tesseract.js (self-hosted WASM, Apache-2.0) + pure per-book layout parsers (DK/FD/MGM/Caesars) with per-field confidence and needs_review honesty — the reader never guesses. POST /api/slips/parse (auth, free 1/day paid 10/day, 4MB cap) + Next proxy. Gated /slip page: upload or paste, manual-correct UI, per-leg grades through the normal engine (refusals render honestly), add-all to Parlay Lab, share card. Vision model upgrade logged post-revenue. 2574 -> 2608 tests. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
8.5 KiB
VYNDR Master Roadmap — Generated 2026-07-10 (Session 56)
The foundation document. Derived from the Session-56 data audit
(specs/propline-audit.md, verified against live MLB Stats / ESPN / Odds APIs).
Every session after this references it. Update it as sessions ship.
Current coverage (verified 2026-07-10)
| Sport | Odds props | Grading | Features (l5/l20) | Outcomes settled | Status |
|---|---|---|---|---|---|
| MLB | ✅ PropLine + odds-api | ✅ | ✅ real (statsapi) | ✅ (S55, expanded S56) | LIVE |
| WNBA | ✅ odds-api/PropLine | ✅ | ⚠️ Python offline → thin | ❌ | PARTIAL |
| Soccer | ✅ odds-api only (no PropLine) | ⚠️ extractor only | ⚠️ | ❌ | PARTIAL |
| NBA | ⚠️ summer league only | ✅ | ⚠️ offline | ❌ | OFF-SEASON (Oct) |
| NFL | ⚠️ preseason | ⚠️ mapped, not e2e | ❌ | ❌ | PRE-SEASON (Sep) |
| NHL | ❌ off-season | ⚠️ mapped | ❌ | ❌ | DARK (Oct) |
The core product is MLB. It is the only sport that is live end-to-end (odds → grade → real features → settled accuracy). Everything else is a build-out target.
Gap analysis (from the audit)
- Outcome settlement is MLB-only — WNBA/NBA/soccer grades never settle, so
the accuracy record (the S55 trust engine) only reflects MLB. Highest-value
gap. Needs the ESPN box-score settle path (
espnStatsAdapteralready parses the shape for season avgs). - NBA/WNBA features depend on an offline Python nba_api service — l5/l20 are often empty; only season avgs survive (ESPN fallback). Needs an ESPN game-log feature path so intel populates without the Python service.
- Soccer has no PropLine source — odds-api backup only; no
SPORT_KEYSentry. Soccer grading isn't wired into the snapshot pipeline end-to-end. - NFL mapped but not graded end-to-end — markets normalize, but no feature/ outcome path. Wire before September.
RBI silent-failure (rbis/rbi)— FIXED S56.Under-requesting MLB markets— FIXED S56 (6 → 12 markets).No pipeline alerting / retry / missed-cron— FIXED S56.- No live calibration — the accuracy record exists but doesn't yet feed back into grade confidence (spec 2.3 from S55).
batter_strikeouts(batter Ks) mapped but not feature/settle-wired.
Session plan (priority-ordered)
| Session | Focus | Ships | Scope |
|---|---|---|---|
| 57 | WNBA/NBA outcome settlement | ESPN box-score settle path in outcomeService → accuracy for basketball; WNBA goes fully live | M |
| 58 | ESPN game-log features | l5/l10/l20 for NBA/WNBA without the Python service → real intel on basketball grade cards | M |
| 59 | Soccer end-to-end | soccer into the snapshot pipeline (odds-api source), feature extractor wired, ESPN settle | L |
| 60 | Live calibration | accuracy record feeds grade-confidence adjustment (under/over-confident tiers nudge); "Model health: Calibrated/Learning" indicator | M |
| 61 | NFL pre-season prep | NFL feature + settle path (ESPN NFL boxscore) so Week 1 (Sep) is live | L |
| 62 | Prop breadth | batter_strikeouts, triples, pitcher walks; NBA pra/turnovers requested; WNBA extra markets |
S |
| 63 | Accuracy depth | per-archetype hit rates, per-stat hit rates, player-level record ("VYNDR on Judge: 12-5"); ledger UI | M |
| 64 | NBA regular-season readiness | verify NBA pipeline for the Oct tip-off; depth-chart/cascade live | M |
Scope key: S ≈ ½ session, M ≈ 1 session, L ≈ 1–2 sessions.
NOTE (Session 58): the numbered plan above predates the overhaul work order. The work order's phases (0 = kill the lies ✅ S57, 1 = truth infrastructure ✅ S58, 2 = slate UX, 3 = mobile, 2.5 below, 4 = scan/ parlay, 5 = records, 6 = landing/content) take sequencing priority; the table's items slot in where they don't conflict.
