Photo credit: Rob Carr
Not all goals are created equal. A team scoring first has almost twice the win percentage of a team that trails first, while scoring an empty net goal almost always means the game was out of reach. But what about all the goals scored in between? Of all those goals that a player scores, how many contribute to victories and how vitally do they contribute?
There is a direct relationship between how many goals a club scores and allows to its won-lost record, often called the Pythagorean expectation. The formula is pretty simple: win% = GF^2/GF^2+GA^2 where GF = goals for, GA = goals against, and ^ means “raised to the power of”, in this case, 2.
For example, last year Washington scored 318 goals and allowed 233, for a Pythagorean win expectation of 318^2/(318^2+233^2) = .651 or 53 games out of 82. They won 54 games last year.
Using this we can weight the value of each goal scored this year to how much it increased the Capitals chance of winning. A goal scored in a 0-0 game has more of an impact on the outcome than the fifth goal in a 7-0 blowout. Scoring in one-goal games will always be at a premium. Washington has already matched their total of 1-goal games (41) from last year, making those goals even more meaningful. I will say there are obvious limitations, such as ignoring assists to give a better picture of who is contributing overall to wins and I am looking into adding this metric — as well as other improvements — to future iterations.
In the table below, goals are the skater’s current goal total this season through game 75. Total Win% Added is the cumulative sum of how much all his goals increased the teams chances of winning and W% added per goal is the average increase that player’s goal contributes to the team’s chances of winning.
Player | Goals | Win% Added | W% added Per goal |
Alex Ovechkin | 29 | 4.53 | 15.6% |
Alexander Semin | 25 | 2.65 | 10.6% |
Mike Knuble | 20 | 2.84 | 14.2% |
Nicklas Backstrom | 18 | 4.36 | 24.2% |
Brooks Laich | 16 | 2.94 | 18.4% |
Marcus Johansson | 12 | 3.13 | 26.1% |
Eric Fehr | 10 | 1.82 | 18.2% |
Jason Chimera | 8 | 1.21 | 15.1% |
Matt Hendricks | 8 | 1.33 | 16.6% |
Mike Green | 8 | 1.56 | 19.5% |
Mathieu Perreault | 7 | 1.64 | 23.5% |
John Carlson | 6 | 1.15 | 19.1% |
Matt Bradley | 4 | 0.50 | 12.5% |
Boyd Gordon | 3 | 0.79 | 26.2% |
John Erskine | 3 | 0.56 | 18.7% |
Jason Arnott | 2 | 0.10 | 5.1% |
Jay Beagle | 2 | 0.11 | 5.7% |
Karl Alzner | 2 | 0.79 | 39.3% |
Tom Poti | 2 | 0.24 | 11.9% |
Andrew Gordon | 1 | 0.50 | 50.0% |
Dennis Wideman | 1 | 0.00 | 0.0% |
Jeff Schultz | 1 | 0.50 | 50.0% |
Scott Hannan | 1 | 0.50 | 50.0% |
Tyler Sloan | 1 | 0.11 | 11.4% |
Let’s start with the three skaters who have eight goals so far on the season: Jason Chimera, Matt Hendricks and Mike Green. On average, a goal scored by Chimera adds a 15.1% chance at a win, while Hendricks’ tallies add 16.6%. Then there’s Mike Green, who’s robust 19.5% shows us why his nickname is “Game Over.”
When Alex Semin scores a goal the Caps are 23-0, but a look at the table shows that he increases the chances of a Caps’ win by about 10% with each one — far less than some of the others atop the leaderboard. Here’s why: almost half his goals have no significant impact on winning. Ten have come when the Caps already have the lead, six when the score is tied and the rest when the Caps trail.
The most intriguing values, at least to me, are those of the centers. Across the board they seem to be higher than the other skaters prompting me to take a look at last year’s values as well. Backstrom’s average contribution is significantly higher this year (24.2%) than last year (14.9%) despite having almost twice as many goals, while Boyd Gordon is relatively even, seeing 26% this year vs. last year’s 30% average contribution. Which brings us to the rookies, Mathieu Perreault and Marcus Johansson, both of whom seem to score goals when it counts.
So what does this all mean? Perhaps this is a different way of looking at who has been “most valuable.” Perhaps Semin’s goals are just windrow dressing and have less impact on the game than we think. Perhaps we are one step closer to defining what “clutch” play truly is — or if it even exists.
Perhaps I just have too much time on my hands.
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