9c5b968351a84bda4c9b1c357187b89a19db550d
457 Commits
| Author | SHA1 | Message | Date | |
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 builtbykev
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e70c02aca0 |
report: incomplete-surface build triage; boundary tag NOT applied (no promotion exists)
Report-only. Nothing built, wired, tagged, or removed.
PART 1 — the recalibration boundary was NOT written. The build order asks to tag
grades pre/post edge-shading at "the true promotion timestamp"; there is no such
timestamp, and writing the marker would insert a fabricated model transition
into an append-only public record — the exact corruption the order exists to
prevent. Three independent production proofs:
A. model_snapshots.code_sha — every sha that ran the pipeline in the last 5
days is a documented commit from this session (
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builtbykev
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d54eca0afc |
report: pre-audit status pull — no promotion occurred; matrix re-derived (15/26)
Verified three ways that nothing was promoted and no re-lettering happened:
HEAD is the no-flip commit with a clean tree, efficiencyShading is imported by
zero production files, and live grades carry 0.0% A-family (MLB {B:1,C:4},
WNBA {B:15,C:10}). Neither 92.9% nor 43.6% is a figure measured here - the
challenger's real numbers were 97.4% would-change / 79.8% up / 79.0% A, with
0 of 1250 rows actually shaded.
Takeable tags landed (1245/1250 tagged, takeable_floor on all, one floor -160;
the 5 untagged have no locked price). The model-version boundary is absent and
correctly so - there was no recalibration to mark. Not a pre-audit gap.
Matrix re-derived from live prod probes, importer counts and nav-link counts:
15 of 26 fully done. Book comparison RESOLVED (BookComparisonPanel routed to
the grade card). Grade card honesty improved by the edge_pct retirement.
ShareCard / MobileEdgeBoard / DemoScan still dead code. Seven live routes
remain orphaned with zero nav links; /system and /offseason are 404. No
LIVE-but-not-HONEST surface found.
Design is NOT complete: Live tracking, Slip reader and Newsletter are shipped
with no design artboard - design is the gap, not build. Offseason is the
reverse (designed, never built).
Chrome audit manifest assembled: 11 items with per-item session state, four
requiring an entitled Desk session that only Kev can drive.
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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10aaaeb1da |
docs: promotion gate not passed (no flip); Order B edge_pct display retired
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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0997334f8b |
Order B: retire edge_pct display. Promotion gate NOT passed — no flip.
THE PROMOTION WAS NOT PERFORMED. Champion grade path byte-identical (diff empty
across intelligence/, gradeSlateService, snapshotService). Projection, p_win and
the CLV instrument untouched.
REVIEW ZERO IS A GATE AND THREE OF FOUR PREREQUISITES FAIL:
0.1 scores are ESTIMATED priors from the founding spec, not measured. The
premise's cited values are not in the code either — the module holds
nba:points .80 and mlb:total_bases .55; there is no NBA 0.72 and no WNBA
score at all.
0.2 VERSION-BOUNDARY TAG DID NOT LAND — config/modelEras.js has zero shading
references. It was deliberately not applied twice (nothing had been
promoted) and reported both times. The order's own rule says STOP.
0.3 NO ROLLBACK FLAG EXISTS — zero occurrences of SHADING_ENABLED /
EDGE_SHADING / shadingEnabled anywhere in src/.
0.4 takeable tags DID land (migration 034, 1246/1254 rows). PASS.
AND THE APPROVED DELTA DOES NOT MATCH THE MEASURED ONE. Approved: 43.6% of
grades re-letter, efficient markets tighten and soft hold. Measured on all 1250
live rows: 97.4% change (1217), 79.8% move UP, 17.6% down, resulting in 79.0%
A-family (MLB 93.4%) against the champion's 0.2%. And rows_actually_shaded = 0
of 1250 — 96.5% of markets are unscored (f=1) and the one scored market present
is the anchor (f=1.0 by construction). The entire re-letter comes from switching
to edge-vs-fixed-bar grading, NOT from efficiency shading, which is inert on
this board. That is an unapproved grading-basis change riding along, which the
order's own "no new scaling changes riding along" guardrail forbids.
Flipping would re-letter 97.4% of an append-only public record, move 79.8% of
grades UP and mint A's on 79% of the board, on a letter whose measured
correlation with outcomes is r ~ 0.005 — the exact scenario the permanent
founder ruling forbids.
SHIPPED — ORDER B (independent of the promotion, and a live falsehood):
edge_pct display retired from GradeResultCard (confidence strip, EDGE stat cell
now honest-absent, alt-ladder rung) and SoccerGradeResult. DeskShowcase kept
(already honest). Computation and the board's signed-edge sort fallback SURVIVE
— deleting them would re-break the sort fixed on 2026-07-29; a test asserts all
three survive and the sort still orders agrees -> disagrees -> absent.
Fixed two build-breakers the retirement caused (orphaned edgeColor import,
orphaned edge_pct destructure; edge_pct stays on the props contract). Two
pre-existing tests superseded rather than deleted: they asserted the edge figure
is sign-coloured, and now assert the stronger property that no edge percentage
renders at all.
