS LABELLED AS ONE: a plate appearance that becomes a double cannot also become a single, so the components are weakly negatively correlated and independent Poissons slightly overstate the tail. Closer to the truth than what it replaces; not a solved problem. HONEST-ABSENT throughout: fewer than 3 usable games, or no derivable component, returns null and the prop keeps the current ladder value. An inconsistent row (hits < extra-base hits) is SKIPPED rather than clamped to zero -- clamping would invent a plausible line out of a broken one. I HIT THE Number(null)===0 TRAP IN MY OWN CODE and a test caught it: a null rate passed a naive finite check and was treated as a measured zero, which is the difference between "this player never triples" and "we do not know his triple rate". Both tbPmf and tbMean now reject null/''/boolean strictly. Holdout committed: TB ROWS ONLY (49 of 437 settled -- averaging into other stats would hide the effect) and DIRECTION-ALIGNED, since the unaligned comparison is the artifact that accounted for 41% of the ladder's apparent loss. If tb-v1 does NOT improve, the family-mismatch hypothesis is wrong and the mean/similarity branch reopens -- recorded in the query header. Migration applied: proj_tb_p_over + proj_tb_meta, NULL-meaningful. Gates: 4,104 tests / 329 suites green; next 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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1372e6bcf7 |
Order Zero Phases 1-3: keyed verification, ruler_version boundary, report
PHASE 1 (measured on the live prod feed with the real key): - WNBA is NOT thin at the feed -- 4.21 books/prop vs MLB's 3.61. It was allow-list-starved exactly as MLB was. This removes one candidate explanation for its anti-predictive result; it does not explain it, and WNBA stays abstaining. - We cannot see 64.8% of the MLB slate at all (zero admitted books). - Exchanges are real (smarkets 27%, novig 22%, kalshi 15% on MLB) but pinnacle, matchbook and polymarket measured 0% on BOTH sports. There is no sharp anchor for player props. The consensus is a MARKET consensus, not a SHARP one -- recorded as a permanent limitation, not a milestone. - DFS is the trap, quantified: prizepicks covers 82% of MLB props, the highest in the feed. Admitting it "for breadth" would have looked like the biggest available win. Permanently excluded. - Endpoints: /context WORKS and is FREE (umpire, roof, pitcher handedness, lineup confirmation -- richer than what we hand-built). /odds/closing and /movement are REDACTED (full structure, zero prices). /results and /exports/resolved-props are 403. - The $19/mo question is answered: soccer IS graded, ~15 competitions in 30 days (MLS 41k, Liga MX 15k, Brasileirao 12k, UCL/Europa/Conference). Our "soccer grades into a void" is a Pro-tier problem, not a data problem. NBA is absent because it is July -- seasonal, not inferable either way. PHASE 2 delta, corrected: MLB mean +1.50 pts, median 0, p90 +10.0, 17.0% of comparable props move >=5 pts, one-directional (the incumbent prices the over below the exchange-inclusive consensus). WNBA symmetric and tight. The median prop does not move -- the change is a right-skewed minority. That the rulers DIFFER is established; that the new one is BETTER is not, and that is the re-run. PHASE 2 item 6: ledger_entries.ruler_version applied to prod, 1,384 existing rows backfilled to v1_first_book (a statement of fact -- every row to date was produced by the first-book rule). ledgerService stamps CURRENT_RULER_VERSION on new rows. Never pool edge or CLV across it. Repo migration numbering lags prod; 025_ledger_ruler_version.sql records the DDL for review. PHASE 3: MLB isotonic p_win remains PROVISIONAL -- calibrated against v1_first_book, does not promote until re-run on the consensus ruler. NOT LIVE, deliberately: ALLOWED_BOOKS unchanged, served slate byte-identical, CURRENT_RULER_VERSION still v1_first_book, no live path calls consensusRuler. Gates: 4,022 tests passed / 322 suites; next 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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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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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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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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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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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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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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da8bfdf1db |
Render directional-CLV badge — Analyst+Desk, server-gated, receipt-bearing
CARD BADGE ONLY. Ticker-CLV explicitly DEFERRED (named, not lost).
