Produced by playoff_translation.py (2026-07-08) from the new playoff PBP + shifts files (1,395 games, 16 postseasons 2010-11 .. 2025-26). Playoff attempts are priced by the season-matched regular-season xG v2 model (Fenwick + flags); player on-ice 5v5 requires exactly 5 skaters a side from playoff shifts; analysis domain is periods 1-4 (multi-OT excluded from rates). Companion data: playoff_player_gaps.csv.
# Playoff Translation Study -- console log
(playoff_translation.py, run 2026-07-08; 1,395 playoff games 2010-2025 playoffs; xG v2 Fenwick+flags built on the 16 regular seasons; on-ice domain periods 1-4.)
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1. ENVIRONMENT SHIFT -- does playoff hockey tighten, and how?
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Domain: periods 1-4 (regulation + first OT); 5v5 = situation code 1551;
shots priced by the season-matched regular-season xG v2 model (Fenwick+flags).
era games xG/60 att/60 xG/att clean reb% rush% PP/60 pen/60 GF/60
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2010-13 RS 4410 2.35 41.2 0.0571 0.0500 2.8% 2.2% 11.75 8.82 2.32
2010-13 PO 354 2.28 41.6 0.0550 0.0485 2.7% 2.5% 12.23 9.38 2.15
2014-17 RS 4961 2.36 41.7 0.0565 0.0502 2.7% 2.0% 10.79 7.69 2.30
2014-17 PO 351 2.24 41.5 0.0541 0.0482 2.6% 2.4% 10.49 8.19 2.13
2018-21 RS 4533 2.60 42.3 0.0614 0.0550 4.1% 2.0% 10.41 7.10 2.53
2018-21 PO 346 2.56 42.3 0.0605 0.0539 4.2% 2.5% 10.74 7.98 2.29
2022-25 RS 5248 2.59 42.3 0.0613 0.0581 5.8% 2.3% 10.17 7.30 2.55
2022-25 PO 344 2.49 42.2 0.0591 0.0558 5.5% 2.8% 10.41 8.49 2.33
ALL RS 19152 2.48 41.9 0.0591 0.0535 3.9% 2.1% 10.75 7.70 2.43
ALL PO 1395 2.39 41.9 0.0572 0.0516 3.8% 2.5% 10.98 8.51 2.22
(PP/60 = two-sided PP minutes per 60 min of play; pen/60 = penalty events per 60. Mean game length, periods 1-4: RS 60.8 min, PO 62.4 min; 5v5 share of play 78.0% -> 77.9%.)
Decomposition of the 5v5 xG/60 shift (playoff vs regular, pooled):
xG/60 -3.4% = attempts/60 -0.0% x xG/attempt -3.3%
xG/attempt split: clean-shot quality -3.6%; rebound share 3.9%->3.8%, rush share 2.1%->2.5%
PP time: 10.75 -> 10.98 min per 60 (+2%); per game 10.90 -> 11.41 (playoff games run longer); penalty events 7.70 -> 8.51/60
League finishing vs xG (all situations): regular -0.00 goals/100 attempts (calibrated ~0), playoff -0.33
Playoff environment by round (pooled 2010-2025):
round games xG/60 att/60 xG/att reb% PP/60 pen/60
round 1 742 2.39 42.4 0.0564 3.8% 11.29 8.81
round 2 376 2.42 42.0 0.0577 3.6% 10.63 8.14
round 3 182 2.39 40.5 0.0591 3.7% 10.54 7.95
round 4 95 2.31 40.1 0.0576 3.8% 10.71 8.77
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2. PLAYER-LEVEL TRANSLATION -- what regular-season signal carries?
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Sample: 696 skaters with >= 300 pooled playoff 5v5 minutes (of 1505 with any).
Outcome: pooled playoff 5v5 on-ice xG% (share of on-ice xG). Predictors: same-season
regular-season relWPA components per 60 (playoff-TOI-weighted across runs) +
shrunk finishing GAx/100. Weighted by playoff 5v5 TOI; standardized betas.
