The 2015 OHL Final Part Three: Erie Otters and Oshawa Generals Passing Data

The last two pieces of mine focused on passing network analysis for both the Erie Otters and Oshawa Generals¬†from their 2015 OHL Final. The point of this short series was to look at how and why teams are successful over a playoff series. Generally, five-game samples aren’t large enough to give much credence to, and yet a sound game plan and tactical preparation can influence an¬†upcoming playoff series. With the type of data collected and analyzed through passing networks, it provides a baseline of how influential the Otters and Generals players were in their series. From there, naturally, any good analyst will go to the video to find evidence of how these numbers occurred, to augment their conclusions. These first two series served as a opportunity to present new ways of analysis with our data this season, something that, come playoff time, will be given a test run in terms of series predictions.

This final piece in this series will focus on the production for each player and team in a more traditional sense. What does that mean? Lots of numbers and charts. For starters, Erie generated far more passing offense in this series than Oshawa. At 5v5, here were the Otters possession numbers for shot sequences from single, multiple, and scoring chance passes.

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The 2015 OHL Final Part One: Erie Otters Passing Network

At the Rochester Hockey Analytics Conference, Stephen Burtch presented on Network Analysis using our passing data from last season. You can access Stephen’s slides here. It was an intriguing presentation on how we can use the passing data to better understand the on-ice environment of players and teams. If you’re at all familiar with my work, you won’t be surprised to hear me say that what happens prior to a shot being attempted is something that escapes us and is more important than just the final act of shooting. Only in better understanding how things happen, or don’t happen, prior to that, will we be in a better place to properly evaluate players. When Stephen presented at #RITHAC, I was sitting there thinking, “Boy, this would be great to do with the 2015 OHL Final Passing Data” I’d tracked, but hadn’t gotten around to sharing the results.

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