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Statistical Analysis

Week 8 Playoff Probabilities

Yes we're over half way, and yes, your team's point totals have had a lot to do with luck.

Below are the current playoff probabilities as of 3/16/13, with change in PP indicating change from 2 weeks ago. Tables are sortable, click on column heading.

The details of the model used to come up with these numbers has come up a few times, and it's been awhile since I explained it in detail, so check out the methods section below for a full disclosure.

Western Conference

Final Standings Team SAF% Playoff Probability Change Mean Points Current Points Current Rank Home/Road Diff
1 Chicago Blackhawks 54.41 99.9% 1.5% 70.90 49 1 2
2 Anaheim Ducks 47.85 98.9% 6.1% 67.38 44 2 3
3 Minnesota Wild 48.79 64.7% 14.3% 54.85 32 3 -1
4 St. Louis Blues 52.09 69.5% 10.5% 55.74 34 4 0
5 Los Angeles Kings 56.02 65.6% 5.1% 55.04 32 6 1
6 Vancouver Canucks 52.64 64.2% -5.2% 54.77 32 7 -1
7 Detroit Red Wings 52.00 53.2% 6.7% 53.22 33 5 -3
8 San Jose Sharks 49.97 53.7% -4.7% 53.03 30 8 1
9 Phoenix Coyotes 51.37 40.0% -6.5% 50.94 30 9 -4
10 Nashville Predators 46.03 41.2% -3.2% 50.81 28 10 4
11 Dallas Stars 50.24 36.6% -9.8% 50.03 27 12 1
12 Edmonton Oilers 46.30 35.6% -5.9% 49.89 26 14 5
13 Calgary Flames 49.95 33.9% 1.1% 49.34 26 13 -4
14 Columbus Blue Jackets 47.04 22.1% 11.7% 47.96 28 11 -5
15 Colorado Avalanche 48.63 20.7% -22.1% 46.95 24 15 1

(updated 3.17.2013 at 12:12 AM PST)

Eastern Conference

Final Standings Team Score Adj Fenwick% Playoff Probability Change in PP Mean Points Current Points Current Rank Home/Road Diff
1 Boston Bruins 53.81 97.7% 4.7% 64.83 41 4 0
2 Pittsburgh Penguins 52.44 97.3% 18.8% 63.05 42 2 3
3 Winnipeg Jets 51.13 69.2% 23.6% 54.50 32 3 4
4 Montreal Canadiens 52.05 97.7% 14.1% 63.74 42 1 0
5 Ottawa Senators 51.56 75.7% 5.8% 56.04 34 5 2
6 Carolina Hurricanes 51.18 66.9% 3.1% 54.04 31 8 1
7 Toronto Maple Leafs 46.46 60.5% -9.9% 53.09 32 6 1
8 New Jersey Devils 52.33 55.5% -11.2% 52.57 32 7 -1
9 New York Islanders 49.83 43.3% 16.0% 50.44 29 9 -2
10 New York Rangers 52.42 43.5% -3.0% 50.30 28 10 -3
11 Philadelphia Flyers 49.63 29.1% -13.4% 48.08 27 11 1
12 Tampa Bay Lightning 46.32 21.9% -11.9% 46.50 25 12 -2
13 Buffalo Sabres 45.62 19.3% -6.6% 46.32 24 13 2
14 Washington Capitals 48.51 20.1% -9.6% 45.84 23 14 -1
15 Florida Panthers 48.41 2.3% -20.5% 40.01 20 15 -5

(updated 3.17.2013 at 12:12 AM PST)

This week I added fenwick close, as well as the difference in rank between these stats. As you can see, SJS are by far an outlier.

Score Adjusted Fenwick%

Team SAF% SAF Rank FenClose% FenClose Rank diff
Los Angeles Kings 56.0 1 57.65 1 0
Chicago Blackhawks 54.4 2 55.27 2 0
Boston Bruins 53.8 3 54.81 4 -1
Vancouver Canucks 52.6 4 53.66 6 -2
New York Rangers 52.4 6 53.53 7 -1
New Jersey Devils 52.3 7 53.71 5 2
Pittsburgh Penguins 52.4 5 51.76 10 -5
St. Louis Blues 52.1 8 54.85 3 5
Detroit Red Wings 52.0 10 51.64 11 -1
Montreal Canadiens 52.0 9 53.36 8 1
Ottawa Senators 51.6 11 50.28 19 -8
Carolina Hurricanes 51.2 13 52.73 9 4
Phoenix Coyotes 51.4 12 50.46 17 -5
Winnipeg Jets 51.1 14 50.36 18 -4
Dallas Stars 50.2 15 50.52 16 -1
San Jose Sharks 50.0 16 51.2 12 4
Calgary Flames 50.0 17 50.88 13 4
New York Islanders 49.8 18 49.57 20 -2
Philadelphia Flyers 49.6 19 50.78 14 5
Colorado Avalanche 48.6 21 47.63 21 0
Washington Capitals 48.5 22 46.21 23 -1
Minnesota Wild 48.8 20 47.42 22 -2
Florida Panthers 48.4 23 50.7 15 8
Anaheim Ducks 47.9 24 45.97 24 0
Columbus Blue Jackets 47.0 25 44.04 29 -4
Toronto Maple Leafs 46.5 26 44.8 27 -1
Edmonton Oilers 46.3 28 45.67 26 2
Tampa Bay Lightning 46.3 27 43.89 30 -3
Nashville Predators 46.0 29 45.92 25 4
Buffalo Sabres 45.6 30 44.07 28 2

(updated 3.17.2013 at 12:12 AM PST)


Methods

The model is a monte carlo simulation of the remainder of the season. I simulate somewhere between 10 and 20 thousand seasons, recording the points and standings position of each team every season. Based on these results I calculate the "playoff probability" which is the percent of sims that a team finishes 8th or better in its conference.


There are a lot of ways to simulate the remainder of the season. I choose to use score-adjusted Fenwick, as it it is best predictor of future success. I grab Fenwick by score data from btn, adjust it for score effects, then regress to the % talent based on the average number of games the league has played thus far. I generate Fenwick For and Against from this proportion based on league average Fenwick events per game.


For each simulated season I give each team a shooting and save percentage randomly, based on a normal distribution expected by chance for the remainder games, and integrate this into their current shooting and save percentage as necessary (at even-strength, this isn't necessary). This gives me a goals per game, and goals against per game for each team for each season.


For the remaining games I generate a end regulation score using a Poisson distribution based on the teams' goals per game and goals against calculated from above, adjusted by their opponent's goals and goals against per game. For tie games, I randomly choose a winner. For games within 1 goal, I adjust for empty net by turning 1 goal games into tied games 12% of the time.


I've simulated enough seasons to ensure that the average points per game for remaining games comes out to about 1.118 over a sufficient number of seasons, and the distribution of points follows a similar distribution based on actual data.


The variables that really end up mattering in the model are games remaining, whether or not those are home vs. away, opponent's remaining, and of course SAF. In total home/away games remaining ends up mattering the most because generally teams are huddled around the mean for SAF, and the strength of the opponents remaining usually ends up being pretty similar.


An important point about this method, is that I have not formally evaluated the sensitivity and specificity of the model. After doing this for awhile, this approach seems the most realistic (with the exception of excluding PP and PK situations, OT scoring), and gives results that most closely align with the point distributions expected..

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