How Should We Forecheck? Let us Count the Ways

Ryan Stimson

Ryan has written extensively on hockey analytics since 2013. He has pioneered work in player evaluation and game strategy, leading the popular Passing Project for several seasons. Ryan has contributed on analytics and published new research at Hockey Graphs, but also has written on using data to better evaluate hockey tactics. He consulted for RIT Men’s Hockey Team from 2015 - 2018 and coached a 14U team as well. Ryan is a Certified Level III USA Hockey Coach. He has published a book you can buy on Amazon, Tape to Space: Redefining Modern Hockey Tactics, that draws on insights gained from data analysis to optimize how teams should play hockey.

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With more detailed data in hockey analytics, there are often more answers to existing questions like “How often does this team exit their zone with possession?” This has been good and we have learned more about each phase of the game and how to weight them appropriately. However, as we learn more about the game and how to measure it, we also come up with new and more detailed questions. Just as numbers like shot share or expected goal differential obscure all the different ways teams can arrive at those numbers, so too can the event level metrics.

Last summer, I wrote about forechecking using zone exit data. The idea was that, lacking detailed data in this phase, we could analyze this by proxy by looking at the opposition controlled zone exit percentage of each team. Put another way, how well does team allow the other to break out of their zone? What you find is that, as a general rule, forechecking matters, but there are different ways to go about being successful at it. To illustrate this point, I’m going to dive into the forechecks on display for both the San Jose Sharks and Vegas Golden Knight, one of which will have won a Game 7 by the time you read this. But first, a chart!

All data here is from 5v5 situations and tracked by Corey Sznajder. There’s an average of about 41 games collected on each team over the last two seasons, or almost 2000 minutes of play.

The x-axis is each team’s opponent’s controlled zone exit percentage. The higher this number, or more to the right, the worse each team’s forecheck. For instance, Washington allowed their opponents to break out of their zone with possession nearly 44% of the time. Arizona was the best in the league at 34%. My research last summer found that a one percentage difference results in about an extra goal every 10 – 20 games, depending on scoring talent. So, if a team like the Capitals moved from the worst to average, say around 39%, that 5% increase would result in about 2.5 extra goals over ten games. This is incremental improvement, but finding gains in the margins is why we use data analysis.

The y-axis shows the pressure rate. Pressure rate is the percentage of opposition zone exits that the forechecking team applied pressure. What is pressure? Corey defined it as any skater within a stride length of the player attempting the zone exit. This is a good proxy for how much direct puck pressure is being applied. However, as you can, just because a team applies a lot of pressure does not necessarily mean they were the best forechecking team.

To bring this back to San Jose and Vegas, both of them forced similar opposition controlled zone exit percentages and are comfortably in the top 10 – 12 teams in the league, but did it in wildly different ways. In a battle of forechecking heavyweights, each go about it their own way. Let’s take a look.



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