Floor: 314 suites / 3908 tests green (9 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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1e9c808d99 |
docs: edge-shading challenger measured — flooding persists, input scale is the bug
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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c2c7abbb65 |
Edge-shading challenger: built + measured. Flooding NOT fixed — input scale is the bug
Challenger only. Champion grade byte-identical (verified by diff). Nothing promoted, no live grade re-lettered, no ledger row deleted or re-settled. BUILT src/services/challengers/efficiencyShading.js (measured-never-served): adjusted_edge = raw_edge * f(efficiency); grade = band(adjusted_edge) against ONE fixed bar (A+>=10, A>=5, B>=3, C>=1, D>=0, F<0) that never moves. f(e) = E_SOFTEST/e bounded to (0,1] — soft markets intact (never amplified), sharp shaded toward but not past zero, unscored -> f=1 and FLAGGED. A fence test asserts no production grade path imports it. Cross-market behaviour is unit-proven: the same raw 6% edge grades A in soft mlb:total_bases and B in sharp nba:points. MEASURED on 1250 live ledger rows — Phase 2.5's answer is NO, the flooding is not gone: challenger 79.0% A and 80.9% A/B (MLB 93.4% A) vs champion 0.2% A. TWO findings explain why, and they are the point of the order: 1. The shading is a NO-OP on the live board: rows_actually_shaded = 0 of 1250. 96.5% of rows are UNSCORED (f=1), and the one scored market present (mlb:total_bases) is the anchor so its f is 1.0 by construction. mlb:strikeouts and nba:points do not appear in the ledger at all (our basketball is wnba, not nba). Challenger vs baseline: 0 rows changed. 2. Placement was never the bug — the INPUT SCALE is. Against a fixed 5% bar the RAW edge already clears A on 100% of MLB doubles, 89.6% of hits, before any shading. MLB median raw edge is 60%, twelve times the bar. Decisive test: apply the sharpest score in the spec (f=0.647) to EVERY row — the maximum the design permits — and 75.8% still clear A (MLB 91.7%). Since f is bounded <= 1, no achievable shading can close a 12x overshoot. Moving the multiply from the threshold to the edge does not change the outcome. This is edge_pct behaving as the 2026-07-29 diagnosis described: a price-free (proj-line)/line gap whose scale is a function of line size. It is not a betting edge, so no fixed betting-edge bar is meaningful against it. 2.6 efficient-market over-suppression: CANNOT DETERMINE — zero live rows are shaded, so there is no efficient market in the data to over-suppress. Phase 3: takeable tagging was completed in the previous order (migration 034, 1246/1254 rows) and is not repeated. The model-version boundary is again NOT applied: nothing promoted, so no boundary exists. Unblocking needs the input replaced, not the multiply moved: p_win vs fair_prob (both already computed) instead of edge_pct, plus scores FIT from our own record for the markets we actually grade. Floor: 313 suites / 3899 tests green (9 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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896e6e1a00 |
docs: takeable tagging shipped, efficiency challenger blocked (board + state)
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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a6afac43cc |
report: market-efficiency scaling check — FLAT, mechanism structurally absent
Report-only. No threshold, grade, or efficiency value changed. VERDICT: FLAT. marketEfficiency.js does not exist (zero occurrences of market_efficiency / efficiency_score in src/ or web/src/). The spec's 0.85/0.60/0.55 values appear in grade_thresholds.json only as PROBABILITY BANDS - a coincidental numeric overlap, not efficiency scores. The base edge thresholds (MLB A:5%, NBA A:7%) do not exist either: engine1.js has zero `edge` references, so the live grade is not an edge-vs-threshold comparison at all. The specced rule threshold = base x efficiency has no host. DISPOSITIVE: engine1.js contains ZERO `sport` references. computeFactors receives no sport or market, so per-market OR per-sport scaling is structurally impossible in the live grader - not merely unwired. Phase 2: the matched-edge test is confounded (edge is not the grading input - the same market emits both B and C at one edge). The aggregate that discriminates: mean grade index wnba points 4.71 at mean edge 10.2 vs mlb hits 4.58 at 69.5 vs mlb total_bases 4.32 at 84.9 - the efficient market earns the highest grades on one-eighth the edge, the opposite of spec. PREMISE CORRECTION (measured): this order's opening claim that full-output and collapsed grades "agree 100%" does not hold - on 512 rows carrying both they agree 17.8%, with 33.8% differing by 3+ tiers. The prior discrimination result stands (champion r=0.0050 null vs probability r=0.1313; MLB 0.0686 n.s. vs 0.2356 p~0.0004). Repo unchanged between orders. The collapse was not a phantom and the re-adjudication list stays open. Scope: flat thresholds are a grade-CALIBRATION gap only - the projection and the CLV edge (which measured p_win, never the letter) are untouched, so this is not a third shadow-model alarm. But the fix is NOT independently bounded: with no threshold step to multiply, efficiency scaling presupposes probability grading. It is rule R4 of specs/full-output-grade-mapping.md and belongs to that MLB-first challenger. 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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708f0fde5c |
report: full-output grade mapping spec + collapse cost measured
Report-only. Nothing built, reconnected, or promoted. Premise corrected again: the three-layer engine is BUILT but NOT WIRED and NOT DEPLOYED (0 python refs in every grade-path file, 0 python in Dockerfile; there is no engine1Adapter). So no posterior/CI/similarity prior exists to inventory or diff. Measured against the collapse that actually exists instead. THREE collapses, not one: (A) estimateProbability's components discarded at analyzeViaEngine1:521-524; (B) THE SEVERE ONE - p_win never reaches the grade at all (engine1.js has zero probability references), so the probability is excluded from grading rather than collapsed into it; (C) grade_thresholds.json (probability->grade) read backwards to manufacture confidence. Market-efficiency scaling is never computed - a gap, not a collapse. MEASURED on 354 settled rows carrying the served letter and the locked pre-game p_win (forward, not lookahead). Grade->outcome point-biserial r: champion letter 0.0050 (p~0.93, null) vs probability letter 0.1313 (p~0.013). Per sport: MLB champ 0.0686 n.s. vs prob 0.2356 (p~0.0004); WNBA champ -0.0986 vs prob -0.1258 - BOTH INVERSE. The served letter is inverted between its only two populated tiers (B 52.4% n=168 vs C 56.9% n=174). Verdict: costly on MLB, and un-collapsing does NOT help WNBA -> the challenger must be MLB-FIRST. Five falsifiable mapping rules specced, incl. R2 (uncertainty grades down) stated explicitly and droppable if it fails. Hard requirement on the next order: persist per-row n, SE and pre-adjustment p, or R2/R4 can never be adjudicated (not stored today). Re-adjudication list flagged incl. proj-v1.1's NOT PROVEN verdict (judged against the collapsed champion, so not final) and ROI-by-grade (with B/C inverted, the MLB-C +4.57% segment is likely an artifact of a meaningless letter). 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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dd98b0b614 |
report: model architecture recovery map — the live grade uses 0 of 3 specced layers
