Sunday, 5 October 2014

Relative Zone Start Charts: Better Visualizing Coaches' Deployment

I've been thinking for a while about what we miss when looking at zone starts. On a micro basis, with just one team, we can look at a player usage chart and see a visualization of how coaches deploy players: typically there's a cluster of players in the middle, a few 'shutdown'/third line guys on the left with few offensive zone starts, and a couple of sheltered rookies or offensive specialists over on the right with a fairly high offensive zone start percentage. Here's a fairly typical example from last season in Dallas (min. 30 games played):
My favorite part about team usage charts is how they combine deployment and production. It's sort of the coaching intent and the outcome rolled into one graph. But when you compare two players on different teams with similar offensive zone start percentages, the human element gets lost. Thanks to hockey-reference's recently unveiled advanced stats, including team zone start percentages, for every team from 2007-14, I've been able to express those differences more clearly.

Last season, teams' offensive zone start percentage ranged from 42.1% (Toronto) to 55% (Chicago). The most sheltered skater for Toronto who played more than half the season was Nazem Kadri at 49.3% and their toughest deployments went to Jay McClement with 28.6%. In fact, Toronto was so bad last season that Rob Vollman's usage charts have even Kadri categorized as a "shut-down" player.  Ignoring Chicago for the moment because they give all the worst zone starts to just one line, LA is next at 53.6%. Their zone starts range from 51.8% (Willie Mitchell) to 59.3% (Andrew Campbell). Just to emphasize how absolutely absurd this is:
See where this is leading? Most-sheltered Nazem Kadri would have the toughest zone starts on a Kings squad. That's amazing. And when you consider that he's probably the kind of player whose production you would want to see in sheltered starts, it certainly lends perspective to his production.

My solution to this problem of cross-team visualization is to use a version of a statistic that used to appear on ExtraSkater (EDIT: I'm now told that war-on-ice has them as well) for relative zone starts compared to the team average:

Relative offensive zone start percentage = Individual player's offensive zone start percentage - Team average offensive zone start percentage

(Disclaimer: this isn't strictly a relative stat, at least not in its current incarnation. That would require recalculating to compare the average of all the zone starts when the player was not on the ice, rather than using a team average that includes his deployment, to his own offensive zone start percentage.)

Pretty simple. Because I wanted a visualization that included this variety of deployment more effectively than standard player usage charts, I made a league-wide chart that has relative offensive zone start percentage on the x-axis and relative Corsi on the y-axis. (The size of the bubble doesn't mean anything here; if you want something fancy, feel free to put it together yourself). Clicking on bubbles should bring up the player's name, or you can go directly to the Tableau page here and play around further. 

I think this accomplishes what I wanted. For production purposes, Rob Vollman's player usage charts will always be the gold standard. But if you wanted to compare players who are sheltered relative to their teams across the league to see how well they tend to produce compared to their teams, you can do that. For example, Jeremy Morin (topmost dot on the right) and Nail Yakupov (rightmost dot near the horizontal axis) have nearly the same zone start percentage, but Morin posted a better relative Corsi than Yakupov did. Improving this graph by adding QoC or QoT would add a much-needed dimension that I suspect would explain some of the discrepancy.

I also think it's interesting to think about this kind of visualization in the context of trades or free agent signings. Teams look for players to fill specific kinds of roles. It would be easy to miss a Nazem Kadri in the search for a center who produces decently in carefully curated offensive zone starts--just as easily as missing Willie Mitchell when seeking someone who will play tougher minutes. Zone starts by themselves simply aren't enough when looking for these players, because on a team as bad as Toronto was last year, there isn't an opportunity for Kadri to get the kind of deployment that would likely benefit his production. Despite griping by me and many bloggers about nonsensical deployment decisions, on the whole I do value where coaches choose to play their skaters. And obviously teams and GMs do even more so.

Aptly, Matt has a few resources (some already up and some arriving soon) to present and tweak these stats. On the Player Stats tab, you have the option to adjust for zone starts and score state. And Progressive Hockey will soon have both team zone start percentages and player relative zone start statistics--the latter calculated via better methodology than mine.

Megan blogs intermittently about whichever hockey stats catch her fancy at She can be reached on twitter at @butyoucarlotta, or via email at shinnystats at gmail.

Wednesday, 1 October 2014

Guess What? The Pre-Season Doesn't Matter

I looked at NHL team's goal differential in the pre-season and how they went on to do, by goal differential in the regular season. I found very little evidence of correlation between the two.

Last seasons edition of the New York Rangers had a calamitous 29% goal differential before going on to the Stanley Cup Final, while the Sabres had a 56% differential going into their not-so-great campaign. 

You probably already knew that you shouldn't take much away from your team's performance in the pre-season, but now you have the evidence!

For those who are interested, here's some more statistical information on the model: