PART A -- WNBA TRUTH CORRECTION (no behaviour change).
WNBA does not "abstain" and is not "anti-predictive". The -0.12 that
produced those words was NBA-template machinery run on WNBA data -- WNBA
has never had its own archetypes, variables, conditions or calibration,
which is precisely the "sport stubbed in on another sport's template"
CLAUDE.md forbids. That is an UNBUILT MODEL'S EXPECTED FAILURE, not a
verdict on the sport; reading it as a verdict would quietly retire a sport
we never actually attempted. Its own build is QUEUED, after MLB.
The guard CODE is unchanged -- FORECAST_RANKED_SPORTS = {'mlb'} and the
inheritance test are correct live safety either way. Only the meaning is
corrected, and generalised into the doctrine-as-a-gate: a sport ranks on
p_win ONLY once its OWN model is built and shown to predict (calibration
AND resolution on its own holdout). Others are held out as NOT-BUILT,
never as failed. Re-labelled across gradeRanking, snapshot route, tests,
MASTER-PLAN and the challenger report.
PART B -- THE FLIP, gated on a full-slate re-run.
The re-run found something better than a bigger sample. An induced
snapshot graded 7 props: gradeAndCacheSlate runs with DEFAULT_LIMIT = 25
and ~72% of those refuse for insufficient_data, while 546 props are
gradeable. So 8 props IS the board, structurally -- not a small sample of
it. Logged as its own finding; the cap is a separate order.
For a statistically meaningful delta I used 11 real historical boards
(n=328, board sizes 14-57): 79.9% of rows move, mean 5.16 places per
board, TOP READ CHANGES ON 9 OF 11 BOARDS. The re-ordering holds at real
board size. Query committed.
FLIPPED:
- rankGrades drops its edge key (safe for every sport: removes a
non-predictive tiebreak without putting p_win in front).
- selectTopGrades leads on forecast_rank, edge key removed.
- flattenToEdgeBoard sorts on forecastRank, not edge -- this board had
edge as its PRIMARY key, so the whole mobile board was ordered by a
quantity measured not to predict.
- forecast_rank threaded onto strip props.
Sports whose model is not built supply no forecast_rank, so their boards
fall through to the unchanged grade chain -- the fallback is the guard.
ROLLBACK ARMED: boards sort by forecast_rank WHEN PRESENT, so
FORECAST_RANK=0 reverts every surface on the next response -- no deploy,
no client release.
Edge is still computed, stored, carried and displayed as a labelled
diagnostic. Retired from ranking, not deleted.
Eight superseded tests updated to strictly stronger INVERSE properties --
they now fail if edge is ever re-introduced as a ranking key, which the
originals could not detect.
Gates: 4,045 tests / 323 suites green; next build exit 0.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01QJs13VsyiSKYQP6rj3NNmc
Phone audit called the board 'mostly-empty'. Two causes, both now addressed:
1. Dead images (P0-2, already fixed) → the matchup/team chips render logos now.
2. Degraded edge data. Live snapshot edge_pct is on a broken scale (distinct
values 20/60/100/140 — not a market %), with projection=0 and confidence
35-55%. A real prop-market edge is single-digit, never past ~40%. Leading
the board with '+140%' fabricates a signal (Data Semantics Rule).
Fix: an edge whose |value| > 40 is treated as ABSENT at BOTH layers — the
data layer (flattenToEdgeBoard nulls it, so it can't RANK a fake +140% above a
real +8.4%) and the display (EdgeCell shows '—'). Board falls through to the
grade-rank tiebreak when edges are unreliable. Real edges (≤40) are untouched.
The root cause — edge_pct/projection/confidence degradation — is a BACKEND
grading issue (same family as the P2-9 '45% B' flag), reported separately; this
is the honest frontend guard, not a fix for the data.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
The one genuinely-new mobile screen. Design's mobile BOARD is a FLAT edge-ranked
list (all graded props across every game on one list, sorted by edge) — not the
desktop's game-grouped cards. Implemented to the drawing with REAL snapshot data:
- slateAdapter.flattenToEdgeBoard(cards) — pure transform of the assembled
GameCardData[] (grade→game join already done) into ranked rows, edge desc.
STRICT null edge sorts LAST (never 0-coerced to the top — Data Semantics Rule).
Threaded edge_pct through buildPlayerStripsFromProps (was dropped). 6 unit tests.
- MobileEdgeBoard component — Design's exact screen-01 rows: rank (green #1),
player + prop, matchup sub-line with TeamChips + live-dot, tier grade chip,
and the edge% as the one bold mono hero (green +, red −). Ranked opacity ramp
(1 → .55) + green inset border on the top reads. Breadth strip EDGES/AVG CLV/
GAMES — CLV honest '—' (per-slate CLV isn't computed; never fabricated).
- Slate: <768px renders the flat board, ≥768px keeps game cards (same data,
toggled by width). Ungraded slate still shows game cards on phones (no blank).
Built to Design's screen-01 drawing, VISUALLY UNVERIFIED at 390px — the core
mobile screen, top of the master-audit list.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
builtbykev