Archaeology only; nothing built, reconnected, or promoted. The champion is two DISCONNECTED estimates: the letter is engine1's additive factor index (zero references to p_win or any probability in engine1.js), and p_win is probabilityEstimator's frequencyOver + 5 heuristic layers, computed after and merely attached. The live grade path never calls the Python service. The Python three-layer engine is NOT DEPLOYED — no python/pip in the Dockerfile; app.js only health-checks it. So Layers 1-2 never shipped. Layer 3 is wired BACKWARDS: grade_thresholds.json maps PROBABILITY->GRADE and the live JS reads it in reverse to manufacture confidence from an already-chosen letter. Per-sport market-efficiency scaling is specced-absent. Consequence stated plainly: every metric audited to date is on the shadow model, not the specced engine, which has never been measured. Sport boundary TESTED not asserted: a new sport on the live path is a ~10-file core edit with four documented silent-failure modes. Per-sport records DO exist (sports.mlb n=526/62% vs pooled overall n=937/58%, each n>=20 gated), but /api/accuracy ignores ?sport= and the pooled overall would absorb a new sport. Park x weather confirmed challenger-only; xwOBA and leash absent. Recovery map is dependency-ordered with MLB as the reference module. 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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f3bf300b36 |
report: C1 takeable-floor derivation — CANNOT DERIVE (every bucket CI spans zero)
MLB decided overs n=296, 100% with locked_odds. ROI by locked-price bucket shows every 95% CI containing zero; the curve is NON-MONOTONE and runs opposite to the premise (deepest buckets positive, the -111..-160 middle most negative); and price bucket is confounded with market (+200up = doubles/HR longshots). Rows needed per bucket to resolve a 5-pt edge: 661-2285 vs actual 8-71 (~187 days for one bucket at current accrual). The inherited -160 is neither confirmed nor refuted. The no-ceiling call is not supported by this data either (+200up is the worst bucket) though it is not refuted - it stays a design choice, not a data-backed one. Recommends C2 proceed with -160 as an explicitly-labelled POLICY floor plus a re-derivation trigger (any negative bucket n>=300, or end of MLB regular season; adopt a derived floor only when a bucket CI excludes zero). Enumerates all 9 takeable sites, incl. the live drift hazard (backend env-tunable, frontend hardcoded) and the user-visible band copy in PriceTriplet. 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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f310608ca4 |
docs: top-graded selector fingerprinted — strip-after-rank boundary proven in prod
The anonymous live order (Brionna Jones edge 29.4 ahead of Rhyne Howard edge 42.9) is only explicable by server-side p_win ranking (.90 vs .745, both takeable) while the payload carries no paid fields — the free caller got the paid RANKING without the paid SIGNAL, on live data. 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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72a14dc4cd |
Build /api/props/top-graded server selector: rank with p_win, serve without it
New READ endpoint. No grade, ledger row, lock_line, or scoring write. Push
scoring untouched.
REVIEW ZERO CORRECTED THE PREMISE: the handler NEVER EXISTED in any commit
(searched git rev-list --all for a /top-graded definition in src/ — zero hits).
Not "removed" — the three axios callers (cheatsheetGenerator, gradeOfTheDay,
widget) and the Next proxy were written against a phantom endpoint, so those
three content generators have silently received [] for their entire life.
Contract recovered from the four consumers, not guessed: {props:[...]},
?sport=UPPERCASE (absent = all sports, which gradeOfTheDay relies on) + ?limit,
rows carrying player/stat/line/direction/sport/grade/confidence? plus the
player_name/stat_type aliases and game_id.
POPULATED-PATH RISK FOUND: the board's populated branch had never run in prod,
and dashboard/page.tsx:463 calls g.stat.replace(/_/g,' ') UNGUARDED (g.player
also feeds the row key, /scan URL and heading; sport must be UPPERCASE for
SportPill). toRow requires non-empty string player+stat and a finite line,
uppercases sport, and DROPS unrenderable rows — a shorter board beats a broken
one.
THE LEAK BOUNDARY (why this is server-side): the browser cannot rank on p_win
for all tiers because stripModelPrice deliberately withholds it from unentitled
tiers. Order of operations is
read cache -> RANK with p_win (every tier) -> map rows incl. model fields
-> stripModelPrice(rows, tier) -> serialize
so a free caller receives the paid RANKING without the paid VALUES. Tier comes
from resolveTierFromRequest, which FAILS CLOSED to 'free'. Cache-Control is
private under a bearer token, public otherwise (the /api/snapshot precedent).
ONE SHARED DEFINITION, no drift: new src/utils/gradeRanking.js
(takeablePWin/descNullsLast/rankGrades). heroPropService now imports
takeablePWin instead of its inline copy (behaviour unchanged — it was that
logic verbatim); the selector imports rankGrades; web/src/lib/slateAdapter
keeps its mirror (the browser cannot import src/, S25) and a test cross-checks
the two on identical fixtures (playerName.js precedent). Board is grade-first
("top GRADES"), hero is p_win-first ("top read") — they differ BY DESIGN and
agree within the leading tier.
HONEST LIMIT: the Next proxy (cachedBackendJson) sends no Authorization header
and caches under a shared key, so via the dashboard every viewer gets the
free-tier payload — correct order, no paid values. That is the SAFE behaviour;
forwarding auth into a shared cache is exactly how a paid payload leaks to
anonymous viewers. Per-tier delivery through the proxy needs a tier-keyed cache
and is not done here.
Verified on real prod snapshot data (anonymous path): MLB 8 props, WNBA 10,
0 paid-field leaks, render-contract safe on every row, sport uppercase.
Floor: 311 suites / 3882 tests green (18 new — leak test uses POPULATED p_win,
not today's nulls: entitled gets p_win and it drove the order, unentitled gets
a byte-identical order with all five MODEL_FIELDS absent and no trace in
JSON.stringify, while book/fair market facts survive). Web build exit 0.
Dashboard visual is auth-gated -> tagged for the Chrome audit, not faked.
Held: edge_pct rescale/retirement (Order B); board columns/contract unchanged;
tier-keyed proxy caching.
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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69feab4d25 |
docs: grade-board sort fingerprinted (deploy boundary captured; ladder induced both directions)
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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b85b351993 |
Grade-board sort: signed signal, takeable-gated p_win, missing sorts LAST
Display ORDERING only. No grade, ledger row, lock_line, scoring, or edge_pct
scale/display change. Push scoring untouched.
Two defects removed from selectTopGrades (wrong at ANY scale, independent of
edge_pct's separate retirement):
1. edge: Math.abs(numOr(g.edge, -Infinity)) — abs() on an already-
direction-signed value ranked the model's strongest DISAGREEMENTS level
with its strongest agreements (177 public ledger rows carry a negative
edge; positive = the model AGREES with the graded side).
2. Math.abs(-Infinity) === Infinity, so a row with NO edge sorted FIRST —
absent data presented as the top pick (the Number(null) class).
New key: grade -> confidence -> takeable-gated p_win (nulls LAST) -> SIGNED
edge (nulls LAST) -> input order. Scales are never mixed in one comparator.
Takeable band = web valueState.isTakeable, asserted byte-equal to the hero's
config/valueEngine.isTakeable (-160..+200) incl. strict-null.
