Neutral Winning Percentage
Copyright Iain Fyffe, 2002
This essay describes a method for evaluating goaltenders which is, in theory, free from bias created by the team the goalie plays for and the teams he faces. It developed from an idea proposed by Marc Foster, president of the Hockey Research Association. This idea was to adapt Michael Wolverton's support-neutral pitcher records for used in hockey.
Support-neutral records remove the effect of team offence from a pitcher’s won-lost record, thereby producing a result that more fairly evaluates a pitcher’s performance. Foster proposed to adapt this method to calculate offence-neutral records for goaltenders, as follows.
Each goaltender’s season is broken down by the number of times which he allows zero goals in a game, one goal in a game, two goals, and so on. The records for all teams in the league are then broken down based on the number of goals they allowed in each game. We then use these league numbers to compute an expected record for the goaltender, based on the number of times he allowed each number of goals against.
For instance, the breakdown by goals against for the 2000/01 NHL season is as follows:
| GA | # | W | W% | L | L% | T | T% |
| 0 | 186 | 172 | .92 | 0 | .00 | 14 | .08 |
| 1 | 406 | 316 | .78 | 28 | .07 | 62 | .15 |
| 2 | 595 | 340 | .57 | 141 | .24 | 114 | .19 |
| 3 | 520 | 171 | .33 | 275 | .53 | 74 | .14 |
| 4 | 365 | 58 | .16 | 275 | .75 | 32 | .09 |
| 5 | 228 | 16 | .07 | 206 | .90 | 6 | .03 |
| 6 | 111 | 5 | .05 | 104 | .94 | 2 | .01 |
| 7+ | 49 | 0 | .00 | 49 | .00 | 0 | .00 |
| 2460 | 1078 | 1078 | 304 |
So, if a goalie allows 2 goals in a game, we expect him to win 57% of the time, lose 24% of the time, and tie 19%. We therefore give him credit for 0.57 wins, 0.24 losses, and 0.19 ties for each game in which he allows 2 goals. We multiply the number of games in which he allows each number of goals by the appropriate factors for wins, losses and ties. Adding the results gives us a won-lost-tied record. We then convert the record into a winning percentage, so we can compare goaltenders directly.
This winning percentage is offence-neutral. The number of goals the goaltender’s team scores has no effect upon the percentage. The bias resulting from playing for a high- or low-scoring team is eliminated.
Foster’s idea, as presented above, is a good first step. But we can go further and remove even more team-related bias from a goaltender’s record. This is, in fact, the point of this exercise: to remove all team effects from a goalie’s record, so we can evaluate the goalie based solely upon his efforts.
We have already eliminated the distortion caused by team offence. Two types of distortion remain: distortion from team defence, and distortion from opponent’s offence. Fortunately, both of these can be compensated for.
Distortion from team defence
In the essay entitled “Goaltender Perseverance: a Useless Stat”, I demonstrate that the number of shots a goalie faces is a function of his team. Thus, a goaltender who faces a large number of shots is being unfairly penalized for playing for his particular team. This distortion must be removed to effectively compare goaltenders.
To control for this distortion, we should not evaluate a goalie based on the actual number of goals he allows, but on the number of goals he would allow when facing an average number of shots. In this was, we remove the bias resulting from facing a high or low number of shots.
Unfortunately, some distortion will remain. Team defence affects not only the number of shots faced, but the quality of shots faced. However, this distortion cannot be removed because we cannot determine the effect it has on a goalie’s save percentage. Still, this distortion is present in all methods currently used for evaluating goaltenders (including save percentage), so even if it is present in Neutral Winning Percentage, this method is still an improvement.
Distortion from opponent's offence
The idea here is basically the same as Keith Woolner’s Pitcher’s Quality of Opposition. If a goalie faces teams who are more better shooters (that is, have higher scoring percentages), he will give more goals, even when his shots against are normalized.
