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Playoff net goals: the model's value chain on 1,395 playoff games

Producer: playoff_ng_study.py (2026-09-17), on the playoff outputs of the chain scripts' --playoffs modes (build_shot_ledger.py, build_playoff_components.py, gax_gsax_v2.py, extract_penalties.py, extract_faceoffs.py, build_ng_attribution.py). Universe: every playoff game 2010-11 to 2025-26 (16 postseasons, 1,395 games, 121,805 priced attempts, 5,439 skater-postseasons, 417 goalie-postseasons).

Question. The site prices every skater in net goals added per 82 games versus a league-average player, from regular-season games only. What are the same players worth in the playoffs, in the same units, and does the playoff number tell us anything the regular one does not?

Method. The playoff games go through the unchanged regular-season chain: shots priced by the season-matched xG v2 model; every second of every shift priced by the strength-aware win-probability table; each shift's actual priced flow compared with the league-average expectation for its context (score, clock, skaters, zone start) from the regular-season context table; finishing, penalties and faceoffs at the same calibrated prices; the same per-season re-centring biases. A playoff value is therefore "net goals versus a league-average regular-season player in that season's environment" and compares directly with the regular number. Nothing is re-centred on the playoff pool itself, which is a stronger and tighter field. Three playoff-specific rules:

1. The playoff environment against the regular-season baseline

GP-weighted mean value of a playoff skater-game, per 82 games, versus the same for regular-season skater-games (which re-centre to about zero by construction).

ComponentPlayoffs (NG/82)Regular season (NG/82)
EV offense-0.40+0.02
EV defense+0.39-0.00
Power play+0.11+0.00
Penalty kill-0.09+0.00
Finishing-0.29+0.03
Penalties-0.05+0.01
Faceoffs+0.00+0.00
Overall-0.32+0.05

Goalies: league playoff GSAx +179.6 over 2,995 goalie-games (+4.92 per 82 starts), against the regular-season xG which nets to zero by season. The playoff field converts below the regular-season model on both sides: shooters finish below expectation and goalies above it, which is the tightening the playoff-translation study measured as shot quality rather than volume. Even-strength on-ice value nets to about zero, as it must when both teams' skaters are priced.

By postseason (GP-weighted skater Overall per 82, league playoff GSAx per goalie-game):

PostseasonGamesSkater Overall/82Finishing/82Goalie GSAx/game
2010-1189-0.09-0.03-0.010
2011-1286-0.71-0.69+0.172
2012-1386-0.97-1.10+0.261
2013-1493+0.35+0.38-0.089
2014-1589-0.36-0.30+0.091
2015-1691-0.08-0.10+0.014
2016-1787-0.46-0.37+0.052
2017-1884+0.30+0.40-0.109
2018-1987-1.07-1.01+0.205
2019-2086-0.48-0.49+0.113
2020-2184-1.12-1.04+0.245
2021-2289-0.47-0.48+0.090
2022-2388+0.44+0.40-0.085
2023-2488-0.11+0.02-0.002
2024-2586+0.31+0.28-0.055
2025-2682-0.71-0.58+0.120

2. What translates: same-season regular value vs playoff value

Skater-postseasons with at least 8 playoff GP and a regular-season row (10+ GP): n = 2,278. Correlation and slope of the playoff rate on the same-season regular rate, weighted by playoff GP. A slope near 1 means the regular number is an unbiased guide to the playoff number; the correlation says how much of one run the regular season explains.

Componentr (weighted)slopeplayoff SD/82regular SD/82
EV offense0.510.632.31.8
EV defense0.290.522.11.2
Power play0.450.691.20.8
Penalty kill0.180.341.00.5
Finishing0.140.237.24.3
Penalties0.400.602.51.6
Faceoffs0.670.810.60.5
Overall0.320.498.75.7

Faceoffs and even-strength offense carry best; finishing barely carries within a run (a run is 20-100 shots). The playoff SDs are 2-3 times the regular ones because they are 8-28 game samples, not because playoff skill is more spread out.

Even-strength by position (same sample):

PositionnEV offense rEV defense rOverall r
Forwards1,5150.540.270.31
Defensemen7630.430.320.29

3. Career playoff net goals

Skaters with 40+ playoff GP, by total playoff net goals (the sum over runs; NG/82 is that total per 82 games; the last column is the player's career regular-season NG/82 for comparison). Full table: playoff_ng_career.csv.