Alt-line ladder (analyzeViaEngine1:506) no longer sorts by edge_pct: ordered
highest-p_win-first derived analytically at zero added compute — P(stat >= k)
is monotone non-increasing in k, so p_win-desc is line-ASC for an over and
line-DESC for an under. base stays marked; no consumer depends on
alt_lines[0]; deskShowcaseService.rungsOf already re-sorted by line.
THREE PREMISE BREAKS found report-first, before code:
- /api/props/top-graded 404s in prod (absent from src/) so the dashboard
board renders receipts/empty — the edge sort orders nothing there today.
The prior order's "97.3% of rows tie" was a LEDGER measurement wrongly
extrapolated to that board. Fix is correct-in-itself and lands when the
feed is restored.
- p_win cannot be a client-side key for all tiers: snapshotGating strips it
for unentitled tiers ("shipping p_win is shipping the model price").
Verified live: prod /api/snapshot carries p_win on 0/8 MLB, 0/25 WNBA.
- Ladder rungs carry no per-rung price, so the takeable gate is inapplicable.
Verified on real data, both sports, both paths: unentitled — WNBA (n=25)
ordering CHANGED, MLB (n=8) unchanged, signed edge non-increasing in every
(grade,confidence) tie group (20 pairs, 0 violations); entitled — 40 real
ledger rows with p_win+locked_odds, p_win-descending, untakeable chalk NOT
promoted (Trea Turner .757 @-275 does not beat Rhyne Howard .745 @-120)
(36 pairs, 0 violations).
Hero consistency, stated honestly: same signal + same gate, different
precedence BY CONTRACT (board = grade-tier-first "top GRADES"; hero =
p_win-first "top read"). Identical within the leading tier (verified); across
tiers the board may lead with an A the hero doesn't pick. Not a contradiction.
Floor: 310 suites / 3864 tests green, web build exit 0. Dashboard + Desk
visuals are auth/feed-gated -> tagged for the Chrome audit, no visual faked.
Held: edge_pct rescale/display retirement (Order B); building the missing
/api/props/top-graded selector; exposing p_win to unentitled tiers.
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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9b5235cf99 |
docs: hero ranking fix verified (new code serving — max-p_win takeable, chalk excluded)
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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41b86e3874 |
Hero ranking fix: rank by champion p_win among takeable, honest empty state
Review Zero found the hero's ACTUAL behavior was worse than "unknown": it ranks on ev_pct (heroPropService v2), but ev_pct is NULL on served grades and Number(null)===0 made Number.isFinite(Number(null)) TRUE — so every prop tied at EV 0 and the "top read" was really the FIRST takeable A/B prop in cache order (arbitrary, dressed as ranked). v3: rank by the CHAMPION's p_win (the only signal with a promising, not proven, edge — its takeable-MLB-over CLV survived the skew audit) among A/B, TAKEABLE- priced reads (isTakeable band -160..+200, same as the proof/audit). Strict null guard kills the Number(null)=0 bug. Takeable filter is mandatory (raw p_win crowns -300 chalk). NO backfill: nothing qualifies → honest empty state (available:false, reason:'no_qualifying_read'), never a weak recent read. p_win is RANKING-ONLY, server-side — toHero never exposes it and the route strips it. Framing unchanged in substance (model number vs book number, grade, timestamp) — no proven-edge / +EV / best-bet claim, no CLV/ROI/edge number. Display-only: reads snapshot caches, writes to nothing (no grade/ledger/lock_lines). Full suite 3852 green, web build exit 0. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01VsztNChZ7vEvSR61AuMhD1 |
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builtbykev
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e7ec501054 |
docs: book-comparison verify note (live-card screenshot auth-blocked; data feed + tests verify)
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
|
36014c7c30 |
docs: Book Comparison wired to the prop card (matrix row 18 DONE, 16/26)
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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2ab2eeaa7d |
Wire BookComparison to the prop card (display-only, honest states)
BookComparison.tsx was built but UNROUTED (dead). Route it to the GradeResultCard via a new self-fetching BookComparisonPanel that reads the live /api/books feed (source:'bookprices' — the snapshot-locked, fenced, byte-identical store). Contract fix (Review Zero 0.1): books frequently sit at DIFFERENT lines (WNBA DK 21.5 / FD 18.5; MLB 2/3), so BookComparison now renders EACH book's own line per-row — never one shared header line implying a false same-number comparison. Honest states: single-book (the common case for MLB) → one book, "One book posting this prop.", NO crown/second row; multi-book → all books' own line+price, NONE crowned (BOOK_CROWN_ENABLED=false — no best-price claim, verified live crowned:false); no books → renders NULL (panel self-hides), never a placeholder. No regression: only the always-empty inline d.books section was replaced; grade, projection, PropLine line, and PriceTriplet price are untouched (wiring test asserts them). Freshness (0.4): bookprices is written in the SAME snapshot that locks the grade (intraday refresh touches neither gradedAt.line nor bookprices) — same fresh, no stale-label needed. Web-only → grade byte-identical trivially. Full suite 3851 green, web build exit 0. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01VsztNChZ7vEvSR61AuMhD1 |
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builtbykev
|
3a05447f77 |
docs: lock-line persistence unblocks the staleness audit (migration 033, lock_lines)
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
|
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
|
37261260d1 |
report: over-side skew audit — champion over-CLV SURVIVES baseline (promising, not confirmed)
Read-only. Takeable MLB overs n=62. Mechanical baseline (no-edge) CLV +1.51pt (n=20); high-edge +8.64pt (n=37); difference +7.14pt = real edge. Champion p_win->CLV partial r=0.375 (SIG p~0.003) survives price control. Skew one-sided (unders -7, over baseline +1.5). De-vig clean (same-book pairing, analyzeViaEngine1:539); close well-defined (DK/MGM r=0.92). Greenlights building the takeable-edge grade ON THE CHAMPION, not proj-v1.1. Flagged promising-not-confirmed: thin n, lock-time multi-book staleness check BLOCKED (not retained), pinnacle ref n=8. No fix, no promotion — diagnosis only. 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
|
59b77cdef2 |
report: proj-v1.1 takeable-edge proof — NOT PROVEN (n=45 MLB overs)
Read-only proof. N-gate passed (overlap 45). proj-v1.1 edge-CLV partial correlation controlling for price = 0.245 (n.s.); ~half the raw 0.455 is the shared -fair_prob_lock term (mechanical). Champion out-predicts proj on the same rows (champ partial-CLV 0.380 sig; champ-edge->hit 0.25 vs 0.12). Unders contaminated (CLV -9.3); WNBA proj-v1.1 doesn't run. Promotion HELD; the under-audit is moot since proj loses to the champion first. 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
|
b8ee216c62 |
docs: CLV instrument repair + the straight finding (unders lag the close)
closing_prob 59 -> 406 (MLB 248, WNBA 158). Root cause was attachClosingProb's truncated read + write-once market_unavailable, not capture or the join. CLV measured: MLB unders lag the close (mean -9.1 prob-pts, 74% lose), MLB overs +2.0, WNBA flat -> the +4.57% MLB-C and over/under asymmetry are substantially stale-line artifacts. Unblocks the proj-v1.1 proof order. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01VsztNChZ7vEvSR61AuMhD1 |
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builtbykev
|
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
|
afb56b144b |
NexaPay purge: VYNDR is Stripe-only — remove all NexaPay traces
NexaPay was cross-project contamination (from another venture) — never a real VYNDR payment path. Purged; Stripe path untouched. Removed: - web/src/services/nexapay.ts (createPaymentLink/getTransaction/HMAC verify) - web/src/app/api/webhook/nexapay/route.ts (the only importer; Next-registered, reachable — now gone) - NexaPay comments in email.ts + checkout/route.ts - Active NexaPay entries in docs/SYSTEM-MANIFEST.md (route list, NEXAPAY_* env table, service row) + stale claim in wiring-data-train.md - sw.js precache entry for the deleted webhook chunk Verified: ZERO NexaPay in code (web/src, src, tests). Full suite 3833 green (count unchanged — nothing depended on it, confirming it was dead). Web build exit 0. sw.js parses clean. Stripe checkout untouched (Next→Express→Stripe). FLAGGED FOR KEV (a repo delete cannot close these): - Coolify env: remove NEXAPAY_API_KEY / NEXAPAY_WEBHOOK_SECRET / NEXAPAY_API_URL - Revoke the NexaPay API key + webhook secret at NexaPay's dashboard; de-register the webhook if an account was ever configured - DB column user_profiles.nexapay_customer_id is orphaned (no reader/writer) — drop via a follow-up migration (migration 011 left as history) Cross-project check: ZERO Noctem-Supabase refs; VYNDR references only its own Supabase (zmdnczhtdxcddsxzttub). NexaPay was the sole contamination found. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01VsztNChZ7vEvSR61AuMhD1 |
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builtbykev
|
3592aba8d5 |
docs: log honesty pass in completion matrix + STATE (rows 19/20/24 HONEST fixed)
Records the six live fabrications removed/hidden, keeps media/newsletter/WIRE on the board as real work, logs the news/line-movement signal as a future model input, and logs the known honesty gaps (hit-rate-without-ROI, CLV starved). Honest state: "no KNOWN live fabrications," not "provably none." Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01VsztNChZ7vEvSR61AuMhD1 |
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builtbykev
|
6bc18d823c |
Honesty pass: remove every live fabrication (REMOVE/HIDE only, no feature cut)
Six live untruths corrected — no grade/snapshot/scorer/pipeline touched: 1. /compare — hardcoded Jokic A+/Wembanyama A + fake VERDICT replaced with an honest in-development state; removed from Nav + BottomTabBar (route still resolves, never the sample). Real two-player build is later. 2. Pricing — founder Desk $34.99→$44.99 (matches lib/checkout.js), Analyst $14.99; removed the struck $19.99/$44.99 "regular" numbers and DeskShowcase's stale $34.99. First-100 counter is real (ClaimMeter → Stripe countFounderSeats); no fake "first 50" desk claim added (no such counter exists). 3. FAQ "NexaPay" → Stripe (verified: live checkout is Next→Express→checkout.stripe.com). 4. FAQ + Features "Brier/CLV published from day one" removed (not surfaced yet) — returns when real. Backend Brier compute untouched. 5. MobileEdgeBoard removed from the Slate — its edge% feed was a miscalibrated placeholder (masked >40% as "—"); phones now show the real game cards. 6. Price triplet — never-computed model/EV now derives NO_MODEL (honest absent, MODEL "—" / "NOT PRICED", no verdict) instead of QUARANTINE's false "we suppressed our price / a leg is poisoned" copy. Fixes grade card + LiveHeroProp. Full suite 3833 green, web build exit 0. Tests updated to the new honest contracts. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01VsztNChZ7vEvSR61AuMhD1 |
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builtbykev
|
be6b4a2849 |
inventory: VYNDR-COMPLETION-MATRIX (5-part DONE map of every surface + model)
Read-only inventory order — no code built/wired/fixed/deployed. Maps every
user-facing surface and model component against DESIGNED·BUILT·WIRED·LIVE·HONEST,
re-derived from repo
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builtbykev
|
b0a51c8a0d |
docs: /api/books contract + crown gate (Book Comparison order)
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01VsztNChZ7vEvSR61AuMhD1 |
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builtbykev
|
e81c9b8c51 |
Book Comparison Phase 1-3(backend): fenced per-book store + honest gated crown
Per-book prices existed only transiently (odds cache, ~1h, raw names, grade-path
input); every grade-path persistence point collapses to one book. The
/api/books feature was built+mounted but non-functional (fed FLAT rows to a
GROUPED comparator -> always empty).
Phase 1: bookPriceStore captures per-book prices from `props` BEFORE dedupeProps,
keyed nameKey|stat, into bookprices:{sport} (SNAP_TTL) in snapshotService. Fenced:
reads props, writes its own key, read by nothing on the grade path. Grade proven
byte-identical (test + no-grade-path-reference grep test).
Phase 2: scripts/measure-book-spread.js reports same-line best-vs-worst spread
(cents + implied-prob pts), per sport, never pooled. Pre-registered crown
threshold: median >=8c OR >=2pp. Runs post-deploy on real data.
Phase 3 (backend): compareProp is honest-absent (single-book/flat -> no crown)
and the crown is gated (BOOK_CROWN_ENABLED, default OFF until Phase 2 clears).
/api/books repointed to the snapshot-locked store (fallback odds cache),
nameKey-matched; `source` field is the deploy fingerprint.
