# 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)

1. **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 (`espnStatsAdapter` already parses
   the shape for season avgs).
2. **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.
3. **Soccer has no PropLine source** — odds-api backup only; no `SPORT_KEYS` entry.
   Soccer grading isn't wired into the snapshot pipeline end-to-end.
4. **NFL mapped but not graded end-to-end** — markets normalize, but no feature/
   outcome path. Wire before September.
5. ~~RBI silent-failure (rbis/rbi)~~ — **FIXED S56.**
6. ~~Under-requesting MLB markets~~ — **FIXED S56** (6 → 12 markets).
7. ~~No pipeline alerting / retry / missed-cron~~ — **FIXED S56.**
8. **No live calibration** — the accuracy record exists but doesn't yet feed back
   into grade confidence (spec 2.3 from S55).
9. **`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_grade` set (column
    already exists in `ledger_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.
- All displayed lines remain real book values from the refresh — the
  refresh CAPTURES market numbers, never computes them.
- After ship: drop `SNAPSHOT_EXPECTED_INTERVAL` to 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_MAP` entry (else silent zero) AND, if
  MLB, a `MLB_LOG_FIELD` entry in BOTH `featureCache` and `outcomeService` (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`) exposes `overdue`.