# Power Play Save Percentage

I expanded my look at save percentages to power play data. Once again I calculated logits from the save percentages. I removed goalies with logits that were infinity or undefined. Power play save percentage looks a lot like the even strength data. Goalies differ, teams don't. Only here, some goalies are better than average.

Power Play versus Even Strength

There is a small correlation between even strength save percentage and power play save percentage. Power play save percentage is converted to “PPLogit” and even strength save percentage is converted to “RawLogit”.

>LinearModel.1 <- lm(PPLogit ~ RawLogit, data=PPData, weights=PPSA)
>anova(LinearModel.1)Analysis of Variance Table
Response:PPLogit
Df Sum Sq Mean Sq F value Pr(>F)
RawLogit 1 70.9 70.922 6.0878 0.01386 *
Residuals 676 7875.3 11.650

While the effect is statistically significant, the effect is of little practical significance.

Year Effect

Unlike even strength, there does not seem to be a year effect.

>LinearModel.3 <- lm(PPLogit ~ Year, data=PPData, weights=PPSA)
>anova(LinearModel.3)
Analysis of Variance Table
Response: PPLogit
Df Sum Sq Mean Sq F value Pr(>F)
Year 1 1.9 1.8913 0.1609 0.6884
Residuals 676 7944.4 11.7520

Team Effect

Taken by itself, there is no team effect.

>LinearModel.4 <- lm(PPLogit ~ Team, data=PPData, weights=PPSA)
>anova(LinearModel.4)
Analysis of Variance Table
Response: PPLogit
Df Sum Sq Mean Sq F value Pr(>F)
Team 29 428.6 14.779 1.2739 0.1548
Residuals 648 7517.6 11.601

Goalie Effect

Taken by itself, there is a significant goalie effect.

>LinearModel.2 <- lm(PPLogit ~ lastfirst, data=PPData, weights=PPSA)
>anova(LinearModel.2)
Analysis of Variance Table
Response: PPLogit
Df Sum Sq Mean Sq F value Pr(>F)
lastfirst 180 2641.1 14.673 1.3746 0.003857 **
Residuals 497 5305.1 10.674

Multiple Effects

Looking at Team, Year, and Goalie.

>LinearModel.5 <- lm(PPLogit ~ lastfirst+Team+Year, data=PPData, weights=PPSA)
>anova(LinearModel.5)
Analysis of Variance Table
Response: PPLogit
Df Sum Sq Mean Sq F value Pr(>F)
lastfirst 180 2641.1 14.6728 1.3640 0.005051 **
Team 29 275.7 9.5067 0.8837 0.643386
Year 1 5.7 5.7223 0.5319 0.466157
Residuals 467 5023.7 10.7574

Since Team and Year don’t seem to add anything, let’s take them out and compare the resulting model.

>LinearModel.6 <- lm(PPLogit ~ lastfirst, data=PPData, weights=PPSA)
>anova(LinearModel.6)
Analysis of Variance Table
Response: PPLogit
Df Sum Sq Mean Sq F value Pr(>F)
lastfirst 180 2641.1 14.673 1.3746 0.003857 **
Residuals 497 5305.1 10.674
>anova(LinearModel.5, LinearModel.6)
Analysis of Variance Table
Model 1: PPLogit ~ lastfirst + Team + Year
Model 2: PPLogit ~ lastfirst
Res.Df RSS Df Sum of Sq F Pr(>F)
1 467 5023.7
2 497 5305.1 -30 -281.42 0.872 0.6644

Comparing the two models shows we have not lost anything. For the coefficients of the final model, see the Appendix below.

Conclusions

Power play save percentage is best predicted by goaltender. Team and Year do not add resolving power to the model. The model predicts about 35% of the total variability seen in the data.

