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Clutch Study -- is high-leverage outperformance a persistent skill?

Run 2026-07-08 on the 2021-26 rated-games universe. Design: per player-season, games split by per-season terciles of w_game (playoff-race importance); clutch_gap = per-game mean of (wpa - xgwpa) in HIGH-importance games minus the same in LOW-importance games. Persistence tested split-half within season (odd/even games, >=30 GP per half) and season-over-season (>=30 GP both seasons), against a 200-rep shuffled-label null. Positive control: plain per-game wpa. Produced by clutch_study.py.

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CLUTCH STUDY -- is outperforming under pressure a persistent skill?
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Ledger rows 236,268 | games 6,198 | seasons 2021-2025 | players 1,650
Games in HIGH/LOW importance terciles: 4,135 (middle tercile dropped)
  league mean  resid: LOW -0.003  HIGH -0.021  (pp per player-game)
  league mean  xgwpa: LOW +0.465  HIGH +0.481  (pp per player-game)
  league mean    wpa: LOW +0.462  HIGH +0.460  (pp per player-game)

Eligible player-seasons: split-half (>= 30 GP/half) 2,251; season-pairs (>= 30 GP both years) 2,275

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1. PERSISTENCE OF THE IMPORTANCE GAP  (HIGH-bucket mean - LOW-bucket mean)
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metric                  split-half r      n   season/season r      n
clutch_gap (wpa-xgwpa)        +0.047   1912            -0.028   1749
xgwpa gap (process)           +0.079   1912            +0.054   1749
wpa gap (results)             +0.055   1912            +0.031   1749

Robustness -- same test, halves = early/late season instead of odd/even
metric                  split-half r      n
clutch_gap (wpa-xgwpa)        -0.109    760
xgwpa gap (process)           -0.002    760
wpa gap (results)             -0.089    760

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2. POSITIVE CONTROL -- plain per-game means (no importance split)
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metric                  split-half r      n   season/season r      n
mean wpa/gm  [CONTROL]        +0.646   2251            +0.612   2275
mean xgwpa/gm                 +0.859   2251            +0.775   2275
mean resid/gm                 +0.133   2251            +0.099   2275

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3. NULL SIMULATION -- shuffle HIGH/LOW labels within player-season, 200 reps
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metric                test             obs r  null mean      null 95% env  p(|null|>=|obs|)
clutch_gap            split-half      +0.047     -0.001   [-0.041,+0.044]             0.035
clutch_gap            season/season   -0.028     +0.000   [-0.057,+0.060]             0.358
xgwpa gap             split-half      +0.079     +0.001   [-0.052,+0.050]             0.010
xgwpa gap             season/season   +0.054     +0.003   [-0.061,+0.061]             0.119
wpa gap               split-half      +0.055     -0.000   [-0.045,+0.040]             0.015
wpa gap               season/season   +0.031     +0.001   [-0.059,+0.057]             0.259

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4. VERDICT
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Positive control: plain per-game wpa persists strongly (split-half r=+0.646, season-over-season r=+0.612) -- the machinery has ample power to detect a real skill of this shape.
Treatment: clutch_gap season-over-season r=-0.028 (n=1749) is squarely inside the shuffled null [-0.057,+0.060] (p=0.36). The odd/even split-half r=+0.047 nominally edges the null [-0.041,+0.044] (p=0.035), but odd/even halves share calendar structure -- importance rises late in the season, so any within-season drift in team context (trades, goalie changes, form) correlates the halves mechanically, and the label-shuffle null destroys exactly that timing link. The early/late robustness split, which removes the shared timing, gives r=-0.109 (n=760). With 6 metric x test combinations examined, one p=0.035 is unremarkable.

VERDICT: clutch is not a detectable persistent player skill in this data. Whatever a player's results-above-chances edge in high-importance games was, it carries essentially zero information about next season's edge (r ~ -0.03 vs a control r of +0.61), and the small within-season correlation is attributable to shared season context rather than the player. The same holds for the process (xgwpa) and results (wpa) gaps.

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5. CAREER CLUTCH_GAP LEADERBOARD (descriptive; min 150 games, min 30 in each bucket)
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rk player                    pos     GP  hi_n  lo_n  gap pp/gm
1  K. Lankinen               G      162    60    42    +11.215
2  I. Shesterkin             G      263    87    90    +10.687
3  S. Skinner                G      210    80    60     +9.721
4  P. Grubauer               G      182    56    60     +9.562
5  A. Vasilevskiy            G      292    94    94     +9.399
6  C. Atkinson               R      176    89    35     +9.066
7  M. Benning                D      157    46    48     +8.160
8  J. Swayman                G      222    76    81     +7.986
9  R. Sandin                 D      329   114   101     +7.923
10 Z. Hyman                  L      348   141    93     +7.865
11 K. Guhle                  D      203    74    54     +7.732
12 C. Miller                 D      231    62    84     +7.593
13 A. Peeke                  D      338   116   118     +7.065
14 M. Joseph                 R      296    87    98     +6.986
15 W. Kaiser                 D      166    34    70     +6.983

Read as: extra realized-over-expected win-probability flow (percentage points per game while on ice) in high- vs low-importance games, 2021-26 pooled.
Goalies dominate: the on-ice wpa-xgwpa residual is mostly saves above/below expected, and a goalie's biggest games are also the starts a coach hands him when he is running hot -- within-player selection, not clutch. Given the null persistence result, this list describes who HAS delivered results beyond chances in big games (variance's honor roll), not who WILL.