#PlayerPosRunsGPPlayoff NGNG/82EV offEV defPPPKFinRegular NG/82
1Leon DraisaitlC798+25.5+21.3+4.6-0.6+3.0+0.0+12.2+18.4
2Brad MarchandL13177+23.9+11.1+2.1+1.8+0.4+0.4+6.7+11.1
3Logan CoutureC8101+18.7+15.1+2.4-0.1+2.9+0.0+7.4+7.0
4Brayden PointC996+18.5+15.8+2.1+1.3+0.7+0.0+9.1+12.2
5Joe PavelskiC12158+18.0+9.4+1.1+1.2+2.5-0.0+1.1+10.1
6Cale MakarD887+17.6+16.6+3.1+2.3+1.9-0.6+6.6+12.4
7Steven StamkosC11128+15.9+10.2-0.1+1.1-0.8-0.3+9.1+12.9
8Jake GuentzelC877+15.6+16.6+2.9+0.7+0.4+0.4+10.9+6.2
9Mark StoneR11126+15.1+9.8+0.0+0.6+1.1-0.3+7.5+9.1
10Ondrej PalatL10152+15.1+8.1+0.8+0.8-0.2+0.2+6.1+2.5
11Sidney CrosbyC11120+14.8+10.1+3.1+0.4+0.5+0.4+2.2+11.5
12Evan BouchardD581+14.8+15.0+3.9+1.2+2.6-0.0+6.1+6.1
13Nathan MacKinnonC10105+14.0+10.9+3.2+0.8+1.5+0.0+3.6+7.1
14Vladimir TarasenkoR12130+13.5+8.5-0.7+0.2-0.3+0.1+7.2+7.6
15Mikko RantanenR9102+13.3+10.7+2.4+0.6+1.4-0.3+5.5+10.9
16William KarlssonC9123+12.7+8.4+1.1+1.2+0.5-0.3+3.9+4.2
17Chris KreiderL10132+12.3+7.7+0.2-0.6-0.1+0.1+10.7+4.5
18David PastrnakR993+12.3+10.9+1.1+1.4+0.9-0.1+5.9+13.9
19Andre BurakovskyL890+11.3+10.3+0.8+1.6+0.0-0.0+7.1+4.1
20Nikita KucherovR12156+11.2+5.9+1.5+1.3+0.2+0.1+1.9+13.4
21Connor McDavidC798+10.7+8.9+5.4+0.2+3.1+0.2-3.9+15.1
22T.J. OshieR1299+10.2+8.4-0.9+0.5+0.2+0.2+6.5+8.2
23Mark ScheifeleC752+10.2+16.0+1.9-1.0-0.3+0.3+13.4+8.6
24Alex OvechkinL13130+9.6+6.1+2.6+0.2+0.5-0.0+3.0+10.3
25David KrejciC10130+9.5+6.0-0.3+0.7+0.1+0.3+5.1+3.7

Bottom of the same table (40+ GP):

PlayerPosRunsGPPlayoff NGNG/82Regular NG/82
Brian BoyleC10120-11.1-7.6-0.5
Brayden SchennC879-9.9-10.2+1.5
Jay BouwmeesterD675-9.1-9.9-4.1
Ryan McDonaghD15200-8.8-3.6+0.0
Darnell NurseD796-8.2-7.0-3.7
Cody CeciD8105-8.1-6.4-3.7
Esa LindellD7106-8.0-6.2-0.7
William CarrierL8112-7.8-5.7-0.6
Jacob TroubaD782-7.7-7.7-4.1
Brad RichardsC583-7.5-7.4+3.1

Highest playoff rate with 60+ GP:

PlayerPosGPNG/82Regular NG/82
Leon DraisaitlC98+21.3+18.4
Jake GuentzelC77+16.6+6.2
Cale MakarD87+16.6+12.4
Brayden PointC96+15.8+12.2
Logan CoutureC101+15.1+7.0
Evan BouchardD81+15.0+6.1
Morgan RiellyD65+11.6-0.3
Brad MarchandL177+11.1+11.1
Nathan MacKinnonC105+10.9+7.1
David PastrnakR93+10.9+13.9
Jason RobertsonL62+10.7+13.9
Mikko RantanenR102+10.7+10.9

Goalies with 20+ playoff games, by total playoff GSAx (goals saved above the regular-season xG model; per-82 rate and the career regular-season rate alongside):

#GoalieRunsGamesShotsPlayoff GSAxGSAx/82Regular GSAx/82
1Henrik Lundqvist7982936+37.0+30.9+21.1
2Igor Shesterkin3431448+35.1+67.0+32.3
3Andrei Vasilevskiy111243675+31.5+20.8+21.4
4Jonathan Quick7862551+28.1+26.8-1.4
5Tuukka Rask7892765+27.6+25.5+8.1
6Braden Holtby8942809+27.3+23.8+5.5
7Mike Smith5441551+18.2+33.9+5.4
8Craig Anderson5421362+17.3+33.7-6.2
9Ben Bishop4511459+13.4+21.5+13.4
10Jakub Dobes222623+11.8+44.1+23.6
11Tim Thomas3331058+11.5+28.7+17.3
12Jeremy Swayman526735+9.5+29.9+16.8
13Robin Lehner427679+9.0+27.3+7.8
14Anton Khudobin325762+8.7+28.5+10.5
15Corey Crawford8912772+8.2+7.4+15.3
16Carey Price7692076+7.8+9.3+9.3
17Jimmy Howard6361104+7.5+17.2-3.5
18Adin Hill330852+6.5+17.7-4.4
19Matt Murray5491327+6.1+10.2+6.0
20Sergei Bobrovsky111133247+5.4+3.9+11.3

4. Is there a playoff performer? The gap, run to run

For every skater-postseason with 8+ playoff GP, the gap = playoff NG/gm minus the same season's regular NG/gm. If some players reliably raise (or lower) their game in the spring, a player's gap in one run should predict his gap in his next run. Pairs are a player's consecutive qualifying runs no more than three seasons apart; the null is 500 shuffles of the gaps within each postseason.

Consecutive-run pairs: 1,116 (967 skaters with a qualifying run).

Quantityr (run to run)null meannull 95% bandp
gap, Overall+0.003-0.000[-0.061, +0.066]0.902
gap, EV offense+0.016+0.012[-0.040, +0.069]0.904
gap, EV defense+0.087+0.007[-0.051, +0.071]0.004
gap, Power play+0.019+0.004[-0.049, +0.060]0.628
gap, Finishing-0.014-0.002[-0.060, +0.051]0.680
raw playoff Overall (control)+0.198
same-season regular Overall (control)+0.557

Read: the raw playoff number persists because talent persists (and the regular-season number, which is the talent estimate, persists far more). The playoff-minus-regular gap is what a "playoff performer" would have to carry, and its run-to-run correlation is what the table shows. This repeats the playoff-translation study's verdict in the model's own units.

5. Where the numbers live