PHASE 1 — SERVER-SIDE GATE AT THE DATA LAYER. A Free request never
RECEIVES dclv data: the CLV columns are appended to the SELECT only behind
canAccess(tier,'clv_badge') (new capability, analyst+desk), and responses
are ALSO stripped as defence in depth so a future SELECT change cannot
quietly leak. No CSS/client gate — data that reaches the browser has left
the building. dclv_fair_lock/fair_close are de-vig internals and are never
sent at all.
SURFACE AUDIT, all six channels, each test-locked to contain no CLV:
public profile (share link), snapshot/card feed, ticker feed, share
card/OG, embeddable widget, newsletter. A test also asserts no
ledger_entries read uses select('*') — a star would auto-leak every new
column, which is exactly how a gate becomes theatre.
PHASE 2 — IMMUTABLE ONCE COMPUTED. A settle can re-run (stat correction,
protested game) and a badge that flips positive->negative AFTER a user saw
or screenshotted it is a credibility failure. First computation wins: dclv
is only computed when dclv_computed_at is null, so a re-settle can never
rewrite a shown badge. Same discipline as the locked grade.
PHASE 3 — RENDER, test-first, ABSENCE IS HONEST. unknown / flat / null /
missing-receipt all render NOTHING — no element, no placeholder, no
"pending". Proven on an ALL-NULL board (today: 0 badges) and a MIXED board
(tomorrow: 1 of 4 badged, badge-less cards clean). Binary states only:
positive -> MOVED TOWARD US "graded -110 · closed -145"
negative -> MOVED AWAY "graded -110 · closed +120"
The RECEIPT is the persuasive part, so a badge with no numbers is
suppressed rather than shown as a bare claim. Negative is neutral context
and NEVER touches the locked grade — no back-door re-grading.
NO aggregate, count or rollup exists by construction: the module exports
exactly {clvBadge, fmtPrice} and a badge payload carries exactly
{tone,label,receipt} — asserted by test, because an on-screen tally would
be the held aggregate claim through the side door.
Build gotcha hit and fixed: clvBadge is CommonJS (allowJs) with no TS
types, so the .tsx needed an explicit cast at the call site — the build
worker exits 1 on type errors even though compilation "succeeds".
Suite 288/3473 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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dcdad60896 |
Directional CLV — per-read signal, side-bound, with a real compute trigger
PER-READ ONLY. No aggregate CLV stat, no CLV marketing un-held. PHASE 0 FINDING THAT SHAPED THE BUILD: the LOCK end must come from model_snapshots, NOT ledger_entries. The ledger stores only the graded side's locked_odds (694 rows, single-side) which CANNOT be de-vigged. model_snapshots retains BOTH side prices on 520/520 graded rows AND an already-de-vigged fair_prob on 520/520 — produced by the same devig.devigTwoWay the close uses, so "same method both ends" holds by construction rather than by convention. THE COMPUTE TRIGGER is the SETTLE PASS (ledgerService.settleLedger). At settle the game is final, so the close has landed and the read is final — the only moment both ends of the comparison exist. Grade and locked prices are written hours earlier and the close at lock, so without this trigger a correct CLV function would simply never populate. JOIN INHERITS THE PROVEN KEY: (sport, player_key, stat, side, game_date), WITHOUT line — a close that moved off the graded line is the entire point. Verified clean earlier: 164 identity groups, zero ambiguity. Rows whose capture refused (missed/ambiguous/one-sided) are UNKNOWN for CLV, matching the capture layer's own honesty. SIGN IS SIDE-BOUND and proven by test before the logic existed — the badge-inverting trap. Same market move: OVER-graded -> positive clv +0.0800 (fair .500 -> .580) UNDER-graded -> negative clv -0.0800 (fair .500 -> .420) exact mirrors. FLAT is a PROBABILITY-space threshold always (1.5pp): a 40-cent price move on a deep favourite reads flat, correctly, because price space lies about magnitude. UNKNOWN is a first-class state, never 0 — zero asserts "the market did not move", which is a claim; a missing close asserts nothing. describe() returns null for unknown so a badge can never render for it. migration 030 adds dclv/dclv_state/dclv_fair_lock/dclv_fair_close/ dclv_computed_at as NEW columns rather than reusing the C4 clv fields — conflating a verified per-read signal with a known-broken one would be the worst kind of quiet lie. Caught pre-deploy: the trigger call passed `deps`, which is not in scope in settleLedger (it uses `opts`) — a ReferenceError at the call site, outside the helper's try/catch, which broke two settlement suites. Suite 286/3447 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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b33612675d |