Appendix

 Coefficients: Estimate Std.Error tvalue Pr(>|t|) (Intercept) 2.167 0.282 7.676 0.000 lastfirst[T.HuetCristobal] 1.108 0.365 3.035 0.003 lastfirst[T.HowardJimmy] 1.519 0.527 2.884 0.004 lastfirst[T.RaskTuukka] 1.498 0.589 2.544 0.011 lastfirst[T.DafoeByron] 0.845 0.340 2.488 0.013 lastfirst[T.ThibaultJocelyn] 0.800 0.328 2.440 0.015 lastfirst[T.LeclairePascal] 0.929 0.388 2.393 0.017 lastfirst[T.ElliottBrian] 1.007 0.473 2.127 0.034 lastfirst[T.KiddTrevor] 0.738 0.350 2.112 0.035 lastfirst[T.BudajPeter] 0.777 0.380 2.046 0.041 lastfirst[T.VernonMichael] 0.755 0.385 1.963 0.050 lastfirst[T.TheodoreJose] 0.605 0.326 1.857 0.064 lastfirst[T.GiguereJean-Sebastien] 0.595 0.321 1.854 0.064 lastfirst[T.KhabibulinNikolai] 0.538 0.313 1.718 0.086 lastfirst[T.VokounTomas] 0.509 0.314 1.624 0.105 lastfirst[T.ShieldsSteve] 0.576 0.357 1.615 0.107 lastfirst[T.NoronenMika] 0.944 0.607 1.556 0.120 lastfirst[T.MarkkanenJussi] 0.786 0.514 1.531 0.126 lastfirst[T.NorrenaFredrik] 0.721 0.473 1.524 0.128 lastfirst[T.DanisYann] 0.866 0.607 1.427 0.154 lastfirst[T.BryzgalovIlya] 0.513 0.372 1.377 0.169 lastfirst[T.MillerRyan] 0.424 0.324 1.308 0.192 lastfirst[T.HasekDominik] 0.394 0.317 1.244 0.214 lastfirst[T.CloutierDan] 0.401 0.343 1.169 0.243 lastfirst[T.SmithMike] 0.479 0.415 1.154 0.249 lastfirst[T.JosephCurtis] 0.360 0.315 1.142 0.254 lastfirst[T.BurkeSean] 0.390 0.345 1.129 0.260 lastfirst[T.KiprusoffMiikka] 0.362 0.323 1.122 0.263 lastfirst[T.LehtonenKari] 0.384 0.344 1.115 0.265 lastfirst[T.HnilickaMilan] 0.472 0.425 1.112 0.267 lastfirst[T.GerberMartin] 0.394 0.356 1.107 0.269 lastfirst[T.HealyGlenn] 0.598 0.541 1.104 0.270 lastfirst[T.LalimePatrick] 0.364 0.330 1.100 0.272 lastfirst[T.PriceCarey] 0.444 0.405 1.096 0.274 lastfirst[T.IrbeArturs] 0.356 0.326 1.090 0.276 lastfirst[T.CechmanekRoman] 0.409 0.376 1.088 0.277 lastfirst[T.NiemiAntti] 0.830 0.767 1.082 0.280 lastfirst[T.WaiteJimmy] 0.830 0.767 1.082 0.280 lastfirst[T.GrahameJohn] 0.410 0.387 1.062 0.289 lastfirst[T.SaloTommy] 0.351 0.331 1.060 0.290 lastfirst[T.BelfourEd] 0.330 0.314 1.052 0.293 lastfirst[T.RolosonDwayne] 0.337 0.328 1.026 0.305 lastfirst[T.RanfordBill] 0.634 0.627 1.011 0.313 lastfirst[T.ToivonenHannu] 0.427 0.471 0.906 0.366 lastfirst[T.KolzigOlie] 0.282 0.316 0.894 0.372 lastfirst[T.TurcoMarty] 0.281 0.321 0.878 0.381 lastfirst[T.DipietroRick] 0.303 0.346 0.875 0.382 lastfirst[T.BacashihuaJason] 0.542 0.643 0.842 0.400 lastfirst[T.TurekRoman] 0.299 0.356 0.839 0.402 lastfirst[T.HackettJeff] 0.324 0.406 0.798 0.425 lastfirst[T.NabokovEvgeni] 0.248 0.312 0.795 0.427 lastfirst[T.BrathwaiteFred] 0.261 0.352 0.742 0.458 lastfirst[T.ToskalaVesa] 0.258 0.349 0.738 0.461 lastfirst[T.DenisMarc] 0.239 0.325 0.735 0.462 lastfirst[T.BironMartin] 0.231 0.326 0.710 0.478 lastfirst[T.LegaceManny] 0.230 0.333 0.692 0.489 lastfirst[T.NiittymakiAntero] 0.252 0.367 0.689 0.491 lastfirst[T.HedbergJohan] 0.234 0.345 0.677 0.499 lastfirst[T.RamoKarri] 0.416 0.620 0.671 0.502 lastfirst[T.FitzpatrickMark] 0.484 0.737 0.656 0.512 lastfirst[T.MasonChris] 0.238 0.366 0.651 0.515 