HELD unchanged: dedupeProps, snapshot dedup, selector, grade, champion,
challengers, ranking, edge_pct/ev_pct. UI routing of BookComparison + crown
treatment deferred to post-measurement (gated on Phase 2). Full suite 3834 green,
web build exit 0.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01VsztNChZ7vEvSR61AuMhD1
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builtbykev
|
914a057611 |
proj-v1 book-implied: raw odds → de-vigged FAIR (fix self-flattering basis)
proj_book_implied derived from raw book_odds — VIG-INCLUSIVE. A -110/-110 market
implies 52.4%/side (104.8% sum); fair is 50%. Comparing our P against raw book
overstates the book on both sides, biasing the handicapper test IN OUR FAVOR; on
juiced longshots (the Judge HR -18.5pt case) much of that "edge" was vig, not
disagreement.
Fix (fenced to proj-v1's stored comparison basis): proj_book_implied now derives
from DE-VIGGED FAIR via the grade's g.fair_prob — the SAME multiplicative de-vig
the triplet uses (utils/devig.js), so the basis matches the product's shown fair.
Expressed on the OVER basis (under props → 1 - fair) to match our stored P(≥rung);
traded-rung ladder book_implied likewise. HONEST-NULL where fair is uncomputable
(one-sided market, ~14%) — NEVER a raw-book fallback (that would recreate the vig
bias on a subset and mix two bases in one ledger). proj_factors records
book_implied_basis ('fair_multiplicative'|'none').
Phase 0 (prod-verified): fair reachable at store point (g.fair_prob on the grade,
no threading); 86% batting coverage; method = multiplicative/proportional.
Phase 2 FLAG: multiplicative de-vig mis-splits vig on juiced longshots (favorite-
longshot bias), so a longshot fair still carries known method bias — flagged
per-row (longshot_devig_caveat); a better de-vig (Shin/power) is a separate item.
Phase 3: version bumped proj-v1 → proj-v1.1 so pre-fix (raw-book) and post-fix
(fair) rows never silently mix — the projection model is byte-identical, only the
basis changed; pre-fix rows can't be recomputed (only the graded side's odds were
stored). Champion + arch-v1 + contact-v1 + proj-v1's other columns untouched.
proj suites 26/26.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj
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builtbykev
|
e96b0dbb6d |
proj-v1: book-implied from book_odds (grades carry odds, not fair_prob)
The live fingerprint showed proj_book_implied null on every real row: grades carry book_odds/locked_odds (e.g. -264) but NOT a de-vigged fair_prob, so keying the book comparison off fair_prob yielded null. The book ODDS are exactly "the book's implied probability" the handicapper test needs. Now proj_book_implied + the traded rung's book_implied derive from americanToImplied(book_odds), expressed on the OVER basis (under props → 1 - implied) so it's directly comparable to our P(≥rung). Vigged (a known offset the ledger measures both sides of). proj-v1 suites 24/24. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj |
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builtbykev
|
316b79733e |
proj-v1 sanity fixes (caught in the real-data induction)
1. matchupRead fly-ball signal: the batter metrics `gb_pct_bb`/`fb_ld_pct` are MISLABELED — they're exit velocities by batted-ball type (Judge fb_ld_pct = 100.3 mph, not a rate), not ground/fly RATES. Switched fly-ball lean to avg_launch_angle (league p10/p50/p90 = 7.1/13.9/20.1°), the correct signal. 2. Absolute rate now fits the FULL season (recency-weighted), not a 20-game window: the window under-sampled rare stats — Judge HR projected 0.11 vs his 0.28 season rate (a fake -32pt edge). Now point=0.27 (matches season); the last-5-2x recency lean is preserved. Post-fix induction (real statsapi logs + real statcast): Judge HR 0.27 (P>=1 0.235 vs book 0.42 -> flags the juiced over), Judge TB P>=2 0.548 vs 0.48 (+6.8pt), thin-hot 3-game P>=1 0.726 / P>=3 0.164 (credible low, thin high), .300 hitter != 3.0. proj-v1 suites 23/23. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj |
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builtbykev
|
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
|
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
|
125919f86a |
Scanner reskin: amber → blue boundary channel + build never-built S6/S7 states
Semantic COLOR fix, not cosmetic. The S6/S7 build predated the current Scanner
States spec: it used AMBER (the quarantine / model-suppressed channel) for the
"no market / line not priced" case, telling users "model suppressed" when the
truth is "the board never priced this." Corrected to the HANDOFF Session-3
blue-boundary law: BLUE (--priced-out #8FB2DE) = no-market boundary; amber stays
QUARANTINE; red stays REFUSAL.
Phase 1 (reskin): NoMarketState → dashed BLUE void box + blue header/copy; the
S7 rows → spec format (o 27.5 · BK −114 · ◆ −105 · OPEN READ ▸) at 44px,
390-legible. Input-area surfacer pills reskinned to the blue channel too.
Phase 2 (never-built states, only those Phase 0 confirmed against live data):
- GREEN CTA with LIVE player count ("PLAYER · N PRICED PROPS ▸"), degrading
honestly to the board path ("N PROPS LIVE · TONIGHT'S BOARD ▸") at 0 — count
from the SAME fresh index as the rows (pricedCountForPlayer), can't disagree.
- CASE A none-priced DEFAULT: "WE PRICE THESE FOR [player]" — the player's other
priced stats (pricedStatsForPlayer, filter by nameKey).
- Typed-line-mismatch blue fact line ("o X ISN'T PRICED · NEAREST ↓").
FLAGGED / not built (no shells): Case C off-slate quiet-stop needs schedule/
roster membership the pricedLines index doesn't carry (out of the presentation
fence). Spec CONTRADICTION: Case B says "fair previews amber," but the law
reserves amber for quarantine — fair renders NEUTRAL ◆ (blue-dim), not amber, to
avoid blurring the channel.
Free-tier gate VERIFIED before rendering FAIR: fair_odds is the de-vigged MARKET
price (valueState: "never hide the honest fair number"), NOT the gated
model_odds — no paid leak. Carried through indexPricedLines (additive; keying/
refresh/onPick/stale-tap all unchanged — the proven S7 data path is untouched).
Scan A byte-identical; PRICED_NUDGE_ENABLED still the kill switch; reversible.
Build exit 0; priced + parity suites green (67).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj
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builtbykev
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83e9da3663 |
Consistency classifier: CV → index of dispersion for low-mean counts
The A/D investigation found CV (std/mean) is scale-broken on count data —
for a Poisson-ish stat cv ≈ 1/sqrt(mean), so EVERY stat with mean < 4 blew
past the boom_bust cutoff regardless of behavior. The S63 stopgap made those
return 'unknown', which silently ate a real +1.0 consistency signal on every
MLB batting prop — steady low-mean hitters never got their earned factor.