Heal execute: quarantine markers, re-enable DNP voiding, two exclusion scopes
Order 2 Phases 2 + 4. Pre-heal rollback point secured first: vyndr-20260720-093821.dump (856,890 bytes) VERIFIED ON THE BOX, not just exit 0. MIGRATION 027 — two DISTINCT exclusion scopes, deliberately separate: - quarantine_reason: the row's GRADE is untrustworthy (wrong_opponent_grade). The row REMAINS a real public settled result — the bet happened, the outcome is real — but it must never train or validate, so getModelAggregate now excludes it from the denominator alongside void/unrecoverable. - analysis_flags: the row is VALID for settlement and the record but unattributable for PER-GAME analysis (doubleheader dates). Explicitly NOT filtered from aggregates. Collapsing these would either wrongly drop 166 doubleheader rows from the record or wrongly keep 25 wrong-opponent grades inside model validation. Tests assert both directions, including that analysis_flags is NOT filtered. Also adds re_settled_at + settlement_source to model_snapshots. DNP VOIDING RE-ENABLED — reversing my own Order 1.5 disable, with scrutiny, because its premise was FALSE. Order 1.5 assumed a missing player row meant the row's DATE was wrong. The Phase 0 dry-run disproved it: across every bindable row the stored date matched a real game (MIS-DATED: 0), and the players I had cited as counter-evidence were genuine DNPs on their true dates (Freeman 07-18; Kwan/Hedges/Davis 07-17 — their teams played, they did not). The evidence is positive: games FINAL + no line in a full-season log = no bet existed. I got this wrong twice tonight in opposite directions; the dry-run is what caught it. Recording the reasoning in the code so the next reader sees why the flag flipped back. Suite 282/3386 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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1bcdd8b305 |
Fix the ROOT: bind props to their real game, never date by the grade clock
Order 1.5 Phase 1. PropLine emits NO commence_time (grep-verified: zero hits in proplineAdapter), so ledgerService's `dateET(prop.game_time) || dateET(gradedTs)` always fell through to the GRADE timestamp — and a 01:00/03:00 UTC snapshot is 21:00/23:00 ET the PREVIOUS day. Tonight's props were filed under yesterday, settlement correctly found no game there, and Order 1's void logic turned that into 64 destroyed results. gameBinder.attachGameTimes() now matches every prop to a scheduled game by TEAMS across the plausible ET window (grade date, +1, -1) and attaches the GAME'S OWN time/date/id. It runs in snapshotService before grading and before the ledger write, so ledger, retention and settlement all inherit the correct date from one place. HARD CONTRACT: an unbindable prop returns NOTHING. ledgerService no longer has a grade-clock fallback — a row with no real game time is SKIPPED and counted, because a mis-dated row is fabricated data and the ledger holds real values or nothing. A slate that binds nothing pages. DOUBLEHEADERS are reported, never guessed: two games with the same teams on one date mark the binding `ambiguous` so settlement can decline rather than attribute a prop to the wrong game. (Real example already in the data: mlb:2026-07-11:MilwaukeeBrewers@PittsburghPirates(Game1).) Also fixes retention, which had the SAME bug from last night — I had dated model_snapshots rows with the snapshot clock. Rows now take the ET date of the bound game_time. Suite 282/3381 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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d4a6170ffa |
Settlement fix forward: date-targeted resolution + terminal states
Order 1 of 2. Push scoring UNTOUCHED — it is correct. No healing here.
PHASE 1 — DATE-TARGETED FETCH replaces the rolling window for settlement.
settleSource.resolveOutcome() resolves the SPECIFIC DATE and, when the
player is absent, reads GAME STATE to learn what the absence MEANS:
game final + player has a line -> SETTLE (a partial game is a real
result, never a void)
game final + player absent -> VOID (confirmed DNP)
postponed / cancelled -> VOID
scheduled / in progress / SUSPENDED -> PENDING (a suspended game resumes;
voiding it would destroy a real bet)
player played, stat missing -> unknown, NEVER void a real appearance
This is FREE for MLB: mlbStatsAdapter.getPlayerGameLog already returned the
full season log and getPlayerStats was discarding it with .slice(-10).
Settlement now reads fullLog — same request, same cache — which removes
window-decay entirely (the verified failure was a Jul 12 game outside a
last10 starting Jul 6). Projections keep using last10, unchanged.
PHASE 2 — TERMINAL STATES (migration 026 applied). outcome CHECK widened to
hit/miss/push/void/unrecoverable; added settle_attempts, settlement_source,
settlement_version, model_version. A row that cannot be resolved after
SETTLE_ATTEMPT_CAP (4) date-targeted attempts becomes 'unrecoverable'
rather than pending forever. CRITICAL: getModelAggregate now EXCLUDES void
and unrecoverable from the settled selection — it used
.not('outcome','is',null), so without this a void would have counted as a
settled row and silently moved the public record. Verified in the record
calc, not just the settle path.
PHASE 3 — SETTLEMENT-RATE ALARM. zeroSettleAlarm only caught a TOTAL zero
while ~30% of a slate failed quietly (Jul 17: 57/86). opsWatch
.settlementRateAlarm pages when resolved/attempted falls below
SETTLE_RATE_FLOOR (0.8). Voids count as RESOLVED — a void is a legitimate
terminal state — so healthy voiding never pages. Third silent-failure
surface of the night, now closed.
PHASE 4 — VERSION STAMPING. src/config/modelEras.js defines the cutoff
ONCE (2026-07-19T22:50:00Z); migration 026 backfilled pre-cutoff rows as
'pre-retention-unknown' (naming the uncertainty, not implying knowledge);
new rows carry model_version.
Regression caught pre-deploy: getScheduleFn was not injectable, so the
ledger suite hit the real network and HUNG. Now injectable via opts and a
no-op under NODE_ENV=test. The "no row -> pending" test was updated to the
new behaviour deliberately: a missing row on a FINAL game now voids.
Suite 281/3373 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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89a2977f57 |
Item 7 — public accuracy reads the CLEAN ledger; BEAT CLOSE hidden until C4
Kev's call: the 30D accuracy surfaces must read TRUTH, not a cache that can't be filtered. My earlier degraded-row exclusion only touched getModelAggregate (Postgres); the public buckets/badge still read outcomeService (Redis outcome log), which counts degraded projection-0 outcomes and has no field to filter on. - /api/accuracy (AccuracyBadge) + /api/ledger/accuracy (buckets/ModelRecord) now source from the clean Postgres ledger aggregate via new ledgerService.getAccuracyView + accuracyBucketsFromAgg (model_value > 0 excludes degraded rows). Same response shapes → no frontend change. Redis outcome log is now read by nothing public; it can age out or be rebuilt. - BEAT CLOSE is a MEASURED-WRONG ZERO: captureClosing re-records the locked line as the "closing" line, so clv is flat on the whole sample and beat_close reads 0% (comparing a number to itself). Full write-up: specs/audit-data/ clv-capture-broken.md (the fix belongs to C4). Until then, beat_close_pct + clv_distribution are SUPPRESSED at the source (getModelAggregate, gated by clvCaptureReliable() / CLV_CAPTURE_RELIABLE=1). Every public surface already renders BEAT CLOSE only when non-null, so they all hide it now — no wrong zero anywhere. HIT RATE (real) is unaffected. Suite 271/3261 green, web build exit 0. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> |
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builtbykev
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9fc4edf3a9 |
Blast radius: exclude projection<=0 grades from the public model record
The degraded grades (projection=0 → model_value=0) are already settled in the
append-only ledger and must NOT be deleted (Data Semantics law). But their
hit/miss is noise, not model skill — they never had a real projection. So
getModelAggregate now filters `.gt('model_value', 0)` on both the settled and
pending queries: the rows stay in ledger_entries, but leave the public hit_pct /
CLV / per-tier record. `.gt` also drops NULL model_value. Post-fix no such row
can be written (projection<=0 refuses), so this only sheds the historical set.
