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".

 

Ppraw_medium

 

>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

 

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