PHASE 0 GATE — the answer is BOTH, and the important half was already here.
A STATIC FanGraphs park-factor table has existed since Session 15
(src/data/parkFactors.js) and computeFeatures already consumes it, so park is
not a new idea in this codebase. What was missing is OUR derivation. I nearly
built a second source of truth before finding it; the new service lives at
src/services/parkFactors.js and the two are deliberately distinct.
That discovery changes the point of this order rather than just its scope. If
the champion already sees a park factor, adding one to the challenger risks
double-counting — which is exactly the redundancy the Session-72 harness exists
to catch. So park ships as a NOMINATED CHALLENGER whose job is to be tested for
marginal contribution, not as an assumed improvement. Checked and worth noting:
the static table reaches computeFeatures but NOT probabilityEstimator, so it
does not currently touch p_win at all.
DERIVATION, not ingestion. statsapi gives every game with venue, linescore and
scoringPlays in one call per date range — and since every home run scores at
least the batter, HR totals are fully recoverable from scoring plays. Derived
from 5,055 real games across 2022-2025: Coors tops the run environment at
1.099, Dodger Stadium tops home runs at 1.106, Oracle Park and PNC suppress
them at 0.923 and 0.917. Eighteen parks cleared the floor, eighteen did not and
are honestly absent.
COMPOSABLE BY CONSTRUCTION — the architectural point. Park emits a multiplier
around 1.0, never an additive nudge, because weather has to modulate it next
order: effective = park_base x weather_mod. Additive terms do not compose
correctly (a 5% park and an 8% wind are 1.05 x 1.08, not +13%), and the
challenger converts the multiplier to log-odds so stacking stays correct. A
test multiplies a placeholder weather term onto the park base to prove the shape
composes with no rearchitecting.
DIRECTIONAL BY PROP-OWNER: home_runs and home_runs_allowed both key off hr_base
in the same direction, because the sign lives in the STAT, not the park. Coors
inflates the hitter's home run prop and the pitcher's home-runs-allowed prop
identically.
THREE HONEST STATES, deliberately distinct. Absent (thin sample, adjust
nothing), present (adjust), and weather_na for domes — where the park factor
STILL APPLIES because a dome has a real run environment, and the flag exists so
next order's weather modulation correctly does nothing there. N/A is not absent;
conflating them would either drop a valid park factor or apply wind indoors.
Structural breaks: a season deviating past the threshold starts a new regime
only if the FOLLOWING season confirms it — one odd year is noise, two
consecutive years on the same side is a rebuilt park. Only post-break seasons
are used, so a humidor or moved wall cannot be diluted by the stadium that
preceded it. Factors regress toward neutral by sample size, so a two-season park
cannot assert a Coors-sized coefficient, and fine conditioning stays unavailable
until its own larger floor.
Tests 3669 passed / 297 suites, web build exit 0.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj
PHASE 0 GATE — historical out-of-sample testing is NOT available, and the reason
matters. statcast_aggregates is overwritten nightly by design (Layer 1 is a full
re-pull upsert), so it holds season-TO-DATE numbers with no point-in-time
history. Classifying a player for a 15 July game using today's aggregate would
feed the model games from 15-21 July — look-ahead leakage, and the resulting
"out-of-sample" verdict would be worthless. The harness therefore reads the
archetype vector RETAINED at grade time (Session 70's instrument) and runs
FORWARD-ACCRUAL, not historical. Reported rather than worked around.
CANONICAL NAMES ASSERTED. Every mapping references the axis keys the classifier
actually emits, and a test walks both maps against BATTER_AXES / PITCHER_AXES.
A key that does not exist would look active and never fire — a mapping that
appears wired while silently doing nothing is the exact failure this guards.
TIER 1 IS LIVE, tautological and directional: PUNCHOUT/WHIFF raises strikeouts;
SINKER/SEAM lowers home runs allowed and FLY BALL/ELEVATOR raises them (a ball
on the ground cannot leave the park); SURGEON ARM/PINPOINT lowers walks allowed;
SLUGGER/BOMBER raises total bases and home runs; TECHNICIAN/SURGEON raises hits
and lowers strikeouts; GRINDER/SNIPER raises walks. Each adjusts only its named
stat, mirrors exactly on the under side, and leaves an average player untouched.
SPEED IS HONESTLY ABSENT. BURNER/stolen-bases has no axis to key on — SB is a
statsapi field that never reached the aggregate store, so Layer 2 shelved it.
The mapping is an empty object rather than an invented one.
THE TIER-2 HARNESS tests MARGINAL CONTRIBUTION, not correlation. A ground-ball
arm obviously correlates with fewer home runs; the question is whether the
archetype explains the PROJECTION'S RESIDUAL (outcome minus p_win). If the
projection already knows it, the residual carries no signal and the mapping is
rejected as redundant — that hurdle is what catches double-counting. The split
is by DATE, never random, because rows from one game share a pitcher, a park and
a lineup and would leak across a random split. Direction is validated from the
held-out data and a contradicted sign is REJECTED, never silently flipped to
whatever the data says, which would be fitting noise.
LIFECYCLE ENCODED — nominated, live, claimed. A mapping that survives runs live
and is measured; only the quantified public claim waits for the ledger. Nothing
sits dark.
One fixture bug worth recording: my first synthetic generator aliased the
carrier selector against the outcome draw and manufactured a 0.038 effect where
the generator had put zero. The harness rejected it correctly — it just gave the
sign reason instead of the redundancy reason, which is how I found it. The draw
now uses a coprime modulus.
Real candidate run end to end, GROUND-BALL to hits-allowed: INSUFFICIENT, 0 of
200 settled rows, because no settled row carries p_win yet (Session 70's
instrument starts recording at the next new lock). That is the correct verdict
and the expected one.
Tests 3654 passed / 296 suites, web build exit 0.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj
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
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
The data foundation for the archetype and projection layers, built as the
pattern every sport inherits. Layers 2 and 3 are not touched.
PHASE 0 GATE — both match rates measured live, both 100%. Batters 40/40;
PITCHERS 66/66 across five real rosters (CLE, DET, MIN, NYY, LAD) joined by
MLBAM id against the 713-pitcher Savant feed. Zero honest-absent on identity,
because the join is an integer both systems use natively — and the snapshot
pipeline already stores it per graded row.
SOURCE — five Baseball Savant CSV leaderboards, free and public, pulled with
axios and the CSV parser savantAdapter already runs in prod. pybaseball is
deliberately NOT used: it is an MIT wrapper over these same URLs, and adding it
would reintroduce a Python runtime in a stack where the existing Python service
is already offline. min=1 on every feed, not Savant's default min=q, so the
long tail arrives and OUR minimum-sample gate decides what is thin — explicit
and testable rather than silently dropped upstream.
Measured: 1,354 rows per season (604 batters, 750 pitchers), all five feeds in
about five seconds. Pitcher mechanism includes arm angle, GB/FB/LD, chase and
whiff; batters get exit velo, launch angle, barrel and hard-hit, chase and
z-swing. Handedness rides in free on the movement feed (677 pitchers); batter
handedness stays absent pending a roster join rather than being guessed.
BACKFILL AND REFRESH ARE THE SAME CALL — a full re-pull upserted on
(sport, season, source_id). Idempotent and self-healing: a missed night
self-corrects on the next run, with no incremental who-played bookkeeping to
drift out of sync. At 1,354 rows the simple thing is also the robust one.
HONESTY RULES, each with a test: a metric the feed did not carry is null and
never 0; a thin sample is STORED and flagged rather than dropped or inflated,
because thin and missing are different claims; an unjoined player is stored
with a null player_key and joins later; and if every feed comes back empty the
job REFUSES to write, so a bad night can never blank a good table.
Freshness is treated as a truth property. updated_at on every row, and the
scheduler pages on a failed run AND on silent staleness — a job that stops
being scheduled never produces a failure, so staleness has to alarm on its own.
Never-built is deliberately not stale: different condition, different fix, and
paging on a fresh install teaches the operator to ignore the alarm.
Nightly at STATCAST_HOUR_UTC (default 11 UTC, after every game is final), kill
switch STATCAST=0, and induce-able at POST /api/internal/statcast/refresh with
a freshness probe at /statcast/status — we verify a refresh by running it, not
by waiting for the slot.
Migration 030 applied. Promoted columns for the classification-critical metrics
plus a metrics JSONB carrying every raw field, so Layer 2 can reach something we
did not promote without a re-ingest. Raw per-pitch stays out of Postgres on
purpose: one season is ~0.85 GB against a 500 MB plan ceiling, and it is
re-pullable from the free source if Layer 3 ever needs it.
Pattern documented in docs/MECHANISM-DATA.md for NBA tracking and NFL Next Gen.
Tests 3581 passed / 292 suites, web build exit 0.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj
Live induction on the deployed landing page caught this; markup review and the
unit suite both passed it. With the model leg stripped for anonymous visitors,
LiveHeroProp forwarded book/fair/model/ev/quarantine to PriceTriplet but NOT
model_price_locked, so deriveValueState fell through to the missing-model-price
branch and the card rendered "MODEL READ WITHHELD" — the quarantine state,
whose copy says we suppressed our own price because a leg is poisoned. Nothing
was poisoned. The real reason was the paywall, and the two must never share a
face: one says our data is untrustworthy, the other says you don't have this
tier.
Now forwarded, with a test asserting both the separation in deriveValueState
and the forwarding at the call site.
Tests 3559 passed / 291 suites, web build exit 0.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj
The landing hero reads the snapshot from Redis DIRECTLY via heroPropService,
so it never passed through routes/snapshot.js and was still serving model_odds,
ev_pct, value and takeable to anonymous visitors after the first fix. Same
strip, same tier resolution, same private-cache rule for authenticated callers;
the Next proxy now forwards the bearer token.
PRODUCT CONSEQUENCE, FLAGGED RATHER THAN BURIED: the landing hero is served to
anonymous visitors, so it now renders BOOK and FAIR with the model leg LOCKED
instead of the full triplet it showed this morning. That follows the stated
free-tier rule exactly, but it does trade a strong marketing moment (VALUE
+21.1% VS FAIR on the shop window) for consistency of the gate. Reversing is
one line — add 'model_price' to the free tier in src/config/tiers.js, or
special-case the hero route — and is a product call, not a correctness one.
Tests 3557 passed / 291 suites, web build exit 0.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj
PHASE 0.5 GATE — the three checks, and one correction.
`fairLine` does not exist. Zero hits across src/ and web/src. Option A as
written had no referent, but it resolves better than feared: `fair_odds` is
already a real de-vigged American price on every graded snapshot row, so there
is nothing to derive.
Gate 1 (is it a price): PASS. fair_odds is American odds from
impliedProbToAmerican inside devigTwoWay; fair_prob is the probability. Both
distinct from `line`, the stat threshold.
Gate 2 (numeric match): PASS, 8/8 exact. Recomputed fair_odds and fair_prob
independently from the stored raw over/under prices; every value matched the
stored one to the integer and to 3dp. Same de-vig, same numbers the component
was proven against.
Gate 3 (poison independence): PASS, and proven on the quarantined cohort
itself. devigTwoWay's inputs are (over_odds, under_odds) — market prices
only, no model term is reachable. The 8 rows recomputed above are all
wrong_opponent_grade rows, and their fair prices reproduce exactly from the
market. The poison is in the grade, not the price. Quarantine therefore
suppresses the MODEL leg only; the fair leg stands, as designed.
THE LEAK WAS REAL AND ALREADY LIVE. GET /api/snapshot/:sport is public and
unauthenticated, and it was serving model_odds, p_win, ev_pct, value and
takeable to anonymous callers on every graded row — 25 of 25 on the live wnba
board. The Session-66 gate on /api/analyze was bypassed entirely by this
endpoint.
The strip covers more than model_odds, because model_odds is not the only way
to read the model price: p_win IS the price in another base, and ev_pct is
INVERTIBLE — ev is a function of p_win and book_odds, and book_odds is public,
so leaving ev behind hands the price over. All five model-derived fields go.
book_odds, fair_odds, fair_prob, overround and devig_method stay on every tier:
the fair leg is never the paywall. Rows that keep a book+fair pair are stamped
model_price_locked so a gated price is never mistaken for a missing one.
Tier comes from resolveTierFromRequest, which reads a bearer token when one is
present and otherwise returns 'free'. It FAILS CLOSED on every error path, so a
resolution failure can only ever withhold the price. The response now varies by
entitlement, so the /:sport handler downgrades Cache-Control to private for
authenticated callers and the browser proxy forwards the bearer token —
otherwise a CDN could hand a paid payload to an anonymous viewer, or every
request would look anonymous and paid users would lose the leg.
