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builtbykev	c7cc8f5e52	Build the gate, run it, and find we were proving things on the wrong stat PREMISE CORRECTION FIRST. statModel.js and correlateValidator.js do not exist in this repository. The validation spec's only prior form is src/services/python/blueprints/unconventional.py -- a Flask blueprint in the Python service that is offline in production, scoring NBA factors against a warehouse that was never populated -- and tests/unit/supplementSystems.test.js requires only fs and path while defining its own validateFactor inline at line 368. Those tests assert a re-implementation of the thresholds, not an implementation, which is exactly why they passed for months while nothing was connected. The diagnosis behind the order is right -- every challenger was measured without a gate -- but the cause is that there was no gate on the Node side to import. So it is built, to the exact spec. correlateValidator: n>=500, \|r\|>=0.15, p<0.05, Bonferroni across the sweep. The p-value is exact rather than approximated (t-transform through a regularized incomplete beta) and is verified in the suite against known values, because scipy is not available here. Pairs with an unknown side are dropped, never zero-filled -- a zero-fill inside a correlation does not add noise, it invents a point at the origin. THE RUN, hits, n=570, Bonferroni-8: every skill feature fails, and not narrowly. The strongest marginal correlation against the counter's residual is 0.062 against a 0.15 bar. That is an effect-size failure at a sample that would have found a real effect comfortably -- a clean, well-powered negative. The head-to-head agrees: value engine 0.0499 against the counter's 0.166, delta -0.116 with CI [-0.189, -0.043]. Not promoted. THE RUN, total bases, n=295: cannot be tested, and that is the finding. hard_hit_pct shows a marginal r of 0.153 -- above the threshold -- and exit velo 0.124, refused solely because n is 205 short of 500. It is the most encouraging number this work has produced, and it is what the physics predicts: contact quality governs extra bases, not whether a grounder finds a hole. We have been testing skill inputs on the one stat where they should not matter much. Two things the run forced. Feature verdicts are now PER STAT, because marking these DEAD sport-wide on hits evidence would have killed, for total bases, the features that look most alive there -- per-sport doctrine one level deeper. And the gate now reports r and p even when underpowered, because "not enough data yet" and "nothing here" demand opposite decisions and a bare refusal was hiding the best signal on the board. Next: build the compound TB projection (skillProjection still refuses total bases by design, since a deterministic bases-per-hit made P(TB>=2) identical to P(hits>=1)), accrue to n>=500, re-run this gate. Leave hits alone. 4,200 tests green (334 suites); web build exit 0; counter byte-identical. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01W1sivYNqY2TS5ftykmHBU9	2026-08-03 02:34:02 -04:00
builtbykev	258d8a6655	The skill engine: built, gated by construction, and Stage A honestly lost Built src/services/model/ -- the forward, archetype-selected, skill-based projection, as a challenger. The champion is untouched. featureRegistry makes "earn its place or it's out" structural rather than aspirational: CANDIDATE / PROVEN / DEAD per feature per sport, liveFeatures() returns PROVEN only, promotion requires n>=200 with positive lift and a CI excluding zero, and there is deliberately no override argument. It ships with exactly ONE proven feature -- the incumbent counter, because it is the only one with a measurement. A test asserts that with only PROVEN features allowed the projection returns null, so an unproven model cannot reach a user by accident. The three champion adjustment layers are registered DEAD with their reasons so they cannot be silently rebuilt. skillProjection is a PA outcome tree: K and BB combined by log5 odds-ratio against league (both identities unit-tested), then archetype-weighted contact quality against contact allowed, then Binomial(PA, p_hit) mixed over a PA distribution. Archetype is a FEATURE SELECTOR, not a nudge -- BOMBER reads barrels at 0.50 and ground-ball speed at 0.00, GHOST inverts it -- and a test locks that the same hitter read two ways moves more than 0.15. STAGE A: IT LOSES. Out-of-sample on 570 settled hits props with 91.9% opposing-pitcher coverage, resolution 0.0499 against the champion's 0.166, delta -0.116 with CI [-0.189, -0.043]. It is not selective either: its eight most confident picks hit 50%, a lift of -0.065. Not promoted. The gate did its job on its first real test, which is the point of having built it that way. Two false starts, both recorded because they nearly produced a wrong verdict: statcast_aggregates stores PERCENTAGES, so raw rows made bip = 1-29.6-17.1 and refused 568 of 576 -- the honest-absent guards made a units bug loud instead of silent, and the conversion now lives at one chokepoint. And the first run resolved an opposing pitcher for 1 of 570 rows, because ledger team/opponent are NULL, so it would have reported "skill-v1 loses" while measuring a batter-only model with no matchup in it at all. The verdict above is from the corrected run. The loss is real but partial: park was passed as 1.0, handedness and opportunity_drift never fired, PA is season-PA over a constant, and the skill profiles carry no recency at all while the champion has a last-5 term. Also fixed: the Statcast nightly refresh was unreachable code. It sat inside tick() below "if (!HOURS_UTC.includes(h)) return" while testing h === 11, so it had never run once; the aggregates were 13 days stale and both of its alerts were in the same dead branch. It now runs on its own tick, and the test that passed happily throughout -- it only checked the string existed -- is replaced by one that asserts it is not behind the guard. 4,182 tests green (333 suites); web build exit 0. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01W1sivYNqY2TS5ftykmHBU9	2026-08-03 02:20:40 -04:00