This is the functional form of the "marking" the work order asked for — the
degraded locks are effectively marked as non-counting without mutating history.
Test builder mocks gained `.gt`; a lock asserts the filter is applied to both
queries. Suite 269/3253 green, web build exit 0.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
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builtbykev
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873a92931c |
Wave 1: NBA/WNBA settlement — grades settle vs free ESPN game logs
Unblocks the self-learning loop for basketball. Once an NBA/WNBA grade
exists (Wave 0), it now settles against the FREE ESPN per-game log
(espnStatsAdapter.getPlayerGameLog) — the same {found, last10:[{date,stat}]}
contract MLB settlement already consumes. accuracy:{sport} + by_tier
calibration + the Wave-3 TierRecord light up automatically.
- outcomeService/ledgerService: defaultGetPlayerStats routes nba/wnba to
espnStatsAdapter.getPlayerGameLog; MLB stays on mlbStatsAdapter.
- outcomeService: sport-aware statValue + a SEPARATE NBA_BOX_KEY/NBA_COMBO
map (S11 three-map-split kept — never merged with MLB_LOG_FIELD). Combos
(pts_reb_ast, reb_ast, stl_blk, …) sum components; a missing component
never fabricates a total.
- logRowOnDate: ESPN gamelog rows carry a FULL ISO timestamp (a late tip
rolls past UTC midnight), so basketball date-matches on UTC OR ET date;
MLB keeps exact YYYY-MM-DD compare. Outcome `date` is normalized to the
ET calendar day so the accuracy window filter + idempotency key behave
identically across sports.
- Final-honesty guard: never settle a basketball row whose ET date is
today (an in-progress partial box). MLB is final-only + settles same-day,
so the guard is scoped to basketball. The ledger path is already guarded
(.lt('game_date', today)) for all sports.
- opsWatch: nba/wnba added to SETTLEABLE_SPORTS; zeroSettleAlarm gates them
behind a real-finals probe (finalsBySport) so an offseason/off-day's
stale pendings never false-page "settled 0". snapshotScheduler counts
yesterday's ESPN state==='post' events and feeds the map; MLB unchanged.
- snapshotScheduler: boot announce per settleable sport
([settle:mlb] [settle:nba] [settle:wnba]). Thrown-error paging already
covers the new sports (settleAll* loop every sport).
Tests: tests/unit/nbaSettlement.test.js (16) — WNBA hit/miss/push, combo
pra, idempotent re-run, unplayed/today game does NOT settle, accuracy:wnba
+ byGrade + by_tier populate, ledger WNBA settle. opsWatch (+5) — finals
off-day no page, finals present DOES page. MLB suites unregressed.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
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builtbykev
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d3637e7abd |
S6 (a1): display — the full picture under the grammar
- specs/ROW-GRAMMAR.md: the row grammar law (slot order, color law, mark
law, mobile stacking, no-truncation), locked by tests/unit/rowGrammar.
StatStrip violations fixed: MovementChip before the grade (market
context before model output); ViabilityChips after the archetype
(identity is one contiguous run).
- Line-movement sparklines: intradayRefreshService.trackHistory captures
real {t,line} points per grade (seeded with the lock, deduped when
flat, capped 24) inside the snapshot write-back; StatStrip.LineSparkline
renders at >=3 points (green toward / amber against / dim flat).
- Last-10 dot strips: services/last10Dots (streaksService accessors) ->
/api/snapshot/:sport attaches last10_dots from rosterlogs:{sport};
StatStrip.DotStrip renders vs the LOCKED line, newest first.
- CLV distribution: getModelAggregate emits clv_distribution (7 signed
buckets, outliers clamped) only past the centralized n>=20 gate;
ledger MODEL header renders the bar strip.