READ CARD — a manual scan carries no market. The request is {player, stat,
line, direction}, so the engine has no over/under prices to de-vig and
book_odds/fair_odds are legitimately absent from its response; that is why the
triplet was hidden there. lookupSnapshotPrices recovers them from the
pre-graded snapshot via the same cache-only read this route already performs
for locked odds and team. The join is exact on player + stat + line + side
(fair_odds is side-specific), and returns nothing unless book and fair are BOTH
present — a user-chosen line the board never graded has no market attached, so
the triplet stays hidden rather than borrowing another line's price.
FAIR-LEG ABSENCE, measured before shipping: 636 graded rows, 636 with book,
636 with fair, 0 one-sided. Absence rate 0.0%. The hero number is not a
sometimes-number on current data.
Tests 3556 passed / 291 suites, web build exit 0.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01VCNgGSt5qvcLxaeQqa7Zpj
Two Truth-Law fixes found by auditing the product logged-out.
FIX 1 — /u/[handle] claimed a "CLV-verified record" with "closing-line
value included" while ZERO closing-line value renders there. Verified
live: GET /api/profiles/vyndr returns beat_close_pct null (gated behind
CLV_CAPTURE_RELIABLE, unset while C4 is open). Eight instances found —
two of them (the OG + portrait "CLV-VERIFIED RECORD · 30D" eyebrows)
only by the post-removal residual sweep; two more printed the claim in
exactly the no-record branch.
Copy now describes what the page shows. The gated CLV-VERIFIED badge and
the BEAT CLOSE figure are removed from the public profile, OG card and
portrait card. DISPLAY ONLY: beat_close_pct, clvCaptureReliable() and
the whole CLV data path are untouched, and the earned directional badge
stays Analyst+Desk. The claim returns when CLV genuinely renders here.
Also fixes the doubled "· VYNDR · VYNDR" title (layout's '%s · VYNDR'
template already supplies the suffix); verified on composed output by
serving the build and reading the real HTML, not on source.
FIX 2 — the player page's FORM was `70 + 4 × (count of tonight's graded
props)`. Nothing on the HTTP path ever sets stats.form, so that fallback
WAS the live number: Josh Bell's "74" is 70 + 4×1 prop, confirmed
against his live payload. MATCHUP was gradeFromForm(that number), with a
hardcoded 'B' on the no-archetype branch — both fabricated letters with
no opponent input on the path. Systemic: buildIntel is the unconditional
path for every player and sport.
FORM and MATCHUP now render "—" (kind 'plain', so no bar width or colour
is computed off a null). gradeFromForm is deleted and the prop count is
no longer passed into buildIntel. computeFormScore's hardcoded 75 now
returns undefined. Induced across MLB/NBA/WNBA: all render cleanly, and
real values (USAGE 3.6 AB/G, REST B2B) still render.
Neither form value feeds the grade — engine1 reads raw l5_avg/l20_avg
against the line and never a form key; buildIntelFields decorates the
already-graded object. Grade inputs are byte-identical.
Held (needs a per-sport headline-stat design call): a real player-level
form metric + label disambiguation.
Tests 3491 passed / 289 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
MLB statsapi + WNBA ESPN live boxscores -> per-player current values
(live:{sport}:{date} TTL 90s, /api/live/:sport + Next proxy). Pure
propState math (HIT / ON PACE / NEEDS N / HOLDS / LINE PASSED — never
red in-progress), attachLiveProgress strip join on nameKey+statType,
proximity-to-hit slate float, StatStrip LiveTracker in the ROW-GRAMMAR
outcome slot (spec amended + lock test updated). Grades never change
in-game — tracking, labeled as such. 2698 -> 2757 tests, web build 0.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Product overhaul core — the two transformative, differentiated systems:
Self-learning loop (Phase 2): outcomeService settles locked snapshot grades
against real MLB Stats API results → hit/miss/push, rolling accuracy by grade
tier (30d window). Idempotent, injectable, unit-tested. New GET /api/accuracy +
/api/ledger/accuracy + internal settle triggers + cron hook. AccuracyBadge
(dashboard/scan/landing) is honest — "LEARNING" below MIN_SAMPLE, never a fake
number. Settled HIT/MISS chips overlay the live slate.
Real-time layer (Phase 1): Slate silent 60s auto-refresh (no flash, no wipe on
transient blips) + "SIGNAL LIVE · UPDATED Xs ago" freshness strip; Ticker LIVE
badge that flashes on fresh events.
Landing (Phase 3): TopSignals shows tonight's real top-3 A-rated grades + live
accuracy — the product shown, not described.