A goaltender’s adjusted goals against in a game (based on average shots) should therefore be further adjusted, depending on the shooting percentage of the team faced. When facing a team with an above-average shooting percentage, the goals against would be adjusted downward, reflecting the greater challenge faced. Conversely, a low-shooting-percentage team produces an upward adjustment.
Application of the method
For each game, the goaltender’s actual save percentage for that game is applied to an adjusted number of shots to produce an adjusted number of goals against. This goals against figure is rounded to the nearest whole number, since it is impossible to allow 2.3 goals in a game (for example).
The adjusted shots against is calculated thusly:
LgShotsPerGame x (LgShootPct/OppShootPct)
Where:
LgShotsPerGame is the total shots in the league divided by the total games played in the league
LgShootPct is the total goals in the league divided by the total shots in the league
OppShootPct is the opponent’s goals divided by the opponent’s shots
Each level of adjusted goals against (0,1,2...) is compiled for each goaltender, and the record is then computed as described earlier.
One further thing needs discussion: what to do when a goalie does not play a full game. In such a case, the same process is used, but instead of receiving credit for a full game, the goalie receives credit for whatever portion of the opponent's shots he faced. For instance, if a goaltender faces half the shots in a game, the resulting wins, losses and ties for that game are each multiplied by one-half.
2000/01 NHL results
I computed the Neutral Winning Percentage (NWP) for all goalies for the 2000/01 NHL season. Complete results follow. For discussion purposes, here are the leaders and trailers in NWP (minimum 30 ‘decisions’):
| Leaders | Trailers | |||||
| 1. | Manny Fernandez | .611 | 1. | Dan Cloutier | .430 | |
| 2. | Mike Dunham | .610 | 2. | J.S.Aubin | .437 | |
| 3. | Dominik Hasek | .604 | 3. | Mike Vernon | .449 | |
| 4. | Yevgeny Nabokov | .599 | 4. | Trevor Kidd | .451 | |
| 5. | Sean Burke | .594 | 5. | Guy Hebert | .452 | |
| 6. | Roman Cechmanek | .593 | Mike Richter | .452 | ||
| Roberto Luongo | .593 | 7. | Bob Essensa | .456 | ||
| 8. | Manny Legace | .566 | 8. | Marc Denis | .456 | |
| 9. | Ron Tugnutt | .556 | 9. | Jocelyn Thibault | .472 | |
| 10. | Patrick Lalime | .554 | 10. | Damian Rhodes | .482 | |
| Patrick Roy | .554 |
So, even though Fernandez and Dunham were marginally better, Hasek was a good choice as Vezina winner. It remains to be seen whether the young goalies, such as Fernandez, Dunham, Nabokov, Luongo and Legace, will be able to maintain their high levels of performance. Players like Vernon and Richter seem to be surviving on reputation alone.
One of the great advantages of this method is that numbers from one year to the next are directly comparable. Since NWP is based on the averages for that season, we need make no further adjustments to compare different seasons. A .600 NWP is just as impressive in 2000/01 as it is in 1990/91 or 1980/81.
