Percentage of Team Assists

The Top “Young Guns” in NHL History

Benjamin Wendorf NHL League-Wide Analysis Tags: , , , , , , , , , , , 1 Comment

File:Orr Trip.jpg

Photo by “Djcz” via Wikimedia Commons

I don’t think we engage the idea of the place in history that many of today’s best players hold, and I partly attribute that to the difficulty of finding points of comparison across generations. Simply using raw scoring data doesn’t do the best job because a.) everyone knows Gretzky wins, and b.) we know that scoring fluctuated drastically in the 1980s, and it wasn’t because all the best shooters and passers were playing then. With that in mind, I’ve stewed over ways to bring these different generations together, in such a way that we can be comfortable comparing them. It’s led me to build a couple of metrics that move a little bit away from the counting statistics (G, A, PTS) and towards some metrics that demonstrate a player’s share of their team’s results.

The two metrics I’m focusing on for these young guns both relate to offensive measures, but I think that generally they also allude to a player’s importance to play overall. I tend to agree with Vic Ferrari’s assertion (see his third comment here) that forwards and only a select number of defensemen play much of a role in driving offense, and recalling some of the player types implicated in Steve Burtch’s work over at Pension Plan Puppets on Shut-Down Index, I’d propose that players that drive possession (forwards and defense) more generally will return some signals in regards to shooting or playmaking. Whether that simply means, in the future, we’ll get more from simply looking at passes and shots (or robots will do the whole darn thing and save me the trouble), I can’t say. For now, though, I created %TSh, or percentage of team shots, which expresses the proportion of team shooting a player does (in games they played), and %TA, which does the same exercise with team assists. While the issue of whether this expresses positive possession players is ripe for debate, it’s indisputable that players strong in these metrics will be drivers of offense for their teams.

In that spirit, I wanted to delve into some nifty historical data; I’ve been able to go all the way back to 1967-68 with data on %TSh and %TA, and it returns some fascinating studies on NHL legends vis-à-vis today’s stars. For this piece, I’m focusing on the players that get everyone excited, so-called “young guns,” or players under 25 that have already demonstrated their ability at the top level. How do contemporary young guns measure up all-time?

Continue reading →

Friday Quick Graphs: Shooting and Playmaking Contributions, 1967-68 through 2012-13

Benjamin Wendorf Friday Quick Graphs, NHL Topical Analysis Tags: , , , , , , , Leave a comment

I’ve just finished a pretty massive dataset, so I’m geeking out a bit over what I can do with it. Just the beginning, above…this is the distribution of %TSh (player shots divided by estimated team shots in games they played) and %TA (same equation, but with assists) season performances, 20+ GP, from 1967-68 through 2012-13. Per recent arguments about Ovechkin, I’ve added lines showing where his best season (2008-09) and most recent full season (2012-13) fall on the list; his current season would fall approximately in the same place as last season.

Those of you who’ve been following me on Twitter know that I’ve put together a pretty substantial dataset, and I’ve been working through the data with a metric I’ve used for a while. %TSh is a player’s shots divided by his team’s estimated shot total in games they played (Team Shots / Team GP, multiplied by player GP). The measure gives us an idea of the player’s shooting contribution to the team’s offense. It moves outside the pesky variance of shooting percentage and gets closer to a stable indicator of offensive role. I’ve done the same with %TA, which is the same equation for assists. The reason for estimated team totals is we don’t yet have good macro-data on specific games that players played before 1987-88, but the metric runs essentially in lock-step with the real thing and I want to provide a useful, historical point of comparison. Doing this allows us to look 20 years further back.

The distribution above includes over 23,000 player seasons over 20 GP; the orange distribution is %TA, and black is %TSh. I used the marks to connect back to the previous week’s bizarre flame war over Ovechkin’s value and approach to the game; the top one shows Ovechkin’s peak year, 2008-09 (20%), which also happens to be the highest %TSh of all-time. The bottom mark is Ovechkin’s 2012-13 (16.3%), which I’m using because his current season is just slightly higher – it would be good for 16th best in NHL history.

I also did a second graph, wanting to look at the relationship of %TSh to %TA, to see just how much they ran together:

Related to the previous post, I decided to see if the relationship between TSh% and %TA was too close to tell me anything. %TSh is on the x-axis, and %TA is on the y. As you can see, they do run together, which is okay, because rebounds can result in assists for the shooter, and players with a lot of shots will generally be engaged in the offense in all ways. That being said, it’s not so close that they aren’t distinctive. The plot above does look scattered enough for these two metrics to tell us something apart from one another.

In the graph above, the x-axis is %TSh, and the y-axis %TA. Intuitively, these run together a fair amount, as shots create rebounds that can be counted as assists, and a player that shoots a lot is likely to be more heavily involved in the entire offense. That said, they don’t run nearly so close together as to render either measure moot. I think %TA can be a valuable counter-weight for assessing defensemen. Anyway, this is the tip of an enormous iceberg of data, so don’t be surprised to see me refer to and use %TSh and %TA again.