- Global search: SearchModal (cmd-K via GlobalHosts + window.__search),
players via /api/players/search per sport + static lib/teams.js
(soccer deliberately absent); Nav search icon + Search first in the
mobile More sheet. Explore tab untouched.
- Landing LCP: fade-up floored at opacity .6 (hero h1 contentful on
first frame, S33 visible-floor rule) + IBM Plex Mono preload:false
(4 decorative font files off the slow-4G critical path).
2654 -> 2698 tests (226 suites) green; web build exit 0.
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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044941d406 |
S8 (a1): ops — the product watches itself
Settlement alarm (settle-pass THROW pages high; morning zero-settle alarm keyed off the Postgres ledger settle results, once per ET date, never on an empty yesterday), per-sport 3-consecutive-slot failure pager (pure opsWatch.createFailureTracker, pages once per losing streak), odds-api >=80% quota alert (once per day, Redis-deduped), systemHealth (statfs + os mem, disk>85 / mem>90 pages), daily 9 AM ET pulse (ONE notification: ledger rows yesterday via ledgerService.countRowsForDate, settles 24h, quota, disk/mem, desk line), docs/OPS-RUNBOOK.md (Uptime Kuma monitors, Coolify deploy-failure -> ntfy, phone subscription). All copy VOICE v1.1 — deadpan, numbers, no exclamation points (tests lint for it). 2398 -> 2437 tests. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> |
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builtbykev
|
4d2b27d1d0 |
Session 61 (pre-merge): live-verification fixes from day-one rows
1. [settlement] armed boot line — settlement WAS scheduled (the tick runs settleAllOutcomes + settleAllLedgers FIRST at every snapshot slot, src/snapshotScheduler.js) but was invisible at boot. Now verifiable from logs forever. 2. Null locked_odds root cause (4 day-one rows, all betmgm SB unders): genuinely absent in the DB — the first-seen book row carried no juice for that side. indexOdds/indexProps now PREFER a book row with both sides priced (still a real row, never synthesized). Display was correct: absent beats wrong. 3. Verified retry-safe: 'Odds data temporarily unavailable' is the odds-api quota gate (oddsService:423) — thrown BEFORE any spend or cache write; runSnapshot errors write nothing; the next cron retries fresh with PropLine first. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> |
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builtbykev
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f110bd63f1 |
Session F (night2): Phase 5 — records + dossier
5.1 Archetype defined on-page: one line from the archetype library under
ARCHETYPE DNA (BOMBER — elite raw power…); expander keeps the long form.
5.2 VYNDR-on-team live: getModelAggregate team scope (migration-020 column)
+ /api/ledger/model?team= + ModelRecord mounted on the Team Hub header.
5.3 WNBA/NBA profile parity: minutes-based usage (+MIN season cell) when
the feed carries minutes — absent beats invented.
5.4 Settings read meter: real rolling-24h usage from the SAME store the
limiter enforces (GET /api/user/scan-meter + proxy). Metered tiers see
'X of N reads today' + bar; unlimited tiers see nothing. Corrects the
stale '5 scans / month' copy.
5.5 Per-tier calibration on the MODEL tab: A+/A/B/C chips with hit% at
n>=20 PER TIER, 'building (n/20)' below — the separation between tiers
is the proof the grades mean something.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
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builtbykev
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9ae64516e6 |
Session D (night2): Phase 2.5 — intraday refresh + directional movement
Odds-only refresh every 20 min during slate hours (noon–midnight ET), in-process (INTRADAY_REFRESH=0 kill switch; skips full-snapshot slots): - signed delta RELATIVE TO THE GRADED SIDE; direction is the signal. - WITH the grade → STEAM badge, never a re-grade. - AGAINST >=1.0 → re-grade THAT PROP ONLY at the real current line: holds/refuses → VALUE (better entry, same read); drops → PUBLIC revision (grade updates, revised_from_grade preserves the ORIGINAL forever, UI strikethrough on slate strips + ledger cards). - Every run recaptures closing_line/odds → the close is now refresh- fidelity; SYNC goes live by dropping SNAPSHOT_EXPECTED_INTERVAL to 1200. - Ticker MOVE events feed from the refresh (>=1.0 moves). - QUOTA MATH: 36 runs/day/sport x 4 sports <= 144 PropLine calls/day vs 9,000/day free capacity (3 keys x 3,000). Re-grades are internal compute. - POST /api/internal/refresh/all for manual runs. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> |
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builtbykev
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d10bb4cce2 |
Session 59: Addendum + work-order 1.6 + Phase 2 + Phase 3 (2352 tests)
Overnight sprint for the Saturday 10 AM ET deploy gate — day one of the
public ledger record locks against freshly posted lines.
