If you've been checking out the NBA win probability site, you've probably noticed a link for the NHL too. The probabilities are calculated based on the method I outlined in this post. The model now includes power plays, a unique and important factor in hockey.
Latest play descriptions are also included at each point in the graph, which is similar to how the football graphs will work in the fall. The most challenging part of whole project has been automatically adding notes to the graph where the goals were scored. They frequently overlap or overflow off the graph, and the logic of how to arrange them is far more challenging than you'd think.
I don't know much about hockey despite my frequent attendance at Capitals games in high school, and this has been a great way to look at the sport from a different perspective. I realize there aren't nearly as many hockey fans as football fans, but hey, a ten thousand Canadians can't be wrong...or however many Canadians there are. I missed that day at school.
The conference finals start today, so check it out. And if you're not interested in hockey, pass the word to your friends who are.
NHL Win Probability
Live NHL Win Probability
Epic Bulls-Celtics Series
If you haven’t been paying attention to this series you’re missing one of the most exciting 7-game series ever, even if it’s just the first round.
Going into Thursday night’s game, there were already 3 OT games and 1 last second buzzer-beater game. Then this happened: A 3OT potential elimination game that featured multiple furious comebacks for both teams and ultimately tied the series 3-3 with a 1-point win by Chicago. These two teams are as evenly matched as it gets. They square off for Game 7 tonight at 8.
Here are all 6 games of the series so far.
Compared to basketball or football, the hockey graphs aren't as compelling at first glance, at least during the game. But a quick look at a graph after the game tells a dramatic story you just won’t get with a box score. Below is Thursday night’s Game 1 between Chicago and Vancouver.
5-3? Well, that doesn’t sound terribly exciting. But check out what happened: 3-0 lead held until the third period. With 10 minutes left in the game, another goal, and with 5 min left another to tie it 3-3. Then Vancouver gets the game-winning goal with less than 2 min to go. Then in the final seconds, a garbage goal with the goalie pulled makes it 5-3.
You can check out the beta version of the hockey graphs for today's Caps-Penguins and Blackhawks-Canucks games. Power plays have not been factored in yet, but that's in progress, and it should be ready early next week.
NHL In-Game Win Probability
I was at an NHL game the other night, and with the score 2-0 someone asked me, “So Mr. Win Probability, what’s the chance the Capitals win?” I was caught off guard, and after I choked out, “I…don’t…know…,” I experienced the horror that is not knowing the exact up-to-the-second win probability of a sporting contest. Don’t let this happen to you.
The anxiety and shame lasted for two days straight. I kept blaming myself and replaying the incident over and over in my head. The only way to cure my depression was to build a win probability model for NHL hockey.
Unlike my previous models for basketball and football which were empirically based, my hockey model is theoretical. In other words, instead of being based on a massive database of actual previous games, the probabilities are calculated based on a Poisson scoring distribution. The distribution is calculated using the average goals scored per minute in the 2008-9 NHL season. It’s an extension of the model I developed in this post.
Teams score an average of 2.79 goals per 60 minutes of regulation time, which is equal to 0.0465 goals per minute. A Poisson distribution based on that per-minute scoring rate and the time remaining in the game yields the probabilities of each team scoring each number of possible goals by the end of the game. Summing up all the probabilities of all the possible combinations of final scores gives the game’s win probability.
Here’s the graph:
There are a couple wrinkles to address. First, there are power plays. When a team as a man advantage on the ice, it’s much more likely to score. About one in five power plays results in a goal for the team with the advantage. Only about 2% of the time the short-handed team will score. So at the start of a power play, a rough approximation would put the win probability a little less than one fifth of the way toward the next best curve.
For example, if the score is 2-0 with 30 minutes remaining in the game, the win probability would normally be about 13% for the trailing team (the red line). But at the beginning of a power play, the trailing team’s win probability would jump about a fifth of the way up to the ‘down by 1’ line (blue). A rough approximation puts the new win probability at 16%. Then as the power play expires and there’s no score, the win probability would gradually return to the ‘down by 2’ line.
Second, there is the ‘end-game,’ when teams down by a goal will pull their goalie in favor of an additional skater. That would increase the win probability of the trailing team slightly, but only half as much as you might expect. They’d still only be buying an opportunity in overtime. But it could still be factored in. Before I do, I’d need some data on end-game goals.
One advantage of a theoretical approach over an empirical model is that team strength can be factored in far more easily. In an empirical model, when you divide up the data by various classes of team strength, the data is sliced into tiny fragments, usually with very small and unreliable sample sizes. Theoretical formula-based models don’t suffer from that problem. I can simply adjust the mean goals scored and goals allowed for any particular opponent, then rerun the model. The resulting model would be tailored to the specific match-up instead of a generic model for the league as a whole. Home ice advantage can be factored in with a similar approach.
Remember, WPD (Win Probability Dysfunction) can happen at any time, and it’s nothing to be ashamed of. Don't analyze win probability graphs if you take nitrates, often prescribed for chest pain, as this may cause a sudden, unsafe drop in blood pressure. Discuss your health with your doctor to ensure that you are healthy enough to view win probability graphs. If you experience chest pain, nausea, or any other discomforts during a sporting contest, seek immediate medical help. In the rare event of viewing win probability graphs more than 4 hours, seek immediate medical help to avoid long-term injury.
Live NHL win probability graphs now online.
