Real Time Super Stats: Part II

JustinM suggested that I repeat the analysis I did in my first article, but that this time I should only use road stats to eliminate rink bias. I initially didn't want to do this because I thought it would be a pain to separate out the home and road data, but NHL.com actually already does that. So with that in mind, I'm going to look at road-only stats to see if rink bias was driving the results in my previous article. 

I repeated the analysis that I described in my first article, but I only used road stats this time. Here are the numbers over the past five seasons (regular season points were only for road games):

Hits

BS

GV

TK

Reg. Pts.

ANA

4485

2289

1464

1151

214

ATL

3813

3069

1549

1230

195

BOS

4058

2880

1675

1317

217

BUF

3328

2934

1692

1373

237

CAR

3619

2781

1524

1261

209

CBJ

3691

2595

1381

1193

163

CGY

4179

2334

1444

1057

202

CHI

3501

2652

1440

1281

198

COL

3021

3082

1389

1170

201

DAL

3592

2519

1364

1110

225

DET

3156

2170

1580

1285

265

EDM

3442

2887

1648

1149

185

FLA

3597

2983

1560

1247

183

LAK

3672

2703

1481

1169

183

MIN

3131

2539

1605

1283

186

MTL

3924

2979

1590

1212

211

NJD

3829

2859

1505

1263

236

NSH

3241

2484

1410

1114

216

NYI

3849

3053

1470

1196

165

NYR

4092

2760

1627

1216

219

OTT

4065

2854

1655

1280

222

PHI

4125

2958

1352

1231

211

PHX

3574

2763

1619

1257

189

PIT

3770

3023

1729

1419

212

SJS

3800

2418

1459

1141

253

STL

3678

3016

1340

1247

191

TBL

3553

2878

1462

1317

179

TOR

3933

2761

1668

1217

192

VAN

3434

2500

1546

1293

213

WSH

3911

2548

1405

1190

207

I then did a correlation analysis between reg. pts. and each individual stat. The results:

Rtss_road_r_table_medium

In the first analysis, Hits had an "r"coefficient of +0.01. Since there was basically no change in this analysis (meaning rink bias did not affect the total numbers), this is very clear proof that how many hits a team racks up has nothing to do with winning. 

The "r" coefficient in the first analysis for BS was -0.47. While the "r" for road-only stats was weaker, it's still relatively strong on the whole. The conclusion regarding blocked shots is still the same: if you're blocking more shots than average, you're not playing good hockey. 

Giveaways saw a slight increase in significance in this analysis, as the previous "r" was +0.09. While this number moves it out of the "no relationship" category and into the "small relationship" category, it's still too little to draw anything meaningful from it. Giveaways don't have a real correlation with winning, yet the sign on both of these "r's" indicates that our intuition regarding giveaways is a bit off. Ignoring the fact that the "r" is too small, the positive signs tell us that teams with more giveaways are earning more points. This makes sense, as teams with more giveaways have the puck more, and teams that have the puck more tend to win more games than average in the long-run. 

Takeaways also saw an increase in this analysis, as it jumped from -0.01 in my last piece. However, the "r" is barely in the "small relationship" category, so it would be ill-advised to try and draw anything meaningful from these numbers. 

Overall, these results were what I suspected. I didn't think rink bias would have skewed the original data too much, mainly because I think it's an overblown issue in hockey. These real time stats have roughly the same correlation with winning on the road as they do when looking at home and road stats combined. I'm not sure if these numbers are a knock against the rink bias claim, but they're interesting, at least to me. 

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