Founder pricing: FOUNDER_CODE_EXPIRY default 2026-06-30 → 2026-12-31 (had
lapsed, disabling every founder code + the ClaimMeter pitch). That expiry — not
a tier change — was the real cause of the 4 stripe test failures.
Backend 2255 (4 failing) → 2274 (all green; +19 new, +4 fixed). Web build exit 0.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
P1 name edge cases (BOTH playerName.js copies, kept identical):
- normalizeName strips hyphens (display+key): "Jung-hoo Lee" === "Jung Hoo Lee".
- nameKey strips single-letter MIDDLE tokens: "Josh H Smith" === "Josh Smith"
(keeps first+last; real middle names + collapsed initials untouched).
- richie -> richard added to NICKNAMES.
P2 polish:
- Team Hub names normalized at the source (teamService.getTeamHub) so
"J.C. Escarra" renders as "JC Escarra" like the dashboard.
- snapshotService dedup keeps the highest-confidence GRADE but the richest
DISPLAY (accented "José" over "Jose") so prop rows match the pitcher line.
- correlationWarning names the game: "2 legs from the same game (NYY @ BOS)".
Backend 2246 -> 2255 tests (+9), 194 suites. Web build clean (exit 0).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
The link preview still showed engineer-speak ("Bayesian intelligence", "kill
conditions") because the OG meta tags were never updated after the S44 landing
cleanup.
- layout.tsx: de-jargoned the openGraph + main description + titles → "Pre-graded
player props with proprietary archetypes. Correlation-aware Parlay Lab.
Real-time line movement tracking. Built in Detroit." (Used "proprietary
archetypes" not "45" — codebase has 41.)
- NEW app/opengraph-image.tsx (+ twitter-image.tsx re-export): dynamically
generated 1200x630 card — VYNDR wordmark, "The books have every advantage. /
We built this to give it back." + feature row. Node runtime (not edge —
self-hosted standalone). Both routes prerender to a real PNG.
- Removed the stale /og-image.png metadata ref so the file convention owns the
image (no duplicate og:image tag).
Backend 2239 -> 2246 tests (+7), 193 suites. Web build clean (exit 0).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Trace-first: the normalizer functions were correct (S47) but raw names still
flowed through paths that skipped them. Fixed each leaking path.
- 2a (source chokepoint): snapshotService.runSnapshot normalizes each grade's
player to the de-dotted display AND dedupes to one grade per nameKey|stat
(highest confidence) before writing grades:{sport} + snapshot:latest. Every
consumer (GameCard, Explore, leaders, profile) now gets clean merged names.
- 2b: buildPlayerStripsFromProps dedupes a player's props by stat (graded >
awaiting) → one row per stat (kills "Ks 5.5 AND Ks 3.5" variant dupes).
- 2c: scan tonightsPlayers grid groups by nameKey, displays normalized name.
- 3: profile VYNDR INTELLIGENCE "+0%"/"—" was buildIntel's defaults (separate
from the grade card's buildIntelFields, which already works). resolvePlayerStats
now attaches real usage (AB/G) + rest (B2B/Xd); buildIntel renders them; REST
default is now "—".
Backend 2149 -> 2156 tests (+7), 181 suites. Web build clean (exit 0).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
- Name normalization completed: NICKNAMES table (Matt↔Matthew, Mike↔Michael...)
resolved in nameKey, parenthetical team-tag strip "(STL)", verified accent-fold
(Iván/Ivan, José/Jose). Slate strip now DISPLAYS the normalized de-dotted name
("AJ Ewing" not "A.J. Ewing") via buildPlayerStripsFromProps.
- Complete MLB VYNDR INTELLIGENCE: mlbGameLogFeatures derives rest_days (days off
between latest games; 0=B2B) + ab_per_game (usage). buildIntelFields renders
usage as "X AB/G", rest as B2B/Xd, matchup from bvp_advantage fallback.
- Ticker SCAN dedup: pushTickerItems keeps one SCAN per sport (sport field or
text-prefix parse for legacy); MOVE/GRADE preserved; cap 50.
- BOMBER threshold prorated for mid-season (hr>=15 strong / >=10 mod) so June
sluggers classify BOMBER not FLEX/DRIVER.
Backend 2122 -> 2149 tests (+27), 179 suites. Web build clean (exit 0).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Three focused P1 fixes on the Session-45 snapshot model.
