Week 9 Playoff Probabilities

Victor Decolongon

Below are the current playoff probabilities as of 3/23/13, with change in PP indicating change from 1 week ago. Tables are sortable, click on column heading.


Western Conference

Final Standings Team SAF% Playoff Probability Change Mean Points Current Points Current Rank Home/Road Diff
1 Chicago Blackhawks 54.50 100.0% 0.1% 73.80 51 1 4
2 Anaheim Ducks 47.83 99.6% 0.7% 66.59 48 2 0
3 Vancouver Canucks 52.86 88.6% 24.4% 58.60 38 4 -1
4 Los Angeles Kings 55.68 84.3% 18.7% 57.33 36 6 -3
5 St. Louis Blues 52.32 83.0% 13.5% 57.28 36 5 2
6 Minnesota Wild 48.39 78.2% 13.5% 56.57 38 3 0
7 Detroit Red Wings 52.01 62.7% 9.5% 53.89 35 7 -3
8 San Jose Sharks 50.52 53.8% 0.1% 52.46 32 9 4
9 Dallas Stars 50.04 44.4% 7.8% 51.50 33 8 1
10 Phoenix Coyotes 51.81 27.9% -12.1% 48.90 30 12 -3
11 Nashville Predators 46.85 21.4% -19.8% 48.36 32 10 4
12 Columbus Blue Jackets 46.48 14.8% -7.3% 47.05 32 11 -6
13 Calgary Flames 49.52 17.1% -16.8% 46.64 26 14 -1
14 Edmonton Oilers 45.71 15.5% -20.1% 46.57 29 13 2
15 Colorado Avalanche 48.38 8.8% -11.9% 44.64 26 15 0

(updated 3.23.2013 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 Pittsburgh Penguins 52.04 99.9% 2.6% 66.67 48 1 2
2 Boston Bruins 53.74 99.6% 1.9% 65.45 43 4 4
3 Winnipeg Jets 50.25 62.3% -6.9% 52.32 34 3 2
4 Montreal Canadiens 53.56 99.7% 2.0% 65.39 45 2 -1
5 Ottawa Senators 52.11 93.2% 17.5% 58.80 40 5 0
6 New Jersey Devils 52.44 74.3% 18.8% 54.50 36 7 -2
7 New York Rangers 52.53 63.0% 19.5% 52.66 32 9 -4
8 Toronto Maple Leafs 46.64 58.5% -2.0% 52.41 37 6 0
9 Carolina Hurricanes 50.95 60.8% -6.1% 52.01 32 8 0
10 New York Islanders 49.82 23.0% -20.3% 47.19 29 12 -5
11 Washington Capitals 47.95 21.9% 1.8% 46.71 29 11 1
12 Philadelphia Flyers 49.37 19.6% -9.5% 46.12 27 13 2
13 Buffalo Sabres 44.91 12.4% -6.9% 45.32 30 10 4
14 Tampa Bay Lightning 46.47 9.6% -12.3% 43.91 27 14 -1
15 Florida Panthers 48.47 2.2% -0.1% 40.64 24 15 -2

(updated 3.23.2013 at 12:12 AM PST)



Score Adjusted Fenwick%

Team SAF% SAF Rank FenClose% FenClose Rank diff
Los Angeles Kings 55.7 1 57.23 1 0
Chicago Blackhawks 54.5 2 54.66 3 -1
Boston Bruins 53.7 3 54.33 4 -1
Montreal Canadiens 53.6 4 53.42 8 -4
Vancouver Canucks 52.9 5 53.56 6 -1
New York Rangers 52.5 6 53.47 7 -1
New Jersey Devils 52.4 7 53.71 5 2
St. Louis Blues 52.3 8 54.77 2 6
Ottawa Senators 52.1 9 50.28 18 -9
Pittsburgh Penguins 52.0 10 51.34 12 -2
Detroit Red Wings 52.0 11 51.54 11 0
Phoenix Coyotes 51.8 12 50.56 15 -3
Carolina Hurricanes 51.0 13 52.25 9 4
San Jose Sharks 50.5 14 51.88 10 4
Winnipeg Jets 50.2 15 50.49 16 -1
Dallas Stars 50.0 16 50.46 17 -1
New York Islanders 49.8 17 49.77 20 -3
Calgary Flames 49.5 18 49.87 19 -1
Philadelphia Flyers 49.4 19 50.57 14 5
Florida Panthers 48.5 20 50.63 13 7
Minnesota Wild 48.4 21 47.27 22 -1
Colorado Avalanche 48.4 22 47.42 21 1
Washington Capitals 47.9 23 46.13 25 -2
Anaheim Ducks 47.8 24 46.55 24 0
Nashville Predators 46.8 25 46.62 23 2
Toronto Maple Leafs 46.6 26 45.52 26 0
Columbus Blue Jackets 46.5 27 44.76 28 -1
Tampa Bay Lightning 46.5 28 44.26 29 -1
Edmonton Oilers 45.7 29 45.09 27 2
Buffalo Sabres 44.9 30 44.18 30 0

(updated 3.23.2013 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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