lastfirst[T.ThomasTim] 0.218 0.341 0.640 0.522 lastfirst[T.RoyPatrick] 0.206 0.325 0.633 0.527 lastfirst[T.VarlamovSemyon] 0.542 0.864 0.627 0.531 lastfirst[T.NurminenPasi] 0.231 0.381 0.606 0.545 lastfirst[T.HebertGuy] 0.212 0.369 0.574 0.566 lastfirst[T.LaBarberaJason] 0.236 0.433 0.545 0.586 lastfirst[T.OsgoodChris] 0.172 0.319 0.540 0.589 lastfirst[T.SabourinDany] 0.473 0.890 0.531 0.596 lastfirst[T.BrodeurMartin] 0.163 0.310 0.528 0.598 lastfirst[T.AubinJean-Sebastien] 0.189 0.370 0.510 0.610 lastfirst[T.WardCam] 0.171 0.336 0.509 0.611 lastfirst[T.FernandezManny] 0.173 0.340 0.508 0.612 lastfirst[T.LuongoRoberto] 0.157 0.310 0.506 0.613 lastfirst[T.RichterMike] 0.165 0.336 0.492 0.623 lastfirst[T.PuppaDaren] 0.245 0.550 0.446 0.656 lastfirst[T.QuickJonathan] 0.181 0.462 0.393 0.694 lastfirst[T.EscheRobert] 0.164 0.433 0.380 0.704 lastfirst[T.ConklinTy] 0.158 0.425 0.373 0.710 lastfirst[T.McLeanKirk] 0.187 0.517 0.361 0.718 lastfirst[T.GaronMathieu] 0.125 0.363 0.345 0.730 lastfirst[T.VanbiesbrouckJohn] 0.124 0.364 0.340 0.734 lastfirst[T.SanfordCurtis] 0.150 0.450 0.334 0.738 lastfirst[T.TugnuttRon] 0.115 0.364 0.315 0.753 lastfirst[T.RhodesDamian] 0.109 0.363 0.299 0.765 lastfirst[T.LeightonMichael] 0.137 0.475 0.289 0.773 lastfirst[T.BarrassoTom] 0.113 0.403 0.279 0.780 lastfirst[T.PavelecOndrej] 0.169 0.627 0.269 0.788 lastfirst[T.FleuryMarc-Andre] 0.085 0.327 0.259 0.795 lastfirst[T.SnowGarth] 0.093 0.362 0.256 0.798 lastfirst[T.FuhrGrant] 0.099 0.438 0.227 0.821 lastfirst[T.DunhamMike] 0.068 0.333 0.203 0.839 lastfirst[T.AuldAlex] 0.067 0.400 0.168 0.867 lastfirst[T.ShtalenkovMikhail] 0.075 0.534 0.140 0.889 lastfirst[T.HrudeyKelly] 0.085 0.767 0.110 0.912 lastfirst[T.EllisDan] 0.048 0.462 0.104 0.917 lastfirst[T.AndersonCraig] 0.041 0.402 0.102 0.919 lastfirst[T.EssensaBob] 0.039 0.385 0.101 0.920 lastfirst[T.BoucherBrian] 0.035 0.355 0.097 0.922 lastfirst[T.DeslauriersJeff] 0.047 0.594 0.079 0.937 lastfirst[T.ErsbergErik] 0.041 0.660 0.063 0.950 lastfirst[T.MacDonaldJoey] 0.031 0.589 0.052 0.959 lastfirst[T.WeekesKevin] 0.017 0.342 0.049 0.961 lastfirst[T.BerkhoelAdam] 0.031 1.071 0.028 0.977 lastfirst[T.ChiodoAndy] 0.031 1.071 0.028 0.977 lastfirst[T.FisetStephane] 0.011 0.385 0.028 0.977 lastfirst[T.HirschCorey] 0.031 1.071 0.028 0.977 lastfirst[T.McElhinneyCurtis] 0.031 1.071 0.028 0.977 lastfirst[T.ClemmensenScott] 0.003 0.523 0.005 0.996 lastfirst[T.MasonSteve] -0.004 0.450 -0.010 0.992 lastfirst[T.HardingJosh] -0.015 0.475 -0.031 0.975 lastfirst[T.LeneveuDavid] -0.056 0.607 -0.093 0.926 lastfirst[T.LundqvistHenrik] -0.033 0.337 -0.096 0.923 lastfirst[T.GarnettMichael] -0.088 0.820 -0.107 0.915 lastfirst[T.TerreriChris] -0.073 0.660 -0.111 0.911 lastfirst[T.HurmeJani] -0.062 0.558 -0.112 0.911 lastfirst[T.OuelletMaxime] -0.110 0.890 -0.123 0.902 lastfirst[T.StorrJamie] -0.060 0.373 -0.160 0.873 lastfirst[T.LangkowScott] -0.221 1.189 -0.185 0.853 lastfirst[T.PetersJustin] -0.221 1.189 -0.185 0.853 lastfirst[T.ReeseJeff] -0.221 1.189 -0.185 0.853 lastfirst[T.FankhouserScott] -0.168 0.712 -0.236 0.814 