- Grade card intel ROOT CAUSE: gameLogService is NBA/WNBA-only (offline Python),
so MLB props never got l5_avg/l20_avg and buildIntelFields returned {}. Wired
MLB game logs into featureCache.gameLogFeatures via mlbStatsAdapter.getPlayerStats
(pure mlbGameLogFeatures + MLB stat_type->field map). buildIntelFields gained
playerStats/projection fallbacks for partial intel.
- Player name normalization: src/utils/playerName.js (+ web/src/lib copy):
normalizeName -> {display,key}. Strips periods, de-dots suffix, accent-folds
the key. Applied in snapshotService grouping, slateAdapter grade index +
player-strip merge (variants collapse, longest name shown), and
playerIntelService. "A.J. Ewing"/"AJ Ewing" + "Jazz Chisholm"/"Jr." now merge.
- MLB starting pitchers: new GET /api/schedule/:sport/pitchers (probablePitchers
service wrapping mlbStatsAdapter.getScheduleWithPitchers + best-effort ERA).
Slate fetches it, builds a team->pitcher map (full name + mascot match),
attaches pitchers to MLB GameCardData. + Next proxy.
Backend 2100 -> 2122 tests (+22), 176 suites. Web build clean (exit 0).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
The on-demand "Read" grade model is RETIRED. A scheduled pipeline pre-grades the
slate, locks grades to the line, tracks movement; the dashboard shows them already
there. Orchestrates existing services — nothing rebuilt.
- snapshotService.runSnapshot(sport): getOdds → gradeAndCacheSlate → classify
archetype per player → lock gradedAt → line deltas vs previous snapshot → write
snapshot:{sport}:latest/previous + grades:{sport} → ticker events. Fully
injectable, zero-network unit tests. runAllSnapshots = cron entrypoint.
- Internal trigger POST /api/internal/snapshot/:sport + /all (requireInternalAuth).
In-process cron (SNAPSHOT_CRON=1, UTC 14,19,22,1,3) in server.js, no new dep.
- Public reads: GET /api/snapshot/:sport (cache-only) + GET /api/ticker (merges
TICKER_MANUAL pins) + Next proxies.
- GameCard swap: live Slate renders vyndr/GameCard (legacy kept for types only),
overlays locked grades onto game props → player name once + archetype badge +
"Graded Xh ago at -115 · Current 2.5 · ▲ TOWARD +1.0". Ungraded → "Awaiting next
scan", NO Read button. On-demand onGrade flow deleted.
- Ticker polls /api/ticker every 30s, graceful fallback to hardcoded items.
- NBA/WNBA: espnStatsAdapter free fallback (defensive parse → found:false on shape
mismatch) wired into resolvePlayerStats after the offline Python service.
Env: PROPLINE_API_KEY_1/2/3, VYNDR_INTERNAL_KEY, SNAPSHOT_CRON=1, TICKER_MANUAL.
Backend 2061 -> 2100 tests (+39), 173 suites. Web build clean (exit 0).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
P0 fixes + wiring real data into the S42 Player Intelligence architecture.
- P0 dropdown z-index: the nav's backdrop-filter stacking context let the
Ticker/HeartbeatBar paint over the avatar/More dropdowns and eat clicks.
nav now position:relative zIndex:2; menus zIndex:100. Avatar Settings ->
/settings.
- Real MLB stats: mlbStatsAdapter.searchPlayer + getPlayerStats (name->id->
season+gamelog). playerIntelService.resolvePlayerStats normalizes into the
archetype classifier; getPlayerIntel returns found:true + real season +
archetype classified from real stats. NBA via nbaStatsClient (degrades).
- Game cards: slateAdapter.groupPropsByPlayer (playerStrips, name once) +
mapPitchers (MLB probables), folded into mapScheduleToGameCards. Legacy
GameCard line grid renders BookChip (brand colors) not grey text.
- Grade card intel: analyzeViaEngine1.buildIntelFields computes stat-context +
form/usage/matchup/rest from the existing feature vector (zero extra I/O);
gradeAdapter lights up the card sections. Archetype deferred (needs season
line at grade time).
- Depth chart foundation: depthChartService (getLineup/getDepthChart/
getCascadeProjection) + /api/stats/lineup|depth|cascade, graceful + injectable.
- Mobile: player hero name overflow-wrap + 24px on <=640px (was clipping).
Backend 2011 -> 2045 tests (+34), 163 suites. Web build clean (exit 0).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
builtbykev