Task A — ledger team/opponent (migration 020, applied at 0 rows):
populated in both write paths from the real feed; opponent only when the
player's team matches a game participant (never guessed). Roadmap: Phase
4.5 WNBA ESPN-boxscore settlement (due ~Jul 24) + Phase 5 per-tier
calibration logged.
Task B — work-order 1.6 CLOSED (canonical player keys):
- searchPlayer resolves via nameKey; the old matcher deleted accents
("Sanchez" with acute -> "snchez") and substring-guessed onto the WRONG
player (the mismatched last-10 bug). Ambiguous -> null, never guess.
- Slate JOIN INVARIANT: a graded prop whose player's real team isn't in
the game is dropped (TB player can't render under MIL@PIT) — locked by
tests that fail the suite on regression.
- grades:{sport} TTL 2h -> 6h (expired between 5h cron gaps — the real
cause of /team "No active props" for slate players).
Task C — Phase 2 slate UX: tabs are THE filter (URL ?sport=, deep-linkable,
duplicate legacy tablist removed); cards cap at 6 graded props sorted
A+->F with ALL N READS in-place expander; waiting states show the real
next pipeline run ("Grades post ~6:00 PM ET").
Task D — Phase 3 mobile P0: root cause of vanished 390px nav was HIDE_ON
including '/' (landing had zero navigation) — fixed; html/body overflow-x
contained; GAME LINES collapses to best-line summary + "N BOOKS" expander
below 640px; venue drops before time/pitchers ever truncate.
Live verification: raw ESPN today STILL returns the Jun 13 NYK@SA Finals
game without a date pin; the pinned fetch returns 0 games, 0 off-date.
Backend 2327 -> 2352 tests (202 suites), web build exit 0.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
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builtbykev
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d296e40cb6 |
Session 58: Phase 1 — Truth Infrastructure (2327 tests)
ledger_entries is live (migration 019 applied to prod, RLS + NULLS NOT
DISTINCT dedupe verified against the real database). Every grade now
persists, settles against the real result, and carries closing-line value.
- ledgerService: pipeline pre-grade upserts (public model record, user_id
null, idempotent), closing capture on every snapshot (last write before
game start = the close), settlement with SIGNED CLV (over = locked -
closing; beat/faded/flat), 30d model aggregate with the hard n>=20 rule.
- Write paths: snapshotService -> ledger (priority path); Next /api/scan ->
ledger for authenticated users only (anon never touches the public
record). Refused reads write nothing and don't burn a scan.
- Honest refusal (work-order 1.5): no projection => insufficient_data,
grade null, "INSUFFICIENT DATA - no read" UI. The web gradeAdapter no
longer displays the line as the model projection (the audit's
model==line / +0% edge degenerate); the card renders absent states.
projectionFor is sport-aware (l5 -> l20 -> {stat}_per_90 -> xG).
- /ledger: MY READS | MODEL tabs; model header shows hit% + beat-close%
only at n>=20, else RECORD BUILDING + live pending count. ModelRecord
deferred-render strip on landing + player hero. CLV + outcome chips,
revised_from_grade strikethrough (Phase 2.5 ready).
- SYNC (Task 5): thresholds vs SNAPSHOT_EXPECTED_INTERVAL (normal <1.5x,
amber >=1.5x, STALE red >=3x) via /api/snapshot/summary.
- Phase 2.5 logged in specs/vyndr-roadmap.md (build after Phase 3).
- Data-semantics hardening: strict null-safe numeric parsing everywhere a
market value is handled (Number(null)===0 would have fabricated lines).
Backend 2309 -> 2327 tests (201 suites), web build exit 0.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
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