lastfirst[T.MoogAndy] -0.152 0.627 -0.241 0.809 lastfirst[T.RaycroftAndrew] -0.097 0.344 -0.283 0.777 lastfirst[T.JohnsonBrent] -0.106 0.372 -0.284 0.777 lastfirst[T.CousineauMarcel] -0.375 1.267 -0.296 0.768 lastfirst[T.PotvinFelix] -0.118 0.383 -0.308 0.758 lastfirst[T.CharpentierSebastien] -0.295 0.890 -0.331 0.741 lastfirst[T.RousselDominic] -0.295 0.890 -0.331 0.741 lastfirst[T.BackstromNiklas] -0.145 0.372 -0.389 0.698 lastfirst[T.PassmoreSteve] -0.206 0.527 -0.391 0.696 lastfirst[T.FichaudEric] -0.260 0.660 -0.394 0.694 lastfirst[T.RinnePekka] -0.183 0.458 -0.399 0.690 lastfirst[T.BrochuMartin] -0.558 1.363 -0.409 0.683 lastfirst[T.SkudraPeter] -0.170 0.413 -0.411 0.681 lastfirst[T.HextallRon] -0.207 0.502 -0.413 0.680 lastfirst[T.TellqvistMikael] -0.201 0.473 -0.425 0.671 lastfirst[T.EmeryRay] -0.196 0.378 -0.519 0.604 lastfirst[T.GarnerTyrone] -0.781 1.488 -0.524 0.600 lastfirst[T.SalakAlexander] -0.781 1.488 -0.524 0.600 lastfirst[T.WhitmoreKay] -0.781 1.488 -0.524 0.600 lastfirst[T.HodsonKevin] -0.432 0.783 -0.551 0.582 lastfirst[T.McKennaMike] -0.432 0.783 -0.551 0.582 lastfirst[T.HillerJonas] -0.249 0.441 -0.564 0.573 lastfirst[T.BlackburnDan] -0.302 0.534 -0.565 0.572 lastfirst[T.ValiquetteSteve] -0.558 0.984 -0.566 0.571 lastfirst[T.DivisReinhard] -0.489 0.712 -0.687 0.492 lastfirst[T.HolmqvistJohan] -0.403 0.583 -0.690 0.490 lastfirst[T.TabaracciRichard] -0.383 0.523 -0.733 0.464 lastfirst[T.PrusekMartin] -0.538 0.724 -0.742 0.458 lastfirst[T.ColemanGerald] -1.474 1.907 -0.773 0.440 lastfirst[T.GageJoaquin] -1.474 1.907 -0.773 0.440 lastfirst[T.GustafsonDerek] -1.474 1.907 -0.773 0.440 lastfirst[T.HauserAdam] -1.474 1.907 -0.773 0.440 lastfirst[T.KochanDieter] -1.474 1.907 -0.773 0.440 lastfirst[T.MorrisonMichael] -1.474 1.907 -0.773 0.440 lastfirst[T.TrefilovAndrei] -1.474 1.907 -0.773 0.440 lastfirst[T.WilkinsonDerek] -1.474 1.907 -0.773 0.440 lastfirst[T.MaracleNorm] -0.424 0.538 -0.789 0.430 lastfirst[T.TallasRobbie] -0.481 0.568 -0.848 0.397 lastfirst[T.LabbeJean-Francois] -1.068 1.189 -0.898 0.370 lastfirst[T.HalakJaroslav] -0.452 0.477 -0.946 0.345 lastfirst[T.DubielewiczWade] -0.499 0.527 -0.948 0.344 lastfirst[T.ParentRich] -1.242 1.267 -0.980 0.328 lastfirst[T.MunroAdam] -1.251 1.267 -0.987 0.324 lastfirst[T.YeremeyevVitali] -1.251 1.267 -0.987 0.324 lastfirst[T.McLennanJamie] -0.476 0.434 -1.096 0.273 lastfirst[T.CassiviFrederic] -1.159 1.025 -1.131 0.259 lastfirst[T.CaronSebastien] -0.499 0.432 -1.155 0.249 lastfirst[T.BillingtonCraig] -0.556 0.465 -1.196 0.232 lastfirst[T.WreggetKen] -0.886 0.737 -1.201 0.230 lastfirst[T.NeuvirthMichal] -0.837 0.689 -1.215 0.225 lastfirst[T.MossTyler] -1.317 1.071 -1.230 0.219 lastfirst[T.BierkZac] -0.733 0.583 -1.257 0.209 lastfirst[T.SchwabCorey] -0.621 0.477 -1.301 0.194 lastfirst[T.GreissThomas] -1.474 1.125 -1.310 0.191 lastfirst[T.FlahertyWade] -1.065 0.724 -1.470 0.142 lastfirst[T.LamotheMarc] -2.860 1.907 -1.499 0.134 lastfirst[T.LarocqueMichel] -2.860 1.907 -1.499 0.134 lastfirst[T.SauvePhilippe] -1.474 0.890 -1.656 0.098 lastfirst[T.JablonskiPat] -2.572 1.488 -1.728 0.085