Hockey Reference is excited to introduce a new advanced hockey statistic we're calling Expected +/-. This new metric, utilizing league-wide shot location data, shows what we'd expect a player's +/- to be, based on where his team's shots and his opponent's shots came from while we has on the ice in even strength situations. The expected value of these shots is based upon league-wide shooting percentages from the various locations.
We have calculated the statistic for 2014-15 thus far, and will be calculating it for seasons moving forward, as well. As we get more shot location data, these values will eventually be based on three-year rolling averages, but as of now, 2014-15 is based entirely upon 2014-15 shot location data. When we say three-year rolling averages, what we mean is that, eventually, 2015-16 Expected +/- will be based upon shooting percentages from various locations on the ice from 2014-15 to 2016-17.
Here's the 2014-15 leaders:
As you can see, the Expected +/- leaderboard differs quite a bit from the actual +/- leaderboard, with only Nikita Kucherov appearing in the top ten of both. Expected +/- can potentially help identify some of the luck factor in raw +/- numbers:
Since this metric considers the quality of shots (or at least their point of origin), it has an advantage over blunter instruments, like Corsi, which consider quantity, but not quality. However, unlike Corsi, Expected +/- does not include info on shots that weren't on goal, that were blocked, etc. So we see the stats as good complements for each other.
Currently, Expected +/- can be found for all players on the advanced tab of the 2014-15 Skaters register. Additionally, it can found in the Miscellaneous table on player pages.
On a game level, we have added shot charts to our box scores, as well. In the future, we plan to add heat maps showing shooting percentages by location for players, goalies, teams and league seasons. We will also be incorporating Expected +/- into our Player Advanced Stats Finder to allow for customized searches on this metric.
Finally, we would like to thank Wesley Yue for his valuable contributions to this concept.