Fix, fenced to the low-mean branch of consistencyScore (the only branch that
was returning 'unknown'): classify with the index of dispersion (variance/mean,
Poisson baseline 1.0) — the scale-appropriate, UNBIASED statistic for counts.
mean ≥ 4 keeps the NBA-calibrated CV path BYTE-IDENTICAL (zero NBA blast
radius). This is a bug CORRECTION, not threshold loosening: the CV thresholds
and the engine1 ±1.0 delta are unchanged.
Bands (asymmetric around Poisson 1.0, since counts are naturally mildly
over-dispersed): iod<0.60 elite / <0.85 reliable (+1.0) / ≤1.30 volatile
(neutral) / >1.30 boom_bust (−1.0). Sample floor MIN_GAMES_FOR_IOD=8 so a
thin sample abstains ('unknown') — no small-sample guess.
Validated on real 10-game logs (two-sided): Kwan hits 0.67 / Alonso hits
0.78 → reliable (RECOVERED); Alonso TB 2.57 / Henderson hits 1.33 → boom_bust
(no false consistency); HR mean 0.1 → 1.0 → neutral. Direct engine1 proof: a
strong steady prop that grades B+ today reaches A- once the +1.0 fires; a
boom-bust bat stays B (no inflation). A- now emerges NATURALLY from a real
recovered factor. Standing two-sided test pins all three directions.
Forward-only (settled grades are locked in the ledger, never re-graded).
Emitting A- ≠ proving A- — the A-tier record accrues from emission, still
measurement-gated. Full unit suite green (4 pre-existing redis/timing flakes
pass in isolation); web build exit 0.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj
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builtbykev
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3440738d9e |
Landing hero → bundle visual system; claims filtered to earned only
Migrate the Landing hero (Landing-only component; LiveHeroProp/triplet untouched) to the design bundle's visual language: mono "SPORTS INTELLIGENCE TERMINAL" eyebrow, tightened 56px/800 headline "Every line, graded before you bet it.", dual mono CTAs (OPEN THE TERMINAL / SEE THE PUBLIC RECORD), proof chips. Claims audited against the held list — the bundle's marketing copy carries claims we have not earned; those did NOT ship: - "CLV-VERIFIED" chip + "verified against closing lines" — HELD (C4 broken) - "312 props / 47 games" count — fabricated demo → ABSENT (no count) Shipped copy is earned only: pre-graded, edge-ranked, settled in public, misses included; PUBLIC LEDGER / MISSES INCLUDED / 5 FREE READS chips. HELD + FLAGGED for a design pass (fabrication-backed, no honest designed state — check-don't-freelance): the edge-board demo (A+/A don't emit), the "grades calibrate · A+ hit 80%" claim (calibration unmeasured), and the tier-record band (real data is B/C-only, no ROI). Not built with fake data. Tokens via var(--g-a/--void/--border/…) with bundle-hex fallbacks (documented-intentional pattern). Build exit 0; parity QA green. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj |
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builtbykev
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d879a10dd3 |
Design bundle (2): current source of truth — Scanner States + blue-boundary law
Reference material only, ZERO product code. Adds Vyndr Scanner States.dc.html (S6/S7 spec) + HANDOFF Session 3 blue-boundary-channel law (#8FB2DE = the honesty channel: priced-out / no-market / line-not-priced). This is the diff baseline for the design-migration arc. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj |
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builtbykev
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9a91837f63 |
STATE: Session 80 — S7 nudge freshness completed; premise corrected report-first
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj |
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builtbykev
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4f3f433aae |
Complete S7 priced-line nudge: freshness on a long-open page + reversible gate
REPORT-FIRST correction. This order's premise — "S7 is a shell that doesn't update per selection" — is not what the code does. pricedForSelection is a useMemo on [pricedIndex, selectedPlayer, stat] and setSelectedPlayer/setStat fire on every user pick, so the chips already update per selection, and the prior session's verification of that stands. The genuine gap was FRESHNESS: the snapshot fetch depended on [sport] only, so pricedIndex was fetched once per sport-change and never refreshed. The pricing cron re-prices at five UTC hours, so a scanner left open across a cron boundary surfaced hour-stale priced lines. That is the real defect, and the only one fixed. FRESHNESS. The fetch is now a refreshPriced callback re-run when the held snapshot is older than PRICED_STALE_MS (30s, matching the /api/snapshot cache) at the moment of use — on selection change and on window focus — so a long-open page never shows a stale line. Sport change still clears the index first, so the old sport's lines never flash. STALE-TAP was already safe and is unchanged: the scan submit re-fetches the live snapshot server-side, so a chip that's gone stale between render and tap either lands on a real triplet (still priced) or degrades to the honest empty state (rotated away) — proven in the prior session and re-confirmed here (an off-snapshot line returns no market and shows the empty state). REVERSIBLE GATE. The whole nudge sits behind one PRICED_NUDGE_ENABLED flag: false empties the surfaced set, so the scanner falls back to S6's link-only empty state with the chips gone. Shipping enabled only after the cases are proven this session; the flag is the instant revert lever. DISPLAY-LAYER ONLY. Only scan/page.tsx changed. GradeResultCard, PriceTriplet, gradeAdapter, valueState, both scan routes and the pure pricedLines helper are byte-identical — Scan A and the scan-submit resolution are untouched, and the change is independently revertible. Tests 3765 passed / 303 suites, web build exit 0. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj |
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builtbykev
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33d72e38f9 |
STATE: Session 79 — read-card no-market empty state + priced-line surfacer, live
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj |
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builtbykev
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e311f53738 |
Read-card scan: honest no-market empty state + surface real priced lines
The Session-78 diagnosis stands: the join works, and a marketless scan rightly
shows no triplet. This makes that absence legible and points the user at what IS
priced, without fabricating a market.
PHASE 0 gate — design-check, reachability, timing, all clear. Design-check: the
bundle has the triplet's own REFUSAL language ("we'd rather show nothing than a
number we can't stand behind") as the honesty precedent, and a designed
EmptyState component whose actions give a path forward — so the empty state is
built in the established visual language, not freelanced. Reachability: the
scanner already fetches games/odds/search per selection; the snapshot is one
more public, 30s-cached fetch per sport, re-run when the sport changes.