predictor weighted univariate r
EV offense /60 +0.362
EV defense /60 +0.072
PP value /60 +0.191
PK value /60 +0.102
finishing GAx/100 (shrunk) +0.107
WLS: playoff xG% ~ components + finishing (n=696, weighted R^2=0.207)
term beta (xG% pts / SD) t
intercept (mean xG%) 50.37 413.2
EV offense /60 +1.86 10.9
EV defense /60 +1.10 7.9
PP value /60 -0.07 -0.5
PK value /60 +0.07 0.6
finishing GAx/100 (shrunk) -0.05 -0.4
Directional checks: r(reg EV offense, playoff 5v5 xGF/60) = +0.642;
r(reg EV defense, playoff 5v5 xGA/60) = -0.487 (defense component is +good, so negative = carries)
Grit check (run level, 2021-2025 runs with >= 50 playoff 5v5 min, n=1294, R^2=0.125):
EV offense /60 beta +2.16 t +9.2
EV defense /60 beta +1.37 t +7.3
PP value /60 beta +0.25 t +1.2
PK value /60 beta +0.42 t +2.3
finishing GAx/100 (shrunk) beta -0.01 t -0.1
grit (hits+blocks)/60 beta +0.25 t +1.2
PP translation: r(reg PP value/60, playoff PP on-ice xGF/60) = +0.649
(n=653 skaters with >= 20 pooled playoff PP minutes; compare EV: r=+0.642).
Playoff PP TIME per 60 of play: 10.98 vs 10.75 min (+2%) -- the per-60 skill carries; how much PP opportunity exists is an era/officiating question, not a player one.
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3. IS 'PLAYOFF PERFORMER' A REAL ARCHETYPE? (persistence across runs)
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Runs with >= 8 playoff GP: 2278 (962 players).
Run-level regression for the expected playoff xG% (n=2267, R^2=0.104).
Consecutive-run pairs within player: 1316.
metric obs r n null mean null 95% env p
on-ice gap (xG% - expected) +0.114 1307 -0.005 [-0.057,+0.042] 0.005
finishing gap (PO-RS GAx/100) -0.015 952 -0.007 [-0.108,+0.075] 0.736
raw playoff xG% [control] +0.180 1316 -0.004 [-0.057,+0.058] 0.005
VERDICT: raw playoff xG% persists across a player's runs (r=+0.180) -- that is ordinary talent, and the machinery has power. The on-ice GAP persists at r=+0.114 (p=0.005), nominally beating the null, but the regular-season control it is residualized on (relWPA components, run-level R^2=0.10) is an imperfect proxy for on-ice xG% talent, so the residual retains general skill, not necessarily playoff-specific skill. Where the regular and playoff measures are in IDENTICAL units (Fenwick finishing GAx/100, same model family both sides), the playoff-minus-regular gap has zero persistence (r=-0.015, p=0.74). Read: most of the 'playoff riser' signal is measurement leakage of ordinary talent; any true playoff-specific trait is at most weak (bounded above by r~+0.11, ~1% of gap variance).
Descriptive career on-ice gap leaderboard (mean run gap, >= 3 qualifying runs, >= 40 playoff GP; given section 3, read as variance's honor roll):
Taylor Hall L runs 3 GP 41 gap +9.89 xG% pts
Shawn Thornton L runs 3 GP 52 gap +9.35 xG% pts
J.T. Compher L runs 4 GP 54 gap +8.57 xG% pts
Artturi Lehkonen L runs 4 GP 59 gap +8.29 xG% pts
Nick Holden D runs 3 GP 42 gap +7.44 xG% pts
Blake Coleman L runs 3 GP 57 gap +7.34 xG% pts
Ryan McLeod C runs 3 GP 52 gap +7.18 xG% pts
Nazem Kadri C runs 3 GP 41 gap +7.08 xG% pts
Andre Burakovsky L runs 7 GP 83 gap +6.98 xG% pts
Alex Tuch R runs 3 GP 56 gap +6.96 xG% pts
...
Brad Richards C runs 4 GP 78 gap -8.42 xG% pts
Josh Bailey R runs 4 GP 54 gap -9.48 xG% pts
Tanner Glass L runs 3 GP 47 gap -11.29 xG% pts
Mika Zibanejad C runs 4 GP 58 gap -11.83 xG% pts
Nate Thompson C runs 5 GP 68 gap -12.96 xG% pts
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4. TEAM LEVEL -- predicting series winners, and playoff home ice
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Series with complete data: 240 of 240 (A = home-ice team; predictors = A-minus-B).
Home-ice team won the series 56.2% of the time.
model acc(sign) logloss LOSO-CV
home-ice only (intercept) 56.2% 0.6853 0.6895
regular-season points diff 56.2% 0.6675 0.6787
relWPA-sum strength diff 56.7% 0.6678 0.6790
points + relWPA 61.3% 0.6566 0.6757
Coefficients: relWPA model logit = +0.186 + 0.014 x (wins/82 diff); points model logit = -0.202 + 0.0483 x (points-pace diff).
Per-game home win%: playoffs 53.1% (1395 games); excluding the 2019-20 bubble 53.9%.
Regular-season home win%: 54.1% (19,152 games, 2010-2026, incl. OT/SO).
Wrote playoff_player_gaps.csv (1047 players with >= 100 pooled playoff 5v5 minutes).