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builtbykev

c7cc8f5e52

Build the gate, run it, and find we were proving things on the wrong stat

PREMISE CORRECTION FIRST. statModel.js and correlateValidator.js do not exist
in this repository. The validation spec's only prior form is
src/services/python/blueprints/unconventional.py -- a Flask blueprint in the
Python service that is offline in production, scoring NBA factors against a
warehouse that was never populated -- and tests/unit/supplementSystems.test.js
requires only fs and path while defining its own validateFactor inline at line
368. Those tests assert a re-implementation of the thresholds, not an
implementation, which is exactly why they passed for months while nothing was
connected. The diagnosis behind the order is right -- every challenger was
measured without a gate -- but the cause is that there was no gate on the Node
side to import. So it is built, to the exact spec.

correlateValidator: n>=500, |r|>=0.15, p<0.05, Bonferroni across the sweep.
The p-value is exact rather than approximated (t-transform through a
regularized incomplete beta) and is verified in the suite against known
values, because scipy is not available here. Pairs with an unknown side are
dropped, never zero-filled -- a zero-fill inside a correlation does not add
noise, it invents a point at the origin.

THE RUN, hits, n=570, Bonferroni-8: every skill feature fails, and not
narrowly. The strongest marginal correlation against the counter's residual is
0.062 against a 0.15 bar. That is an effect-size failure at a sample that
would have found a real effect comfortably -- a clean, well-powered negative.
The head-to-head agrees: value engine 0.0499 against the counter's 0.166,
delta -0.116 with CI [-0.189, -0.043]. Not promoted.

THE RUN, total bases, n=295: cannot be tested, and that is the finding.
hard_hit_pct shows a marginal r of 0.153 -- above the threshold -- and exit
velo 0.124, refused solely because n is 205 short of 500. It is the most
encouraging number this work has produced, and it is what the physics
predicts: contact quality governs extra bases, not whether a grounder finds a
hole. We have been testing skill inputs on the one stat where they should not
matter much.

Two things the run forced. Feature verdicts are now PER STAT, because marking
these DEAD sport-wide on hits evidence would have killed, for total bases, the
features that look most alive there -- per-sport doctrine one level deeper.
And the gate now reports r and p even when underpowered, because "not enough
data yet" and "nothing here" demand opposite decisions and a bare refusal was
hiding the best signal on the board.

Next: build the compound TB projection (skillProjection still refuses total
bases by design, since a deterministic bases-per-hit made P(TB>=2) identical
to P(hits>=1)), accrue to n>=500, re-run this gate. Leave hits alone.

4,200 tests green (334 suites); web build exit 0; counter byte-identical.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01W1sivYNqY2TS5ftykmHBU9

2026-08-03 02:34:02 -04:00

builtbykev

258d8a6655

The skill engine: built, gated by construction, and Stage A honestly lost

Built src/services/model/ -- the forward, archetype-selected, skill-based
projection, as a challenger. The champion is untouched.

featureRegistry makes "earn its place or it's out" structural rather than
aspirational: CANDIDATE / PROVEN / DEAD per feature per sport, liveFeatures()
returns PROVEN only, promotion requires n>=200 with positive lift and a CI
excluding zero, and there is deliberately no override argument. It ships with
exactly ONE proven feature -- the incumbent counter, because it is the only
one with a measurement. A test asserts that with only PROVEN features allowed
the projection returns null, so an unproven model cannot reach a user by
accident. The three champion adjustment layers are registered DEAD with their
reasons so they cannot be silently rebuilt.

skillProjection is a PA outcome tree: K and BB combined by log5 odds-ratio
against league (both identities unit-tested), then archetype-weighted contact
quality against contact allowed, then Binomial(PA, p_hit) mixed over a PA
distribution. Archetype is a FEATURE SELECTOR, not a nudge -- BOMBER reads
barrels at 0.50 and ground-ball speed at 0.00, GHOST inverts it -- and a test
locks that the same hitter read two ways moves more than 0.15.

STAGE A: IT LOSES. Out-of-sample on 570 settled hits props with 91.9%
opposing-pitcher coverage, resolution 0.0499 against the champion's 0.166,
delta -0.116 with CI [-0.189, -0.043]. It is not selective either: its eight
most confident picks hit 50%, a lift of -0.065. Not promoted. The gate did its
job on its first real test, which is the point of having built it that way.

Two false starts, both recorded because they nearly produced a wrong verdict:
statcast_aggregates stores PERCENTAGES, so raw rows made bip = 1-29.6-17.1 and
refused 568 of 576 -- the honest-absent guards made a units bug loud instead of
silent, and the conversion now lives at one chokepoint. And the first run
resolved an opposing pitcher for 1 of 570 rows, because ledger team/opponent
are NULL, so it would have reported "skill-v1 loses" while measuring a
batter-only model with no matchup in it at all. The verdict above is from the
corrected run.

The loss is real but partial: park was passed as 1.0, handedness and
opportunity_drift never fired, PA is season-PA over a constant, and the skill
profiles carry no recency at all while the champion has a last-5 term.

Also fixed: the Statcast nightly refresh was unreachable code. It sat inside
tick() below "if (!HOURS_UTC.includes(h)) return" while testing h === 11, so
it had never run once; the aggregates were 13 days stale and both of its
alerts were in the same dead branch. It now runs on its own tick, and the test
that passed happily throughout -- it only checked the string existed -- is
replaced by one that asserts it is not behind the guard.

4,182 tests green (333 suites); web build exit 0.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01W1sivYNqY2TS5ftykmHBU9

2026-08-03 02:20:40 -04:00

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