builtbykev
65ca6493db
out-resolved by a frequency table on three of four stats
PHASE 0 — the 14.51% is REAL. Re-derived with a paged pull asserted
against an exact count (rbi 7,930 == 7,930; hits 11,690; TB 12,086; runs
6,440), since this harness produced a false null three times tonight. rbi
resolution 0.03268 reproduces, deciles are monotone through the middle,
and 20 raw rows are in the artifact for hand audit.
CAVEAT GOVERNING EVERYTHING BELOW: the naive forecasts are leave-one-out
ON THE EVALUATION WINDOW, so they see the rows they are scored on while
the model is strictly point-in-time. They are upper bounds on available
resolution, not fair competitors, and every comparison is read that way.
PHASE 1 — the split:
stat MODEL (a)player-base (b)lineup-slot (c)within-stratum
rbi 0.03268 0.01167 0.03608 0.01908
hits 0.00252 0.00446 0.00100 0.00473
TB 0.00442 0.01331 0.03448 0.00607
runs 0.00130 0.00262 0.01156 0.01170
FINDING 1 — rbi's resolution is LINEUP ROLE almost exactly. Batting-order
slot alone resolves 0.03608 against the model's 0.03268. A single integer
accounts for the whole anomaly and slightly more. That is opportunity, not
skill -- the cleanup hitter bats with runners on. 36% is matched by player
identity alone. Within similar-base-rate strata the model still resolves
0.01908, 58% of its total and higher than any other stat's ENTIRE model
resolution, so genuine within-role discrimination exists on top.
FINDING 2 — on three of four stats the model is beaten by "he's a .270
hitter". Base-rate-only out-resolves the model 1.8x on hits, 3.0x on TB,
2.0x on runs. Even allowing for the window-peeking advantage, a 1.8-3.0x
gap is not explained by that alone: the served counter appears to DESTROY
discrimination relative to the player's own rate. rbi is the one stat
where the model beats the naive baseline.
FINDING 3 — lineup slot out-resolves the MODEL on three stats: TB 7.8x,
runs 8.9x, rbi 1.1x. Hits is the only stat where batting order carries
less, which is mechanically right -- a hit is a hit wherever you bat, but
runs, RBI and total bases all scale with opportunity.
PHASE 2 — all three worlds are partly true, in measured proportions.
World A ~90% true (slot covers rbi's entire resolution). World B ~36% true
for rbi, but the WHOLE story for hits/TB/runs where base rate alone wins.
World C true with a low ceiling: hits' total available spread resolution
is 0.00446, i.e. 1.8% of variance from a forecast that has seen the
answers.
PHASE 3 — the next arc is NOT "strengthen hits factors". Hits has the
lowest available resolution on the board and last order's wiring already
took it to 1.39% of a ~1.8% ceiling. Named first factor order for next
session: LINEUP SLOT / RISP OPPORTUNITY on rbi through the two-part gate --
input already ingested and prod-verified (S89), resolution measured not
hypothesised, causally-correct unit is plate appearances with runners on.
Measured availability is not a pass; it still faces the gate.
And higher-value than either: the counter being out-resolved by a
frequency table on three of four stats is a defect in the CHAMPION, not a
factor problem, and it costs nothing to test -- the recency blend and the
+/-0.03 / +/-0.015 nudges are three lines in probabilityEstimator.
The hits transmission win from 43f65d3 stands: the conduit is real and
permanent. This order changes only which stat has the most worth flowing
through it.
Diagnostic only -- no factor wired, no serving path changed, p_win
untouched, all frozen modules byte-identical. No Bonferroni slot.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01W1sivYNqY2TS5ftykmHBU9