Staleness: the snapshot rotates 5x/day and every scan re-validates the market
server-side at submit time, so a surfaced line that goes stale degrades to the
empty state on tap rather than a vanishing triplet — the stale-tap guard is
inherent, not bolted on.
Reversibility was the design constraint. The working card, price triplet, grade
adapter, valueState and the scan route are BYTE-IDENTICAL — a test asserts none
of them even reference the new empty state. Everything new lives in two added
files (lib/pricedLines.js, components/vyndr/NoMarketState.tsx) and additive
blocks in the scan page. Removing them leaves the Scan-A path untouched.
Non-fabricating by construction: indexPricedLines only keeps snapshot rows that
carry a real book price, keyed by exact player+stat via nameKey. A different
stat priced for the same player surfaces nothing for the picked stat; an
off-slate player surfaces nothing; nothing is suggested, interpolated, or
rounded to a nearest line. The empty state shows no market numbers of its own —
only real priced lines as one-tap chips, or a link to the live board when there
are none.
Framing is help, not restriction: a "PRICED TONIGHT" chip row sits under the
free-typed line input, and the scanner still accepts any player, stat and line.
Tapping a chip pre-fills the priced line and re-scans it — the market is
re-resolved server-side, so the tap either yields a real triplet or degrades to
the honest empty state.
Path forward, not a wall: a marketless scan no longer dead-ends in blank space.
It states truthfully that the board didn't price that line, keeps the grade, and
routes the user to the priced lines for that exact player+stat or to tonight's
board.
Tests 3760 passed / 303 suites, web build exit 0.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj
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builtbykev
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4c9707ffbb |
Platoon polarity: VERIFIED correct, pinned by a standing test
Report-only verification of the two unproven claims from the Session-77 wiring, which fired platoon on synthetic split-less hitters where the K=600 regression zeroed the multiplier and masked both direction and resolution. No product code changed — this adds one standing regression test. FIXTURE — Yordan Alvarez (LHB), real 2026 splits, deep both hands: 115 PA vs LHP at .529 slg, 327 PA vs RHP at .695, overall .652. The regression leaves a material multiplier both ways (0.97 vs LHP, 1.023 vs RHP), so unlike the last test this fixture can actually reveal direction. RESOLUTION — verified on the live slate that the pitcher-hand attached to a hitter is the OPPOSING team's probable, not his own. CLE (home) resolved to Minnesota's away starter 696070; MIN (away) resolved to Cleveland's home starter 800048. The chain — hitter's team, the game, the other team, that team's probable, that pitcher's hand — is correct, and it is pinned independently of direction because a backwards resolution is invisible on a neutral hitter. DIRECTION — deterministic L-vs-R on the frozen Alvarez fixture. Facing RHP nudges UP (1.023) because he slugs .695 there, above his .652 overall — a favorable opposite-hand matchup, exactly what platoon theory predicts for a left-handed bat. Facing LHP nudges DOWN (0.97). The two move opposite directions, and crucially the SPECIFIC sides are asserted, not merely "opposite" — a mirrored-but-inverted implementation would put RHP below 1 and fails here. Both- backwards is ruled out. The test also pins a REVERSE-split hitter, Brandon Nimmo, who hits better vs LHP than RHP. His multiplier goes up vs LHP, following his real numbers rather than a hardcoded LHB-vs-RHP assumption — proof the sign is data-driven, which is the correct design. VERDICT: PASS. Resolution correct, direction correctly signed against both the real split and platoon theory. Pinned by tests/unit/platoonPolarity.test.js so the polarity cannot silently regress — the opp_rank_stat lesson applied. Tests 3750 passed / 302 suites. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj |
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builtbykev
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535a7b70ea |
STATE: Session 77 — dormant adjusters wired; env non-null proven, ledger row pending
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj |
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builtbykev
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7b25d97891 |
Wire the four dormant adjusters live — pure input-wiring
Verified state going in: parkBase, weatherMod and platoonSplits were called by nothing, and env_multiplier was non-null on zero rows across four orders. The adjusters were correct in isolation and starved of inputs. This gives them their inputs and changes none of their internal logic — the five adjuster files are byte-identical after this commit. PHASE 0 GATE — all three inputs are available at snapshot build, and the two join keys already existed. Venue: always, on every schedule game object. First-pitch: always, gameTime on the same object. Opposing-pitcher hand: present once the probable is declared, via the pitchers endpoint's pitcherId joined to statsapi handedness — 15 of 15 games declared this afternoon, though morning locks precede declaration and those props honest-absent on platoon, correctly. The batter-handedness join (statcast bats) and the MLBAM id were already on each grade from earlier sessions. environmentContext.js is the wiring, kept separate from the adjusters so they stay pure. It fetches once per snapshot: the schedule (team to venue, gameTime), probable pitchers (team to opposing pitcher id), one batched handedness call, one Open-Meteo forecast per home park, and batter splits per graded hitter. Park coordinates for 30 parks live here as public geometry, the same class as the dome list and centre-field bearings already in weatherMod, rather than inside an adjuster. Everything is best-effort: a missing venue drops park and weather, an undeclared pitcher drops platoon, and any fetch failure degrades that prop to archetype-only rather than breaking the pipeline the adjusters are measured inside. attachChallenger becomes async and takes a per-grade contextFor that returns the environment coefficient (park_base x weather_mod, composed) and the matchup (platoon). Point-in-time holds: the weather is a forecast for first pitch fetched now, and the split is the hitter's line entering the game — neither reads a settle-time value. Attribution is independent. env_multiplier, env_park_base, env_weather_mod and env_weather_state land in their own ledger columns, and challenger_adjustments keeps every axis — archetype, environment, matchup — as a separate entry, so when volume accrues each of the four can be measured for its own marginal contribution rather than as one blended delta. The combined move stays bounded, tested on the worst case: a Coors slugger with wind out and a favourable platoon, all at once, still moves under 12 percent, because every layer is capped and the total nudge is clamped. Stacking leans, it does not compound into a re-forecast. Non-MLB honest-absents entirely — park, weather and platoon are MLB-only today, so a WNBA prop gets no environment and no matchup. The champion is untouched throughout: p_win is read, never written, the served snapshot payload is still the enriched object, and a test confirms p_win passes through byte-for-byte while the challenger moves. Tests 3741 passed / 301 suites, web build exit 0. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj |
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builtbykev
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2adf192d98 |
STATE: Session 76 — platoon regressed; plumbing gap now four orders old
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj |