Monday, 8 September 2014

Updates: Sept 8th

Shot Quality

After some serious fence-sitting I've decided to do what many have been asking for: Adjusting Shot Quality, and therefore Expected GF%, by the player's previous shooting% record. This means that Exp. GF%, shot quality and all the other statistics that rely on that model to predict shooting percentage will be stronger, as they don't just use the variables of the individual shot as previously was the case but also his shooting% from the past 3 seasons, if applicable.

Multiple Seasons

In the player and team stat pages, you can now compute statistics for multiple seasons at a time.

Enjoy the updates! Much more to come.

Tuesday, 2 September 2014

A Beginning

Hello and welcome to This site will be a place where you can access advanced hockey statistics and analysis.

You will notice some small and large differences to what you may have found at other fancystats websites. Here are a few big features to our stats.


Relative stats have taken on a whole new meaning. Instead of simply the entire team's performance when the player is off the ice , relative is calculated as the average performance of his actual on ice teammates and competition without the player in question, weighted by their ice time with him. This provides a much more meaningful metric to evaluate players with.

Exp GF%:

You will notice a 4th stat besides corsi, fenwick and goals for percentages: Exp. GF%, or expected GF%. Exp GF% is simply a player's on ice fenwick weighted by the quality of the shot. I outline the methodology for calculating shot quality here, and a player's own average shot quality is also listed.

Adjusting for Score State and Zone starts:

Score close metrics have been firmly rooted in advanced hockey stat methodology for some time now, but there are many issues:

1)  There is still variance in shooting rates even within the score close definition. I go into detail about this here.

2) Score close removes a whole swath of data, which significantly cuts down on the power of the sample size.

To solve this, and the effect of the variance in the ratio of offensive to defensive zone starts for players, a logistic regression is used to parse out the player-neutral odds that can effect shot differentials. If you wish to use this method when using the stats, simply click 'Yes' on the Adjusting for Zone Starts and Score State option.

I think there's a lot for hockey fans to love here, and this site will continuously develop so be sure to check back often!