Phase 2.5 — Intraday line refresh + directional movement (LOGGED Session 58)
Authoritative scope from the Phase 1 GO prompt. Build after Phase 3 (mobile), before Phase 4. During slate hours (~noon–midnight ET):
- Lightweight ODDS-ONLY refresh every 15–30 min (no full re-grade run). Recompute the signed delta per graded prop RELATIVE TO THE GRADED SIDE — direction is the signal, not magnitude alone.
- Moved WITH the grade (market chasing our number): PropRow badge
STEAM ▲ +N. Good for the record; entry edge compressed. No re-grade. - Moved AGAINST the grade ≥ 1.0 (or odds-equivalent): auto re-grade THAT
PROP ONLY.
- Grade holds → badge
VALUE ▲ better entry(better number, same read). - Grade drops → update the grade with
revised_from_gradeset (column already exists inledger_entries) + a visible revision marker (original grade struck through — the ledger UI already renders it). Revisions are ALWAYS public — never silently regrade, per Ledger ethos.
- Grade holds → badge
- All displayed lines remain real book values from the refresh — the refresh CAPTURES market numbers, never computes them.
- After ship: drop
SNAPSHOT_EXPECTED_INTERVALto the refresh cadence — the HeartbeatBar SYNC badge (normal <1.5x · amber ≥1.5x · STALE ≥3x) goes genuinely live with zero further UI changes.
Phase 4.5 — WNBA settlement via ESPN box scores (DUE DATE, not "roadmap")
Logged Session 59. Pending-forever WNBA ledger rows are honest but become a
credibility hole past ~2 weeks of accumulation. Due: within 2 weeks of
day one of the public record (by ~Jul 24 2026). Scope: ESPN box-score
settle path in outcomeService + ledgerService defaultGetPlayerStats
(WNBA branch) so WNBA rows settle nightly like MLB. Build right after
Phase 4 (scan/parlay polish).
Phase 5 addition — calibration by grade tier (logged Session 59)
Once settles mature: the MODEL tab shows A-tier hit% vs B-tier hit%
SEPARATELY (same n≥20 rule PER TIER — a tier below threshold shows
"building", never a %). The separation between tiers is the proof the
grades mean something. ledger_entries.grade already carries the tier;
this is an aggregate + UI change only.
Stat-type coverage target (fully built)
- MLB (batters): hits, total_bases, home_runs, rbi, runs, doubles, triples, walks, stolen_bases, batter_strikeouts. (pitchers): strikeouts, earned_runs, hits_allowed, innings_pitched, outs, walks. (Bold-new this session: doubles, triples, outs, runs, walks requested + settleable.)
- NBA/WNBA: points, rebounds, assists, threes, steals, blocks, turnovers, pra.
- Soccer: goals, shots, shots_on_target, tackles, cards, corners, saves, passes, clean_sheet.
- NFL: passing/rushing/receiving yards, receptions, pass/rush/rec TDs, anytime_td, interceptions, kicking_points.
Sport coverage target
- MLB ✅ live now (settled accuracy).
- WNBA → live after S57 (settlement) + S58 (features).
- Soccer → live after S59.
- NFL → ready for September (S61).
- NBA → ready for October (S64).
- NHL → ready for October (fast-follow once NBA path exists; shares ESPN pattern).
Slip Reader — vision-model upgrade (POST-REVENUE)
Session 9 (A1 board) shipped the zero-API Slip Reader: tesseract.js OCR (self-hosted WASM, free) + rigid per-book layout parsers (DK/FD/MGM/Caesars) with per-field confidence and needs_review honesty. That architecture is deliberately conservative — it reads clean screenshots of the four big books and refuses everything else.
The upgrade, when revenue funds it (zero-out-of-pocket rule): a vision model
(Claude-class multimodal) replaces the OCR+layout-parser pair — one call reads
ANY book, any theme, any crop, and returns structured legs with real
confidence. Costs per-call money, so it is gated on paid tiers paying for
themselves. The route contract (POST /api/slips/parse → { legs, needs_review, source: 'user_slip' }) is the stable interface; only the
extraction engine behind it swaps. Keep the never-guess rule: model output
below confidence threshold still nulls the field.
Operating invariants (do not regress)
- Three stat_type whitelists stay in sync:
routes/analyze.js,routes/scan.js,python/utils/validation.py. - A requested market MUST have a
MARKET_MAPentry (else silent zero) AND, if MLB, aMLB_LOG_FIELDentry in BOTHfeatureCacheandoutcomeService(else no features / no settlement). - The accuracy pill stays HONEST — "LEARNING" below MIN_SAMPLE, never a faked %.
- Pipeline alerts (ntfy) fire on success/failure/stale/overdue; the status probe
(
GET /api/internal/snapshot/status) exposesoverdue.