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NHL Re-alignment: What would the 2010-2011 season look like? (Updated)

After I heard about the NHL re-alignment I was curious as to how the scheduling might effect team balance. Specifically which teams would make the playoffs, and if there would be significant changes in league standings. Personally I'm for the re-alignment because it will generate greater rivalries and fans get to see every team. Of course the down side is that some conferences will be weaker than others, and it will create an imbalance in the later playoffs, but I think the benefits greatly outweigh the potential problems. To the batcave!

Methods

I used a montecarlo simulation to re-create the 2010-2011 season 10,000 times. I initially generated win probabilities using 2 models as shown below. The first model is based on 2010-2011 GF/G and GA/G data for each team. I ran this through Alan Ryder's PrWin function that calculates the competing Poisson probability of a win. I then used these win probabilities for the 1230 games played during a simulated season. Some nerd stuff in brackets [During a simulated season a win, OT win, or SO win and respective losses were predicted by generating a random number between 0 and 1. A win was assigned if the random number was <= the win probability, a OT win was assigned if the random number was <= the win probability + OT win probability, and lastly a 2nd random number generated to determine (with 50% chance) a SO win. OT loss points were assigned accordingly. 10,000 seasons were simulated and the data from each season was collected and analyzed.] The 2nd model uses road Fenwick%. With this model I assumed a constant Fenwick sh% for every team (0.067), and used Fenwick data to determine GF/G and GA/G. This was then run through the model described above.

Results / Discussion

All tables are sortable for your pleasure (click on the table headers for sorting).

***Updated table below combined the 2 previous tables below showing teams by conference instead.

Conf Team Wins Ties Losses Mean Pts PO Prob Wins Ties Losses Mean Pts PO Prob
A ANAHEIM 41.34 10.02 30.64 92.70 0.421 34.33 9.86 37.81 78.51 0.053
A CALGARY 42.70 10.02 29.27 95.43 0.562 44.40 9.92 27.68 98.71 0.786
A COLORADO 30.39 9.46 42.15 70.23 0.005 36.50 9.94 35.56 82.94 0.127
A EDMONTON 29.28 9.55 43.17 68.11 0.002 34.40 9.93 37.67 78.73 0.052
A LOS ANGELES 43.34 10.32 28.33 97.01 0.639 41.92 10.12 29.96 93.96 0.580
A PHOENIX 41.96 10.12 29.92 94.04 0.499 41.58 9.87 30.55 93.03 0.534
A SAN JOSE 46.68 10.02 25.29 103.39 0.876 46.79 9.91 25.30 103.49 0.909
A VANCOUVER 54.05 9.40 18.55 117.51 0.997 48.57 9.68 23.75 106.83 0.960
Conf Team Wins Ties Losses Mean Pts PO Prob Wins Ties Losses Mean Pts PO Prob
B CHICAGO 46.53 9.95 25.52 103.00 0.915 47.90 9.75 24.35 105.55 0.930
B COLUMBUS 34.30 9.90 37.79 78.51 0.059 45.25 9.90 26.84 100.41 0.800
B DALLAS 40.47 10.17 31.36 91.11 0.455 36.91 10.02 35.07 83.84 0.119
B DETROIT 44.48 9.97 27.55 98.94 0.811 44.67 9.75 27.58 99.09 0.751
B MINNESOTA 36.93 10.22 34.85 84.08 0.172 31.70 9.57 40.72 72.98 0.009
B NASHVILLE 45.25 10.40 26.35 100.90 0.871 41.52 10.06 30.43 93.09 0.460
B ST LOUIS 42.54 10.10 29.36 95.19 0.670 45.22 9.97 26.81 100.41 0.806
Conf Team Wins Ties Losses Mean Pts PO Prob Wins Ties Losses Mean Pts PO Prob
C ATLANTA 33.84 9.83 38.33 77.52 0.049 37.16 9.84 34.99 84.17 0.125
C BOSTON 50.89 9.77 21.33 111.56 0.998 42.36 9.91 29.72 94.64 0.655
C BUFFALO 43.38 10.07 28.55 96.83 0.874 43.72 9.89 28.38 97.34 0.763
C FLORIDA 35.63 10.26 36.11 81.52 0.206 38.97 9.93 33.10 87.87 0.324
C MONTREAL 42.49 10.35 29.16 95.33 0.839 44.32 9.85 27.83 98.49 0.806
C OTTAWA 31.72 9.91 40.37 73.35 0.043 41.26 10.08 30.67 92.59 0.548
C TAMPA BAY 42.47 10.12 29.40 95.07 0.829 45.65 9.95 26.39 101.26 0.877
C TORONTO 35.79 10.08 36.13 81.66 0.212 32.46 9.67 39.87 74.59 0.027
Conf Team Wins Ties Losses Mean Pts PO Prob Wins Ties Losses Mean Pts PO Prob
D CAROLINA 40.06 10.14 31.80 90.26 0.344 34.54 9.71 37.75 78.78 0.107
D NEW JERSEY 33.84 10.45 37.72 78.12 0.042 43.84 10.19 27.97 97.87 0.869
D NY ISLANDERS 34.98 9.92 37.11 79.87 0.058 35.17 9.90 36.93 80.24 0.149
D NY RANGERS 45.62 10.27 26.11 101.51 0.870 37.66 9.91 34.43 85.23 0.323
D PHILADELPHIA 47.25 9.92 24.84 104.41 0.925 41.88 10.00 30.12 93.75 0.746
D PITTSBURGH 46.21 10.17 25.62 102.59 0.893 44.95 9.95 27.09 99.86 0.912
D WASHINGTON 45.58 10.31 26.11 101.48 0.869 44.39 10.06 27.55 98.85 0.894

On the left of the tables above represents model 1, in which I used Goal Differential as the predicting variable. The right side of the tables is model 2, which uses road Fenwick%. The numbers are the average(mean) for its respective category after 10,000 seasons.

The interesting thing that pops up here is the difference in the 2 models. Model 1 (Goal Diff) results are much more similar to the previous year's data. I think it shows how goal diff is a more descriptive stat (meaning it explains previous data, but isnt as predictive). The Fenwick% numbers don't look quite like the 2010-2011 year, but we know from prior analysis that it is more predictive. Hence the numbers we see are regressed to league average as compared to goal diff. I suspect that if we repeated the season with the exact same teams model 2 would be more accurate. The most egregious Fenwick offenders (Dallas, Minn, etc.) show the biggest discrepancy. But it does also show how some teams may have been under-estimated (T.B, STL, OTT, N.J).

The tables above also show playoff probabilities using both models. The numbers represent the percentage of trials that the team made the playoffs under re-alignmnet. Lots to discuss here. the 2010-2011 BOS and NYR teams had a terrible road Fenwick%. That could be because of small sample size (only 41 games to work with), but its interesting that according to the model they miss the playoffs about 44% and 68% of the time respectively (A nod to NASH as well). On the other end of the spectrum is Chicago, N.J and Columbus. CHI barely made the playoffs in the 2010-2011 season, yet under both models they are predicted to make the playoffs above 90% of the time. It really shows how strong a team they were, despite a terrible (unlucky) record.

Team Top 5 Top 10 Middle 10 Bottom 10 Bottom 5 Top 5 Top 10 Middle 10 Bottom 10 Bottom 5
ANAHEIM 0.054 0.214 0.584 0.202 0.030 0.001 0.012 0.158 0.829 0.523
CALGARY 0.095 0.324 0.549 0.128 0.015 0.253 0.525 0.397 0.078 0.011
COLORADO 0.000 0.000 0.031 0.969 0.789 0.008 0.041 0.286 0.673 0.309
EDMONTON 0.000 0.000 0.020 0.979 0.852 0.001 0.011 0.164 0.825 0.505
LOS ANGELES 0.131 0.394 0.514 0.091 0.008 0.107 0.303 0.510 0.187 0.040
PHOENIX 0.073 0.269 0.565 0.166 0.023 0.090 0.272 0.503 0.225 0.046
SAN JOSE 0.365 0.702 0.280 0.018 0.001 0.455 0.741 0.236 0.023 0.002
VANCOUVER 0.928 0.988 0.012 0.000 0.000 0.621 0.853 0.139 0.007 0.001
CHICAGO 0.354 0.681 0.299 0.021 0.001 0.561 0.811 0.177 0.012 0.000
COLUMBUS 0.001 0.008 0.180 0.812 0.425 0.318 0.607 0.345 0.049 0.005
DALLAS 0.039 0.172 0.565 0.263 0.046 0.008 0.047 0.322 0.631 0.276
DETROIT 0.193 0.493 0.445 0.062 0.005 0.263 0.545 0.389 0.066 0.008
MINNESOTA 0.005 0.037 0.376 0.588 0.191 0.000 0.002 0.051 0.947 0.761
NASHVILLE 0.251 0.583 0.384 0.034 0.003 0.089 0.270 0.513 0.218 0.048
ST LOUIS 0.093 0.319 0.547 0.134 0.016 0.314 0.610 0.340 0.051 0.005
ATLANTA 0.001 0.007 0.148 0.846 0.468 0.010 0.049 0.331 0.620 0.260
BOSTON 0.760 0.938 0.061 0.001 0.000 0.126 0.336 0.494 0.171 0.033
BUFFALO 0.127 0.390 0.513 0.096 0.009 0.199 0.451 0.452 0.097 0.017
FLORIDA 0.002 0.019 0.279 0.702 0.286 0.026 0.112 0.452 0.436 0.145
MONTREAL 0.097 0.327 0.539 0.134 0.017 0.237 0.526 0.394 0.081 0.011
OTTAWA 0.000 0.002 0.068 0.930 0.664 0.082 0.251 0.510 0.239 0.056
TAMPA BAY 0.090 0.311 0.554 0.136 0.017 0.348 0.645 0.313 0.042 0.005
TORONTO 0.002 0.021 0.280 0.699 0.277 0.000 0.004 0.078 0.919 0.696
CAROLINA 0.032 0.146 0.558 0.297 0.055 0.001 0.012 0.159 0.829 0.507
NEW JERSEY 0.001 0.008 0.167 0.825 0.445 0.214 0.483 0.427 0.090 0.014
NY ISLANDERS 0.002 0.013 0.220 0.767 0.352 0.003 0.019 0.210 0.771 0.439
NY RANGERS 0.285 0.617 0.352 0.031 0.002 0.014 0.064 0.371 0.565 0.227
PHILADELPHIA 0.415 0.739 0.246 0.016 0.001 0.105 0.292 0.513 0.195 0.039
PITTSBURGH 0.324 0.667 0.309 0.024 0.001 0.292 0.577 0.365 0.058 0.007
WASHINGTON 0.282 0.611 0.357 0.033 0.002 0.254 0.530 0.399 0.070 0.009

Lastly we have league standings, again separated by the 2 models. Each number represents the percentage of trials in which a team fell into the category listed in the header.

Pretty similar data to above just presented in league standings format. I hope you find some fun with the tables. Although I'll be pretty severely limited by time in the next few months, I plan on creating similar tables for this year's data, projecting playoff probabilities under the current format.

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