2000/01 NHL Neutral Winning Percentages
| Goalie | Team(s) | Dec | NWP | Goalie | Team(s) | Dec | NWP | ||
| Aebischer | Col | 23.0 | .489 | Kochan | TB | 5.1 | .422 | ||
| Aubin | Pgh | 34.2 | .437 | Kolzig | Wsh | 70.8 | .545 | ||
| Belfour | Dal | 60.9 | .541 | LaBarbera | NYR | 0.1 | 1.000 | ||
| Bierk | Min | 1.0 | .100 | Lalime | Ott | 59.7 | .554 | ||
| Billington | Wsh | 10.9 | .583 | Larocque | Chi | 2.5 | .240 | ||
| Biron | Buf | 15.3 | .529 | Legace | Det | 35.0 | .566 | ||
| Boucher | Phi | 24.8 | .355 | Luongo | Fla | 43.4 | .593 | ||
| Brathwaite | Cgy | 44.5 | .528 | Maracle | Atl | 12.5 | .448 | ||
| Brodeur | NJ | 69.8 | .527 | Mason | Nsh | 0.9 | .389 | ||
| Burke | Phx | 59.8 | .594 | McLean | NYR | 20.3 | .451 | ||
| Cechmanek | Phi | 56.4 | .593 | McLennan | Min | 36.4 | .533 | ||
| Cloutier | TB-Van | 31.5 | .430 | Moss | Car | 9.2 | .250 | ||
| Dafoe | Bos | 41.4 | .545 | Nabokov | SJ | 60.9 | .599 | ||
| Denis | Clb | 30.2 | .465 | Naumenko | Ana | 1.2 | .083 | ||
| Dipietro | NYI | 18.2 | .390 | Noronen | Buf | 1.9 | .395 | ||
| Dunham | Nsh | 46.5 | .610 | Osgood | Det | 46.9 | .504 | ||
| Esche | Phx | 22.2 | .471 | Ouellet | Phi | 1.3 | .538 | ||
| Essensa | Van | 34.0 | .456 | Parent | Pgh | 5.3 | .509 | ||
| Fankhouser | Atl | 4.3 | .535 | Passmore | LA-Chi | 17.6 | .497 | ||
| Fernandez | Min | 40.5 | .611 | Potvin | Van-LA | 57.3 | .496 | ||
| Fichaud | Mtl | 1.0 | .550 | Raycroft | Bos | 10.8 | .454 | ||
| Fiset | LA | 5.3 | .377 | Rhodes | Atl | 34.0 | .482 | ||
| Flaherty | NYI-TB | 18.5 | .389 | Richter | NYR | 43.8 | .452 | ||
| Fountain | Ott | 0.9 | .389 | Roussel | Ana-Edm | 16.6 | .434 | ||
| Gage | Edm | 4.4 | .307 | Roy | Col | 58.9 | .554 | ||
| Garon | Mtl | 9.2 | .505 | Salo | Edm | 71.7 | .507 | ||
| Giguere | Ana | 33.5 | .534 | Scott | LA | 0.4 | .000 | ||
| Grahame | Bos | 7.9 | .418 | Shields | SJ | 18.6 | .548 | ||
| Gustafson | Min | 4.0 | .463 | Skudra | Bos | 18.5 | .384 | ||
| Hackett | Mtl | 16.3 | .387 | Snow | Pgh | 33.5 | .525 | ||
| Hasek | Buf | 64.2 | .604 | Tallas | Chi | 10.5 | .405 | ||
| Healy | Tor | 14.3 | .339 | Terreri | NJ-NYI | 14.7 | .422 | ||
| Hebert | Ana-NYR | 49.8 | .452 | Theodore | Mtl | 54.9 | .530 | ||
| Hedberg | Pgh | 9.1 | .560 | Thibault | Chi | 63.4 | .472 | ||
| Hirsch | Wsh | 0.3 | 1.000 | Tugnutt | Clb | 51.8 | .556 | ||
| Hnilicka | Atl | 31.0 | .495 | Turco | Dal | 21.1 | .609 | ||
| Holmqvist | NYR | 2.0 | .300 | Turek | StL | 53.1 | .505 | ||
| Hurme | Ott | 21.3 | .491 | Vanbiesbrouck | NYI-NJ | 43.4 | .486 | ||
| Irbe | Car | 72.7 | .545 | Vernon | Cgy | 37.1 | .449 | ||
| Johnson | StL | 28.0 | .546 | Vokoun | Nsh | 34.6 | .542 | ||
| Joseph | Tor | 67.6 | .538 | Weekes | TB | 55.5 | .509 | ||
| Khabibulin | TB | 2.0 | .525 | Whitmore | Bos | 3.6 | .139 | ||
| Kidd | Fla | 38.7 | .451 | Yeremeyev | NYR | 3.6 | .208 | ||
| Kiprusoff | SJ | 2.6 | .558 |
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