Sabres have best shot at Connor McDavid, analytics suggest

Now that we’re officially more than halfway into the season we’re starting to get a clearer picture of which teams are contenders and which are pretenders.

However, there is still a lot of hockey left to play, and there will be a fair bit of movement up and down the standings. So what should we expect in the second half?

In order to answer this question, we gathered data (from and on midseason points, various possession metrics, goal differential and shooting and save percentages for every team after 41 games, starting with the 2007-08 season, but excluding the lockout-shortened season on 2012-13. The goal was to see which combination of these variables was best at predicting teams’ second half point totals.

You’d certainly be excused if you thought that looking at a team’s first half points was the best way to predict its second half points. After 41 games, the standings must certainly reflect a team’s true ability, right?

As it turns out, second half performance is best predicted by two of the most commonly used variables in the analytics repertoire: Score Adjusted Corsi and PDO.

For those not familiar with these concepts, Corsi is another name for shot attempts (shots on goal, missed shots, and blocked shots).  “Score Adjusted” Corsi (SAC) is a stat that, as the name suggests, adjusts Corsi to account for the power of score effects. “Score effects” describes the tendency for teams that are trailing in a game to amp up the offense and attempt significantly more shots. This matters because if you look at Corsi without any adjustments, awful teams (who are playing from behind a lot) look better than they really are and great teams (who are often defending a lead) don’t look as strong as they truly are.

PDO is simpler – it is just the sum of a team’s shooting percentage and save percentage. So, for example, if the Carolina Hurricanes have a team shooting percentage of 6.1% and a save percentage of 90.8%, their PDO is 96.9.

What was interesting, however, was that basing predictions on two variables did only marginally better than looking at just SAC alone. The fact that SAC is one of the best predictors of future success is a result found by almost everyone doing hockey analytics. In general, however, predictions can usually be improved by using more information. In this particular case, what we find is that second half points are very hard to predict, and that, to the extent we can predict them, SAC is really all you need.

Also interesting is the fact that, to the extent that a second variable can improve predictive power, PDO is the best choice. Note that, when considering PDO in isolation, it has very little predictive value. This is generally thought to be because a team’s shooting and save percentage at the midseason point are very noisy measures of its true abilities in that regard. However, it turns out that the information embedded in PDO, shrouded in noise as it may be, is different enough from the information embedded in SAC, that it is the best complement.

Regardless, the predictions generated by these variables still leave a lot of room for error. In recent years teams have produced as many as 67 points in the second half (the 2009-10 Washington Capitals), or as few as 21 (the 2010-11 Colorado Avalanche), and the model can only explain about 20% of that variation. However, they’re still the best data (out of what we looked at) to base any predictions on. So what do they predict?

First, our model predicts the playoff teams will be the ones that held such a spot at the halfway mark. No surprise there, but what is interesting is the significant shuffling of seeding. Nashville should cool off from its torrid start (60 points in the first half), but is still predicted to clinch the best record in the league, just barely holding off Chicago. Buffalo, meanwhile, is predicted to get the best shot at Connor McDavid in the lottery as Edmonton is predicted to recover from its disastrous first half by posting a much improved second half record (better than 5 other teams including Calgary and Toronto). They, along with Carolina, are predicted to show the most improvement in the second half, bettering their first half point totals by 16 points each. Edmonton will, however, still end up 2nd last overall and Carolina 3rd last. The biggest drop-offs are for Anaheim (predicted to amass 12 fewer second half points than they did in the first half) and Montreal (11 fewer).

At the end of the day, however, a good takeaway from this is that second half performance is surprisingly difficult to predict. You might think you have a good handle on your team, but chances are things won’t play out as they did in the first half. Which is just as well – isn’t that why we watch?


Team First Half Points Predicted Second Half Predicted End of Season Team First Half Points Predicted Second Half Predicted End of Season
NASHVILLE 60 49 109 PITTSBURGH 56 49 105
CHICAGO 56 52 108 TAMPA BAY 54 51 105
ANAHEIM 58 47 105 NY ISLANDERS 55 49 104
ST LOUIS 53 48 101 DETROIT 53 50 103
LOS ANGELES 47 50 97 WASHINGTON 52 48 100
SAN JOSE 49 48 97 MONTREAL 55 45 100
WINNIPEG 47 49 96 NY RANGERS 52 48 100
VANCOUVER 49 46 95 FLORIDA 49 47 96
DALLAS 43 47 90 BOSTON 46 48 94
MINNESOTA 41 47 88 OTTAWA 42 45 87
CALGARY 45 40 85 TORONTO 45 41 86
ARIZONA 36 43 79 COLUMBUS 39 41 80
EDMONTON 27 43 70 NEW JERSEY 35 44 79
CAROLINA 30 46 76
BUFFALO 31 31 62


1 Comment

  1. Phil Curry's Gravatar Phil Curry
    February 3, 2015    

    Interesting - thanks for sharing the link!

  1. Awful First Half Teams Will Stay Awful on February 2, 2015 at 9:36 pm

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