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Gravy Train: IPP and the 2014 Draft Class
- Updated: June 8, 2014
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Email: romulus @ theoilersrig.com (no spaces)
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[NOTE: I’ve written an update on this project here related to empty net goals]
In this post, I’m going to combine two tools (one very new and exciting) to try and gain an edge on understanding the 2014 NHL draft class.
The scouting folks over at McKeen’s have put together a very interesting tool: a searchable CHL stats page, which includes all kinds of easily accessible data like even strength scoring, on-ice goals for and against, etc. You can find it here.*
*NB: parts of the site remain buggy. For example, you can’t (as yet) toggle between seasons for individual teams. If you find a bug, please report it to the good folks who operate the site: @KatsHockey and @Super_Steef
The other tool is IPP, or Individual Points Percentage.
IPP is simply the percentage of points earned by a player on goals scored for while a player is on the ice. So, let’s say a player is on the ice for 10 goals for and he accrues 5 points on those ten goals. In that case, his IPP is 50%.
In general, IPP indicates (over a large enough sample) the strength of a player’s even strength contribution to scoring goals while he is on the ice. Elite players, then, tend to have a very high IPP. Over the past four years, for example, Taylor Hall leads the league in IPP with 85% (>2500 5×5 minutes) with Crosby right behind him at 82.8%. Here’s a graph, ranked by IPP, of the past four years:
(Click images to embiggen)
Now, IPP is a record of what happened on the ice. We can rank players based on their IPP. But, we can’t come to any definitive ranking concerning these players. For example, we can’t say Taylor Hall is the best player in the NHL because he has the highest IPP over the past four years. That’s not the purpose of IPP, or what it indicates. IPP does not, for example, take note of who scores the most, against the hardest competition, etc.
For players with a high IPP, over a large enough sample, what it does indicate is… that those players enjoy a high rate of contribution to scoring goals when they are on the ice. Typically, this indicates that a player is driving his team’s scoring while he is on the ice.
For the curious, wishing to read up more on IPP, I suggest these articles: an early piece by Tyler Dellow, a trio of articles by Scott Reynolds (here, here and here). And, Oilers’ fans may remember that IPP came up in relation to Taylor Hall’s weird disjunction this season between his boxcars and his underlying numbers (Hall had an absurd IPP of over 100% due to gaining points while on the bench – i.e., he made a play that contributed to a goal for but had, in the interim, left the ice). To review that situation, go here and here.
For those wishing to simply play around with NHL IPP stats, head over here.
The 2014 Draft Class
Using the tool McKeen’s has made available to us, we can have a look at the IPP of the top ranked CHL forwards from the 2014 draft class.
We get the IPP of a player by simply dividing his even strength points by the even strength goals for scored while he was on the ice. (Feel free to poke around and find the IPP of any player of interest using this method.)
For the purposes of this list, I’ve looked at every CHL forward listed on Bob McKenzie’s Mid-Season Draft Rankings.
(Unfortunately, his “Lottery Edition” only included 8 eligible forwards, so I’m using the larger sample with the understanding some of these forwards may no longer be as highly touted and others worthy of inclusion will be excluded).
Here’s a graph with all 24 eligible players. I’ve sorted the players by IPP, but I’ve included ES points and On-Ice ES Goals For for reference.
(NB: in cases of a tie, I’ve ranked the higher ES scorer ahead)
Again, let me caution that this graph does not tell us who the best player is. What it does do is give us a record of which players contributed to a high percentage of their teams’ even strength goals when they were on the ice.
This record can be analyzed as an indication of which players drive their team’s scoring. That is, a player with a high IPP is arguably a driver of his teams’ scoring while on the ice and a player with a low IPP’s team is arguably benefiting from the play of others (note: benefiting from the scoring of others here does not mean that this player is reliant on others. It simply means that his team is not overwhelmingly reliant on him for scoring goals at even strength while he is on the ice. Or, simply, his team has other options even while he is on the ice).
There are a number of things this graph suggests that are worth noting.
1. While we already knew this to be the case, it is even more stark now that Draisaitl’s Prince Albert Raiders heavily relied upon him for scoring. If we compare his IPP to his linemates, for example, we can see how stark the picture is.
(NB: Valcourt only played half the season with the Raiders)
2. In Draisaitl’s case (an IPP of 91%), we should probably expect a regression. In the NHL, elite scorers tend to have an IPP in the high 70s and low 80s.
3. A regression in IPP (say in Draisaitl’s case) doesn’t necessarily mean a drop in even strength scoring. In fact, it could mean a bump. The assumption here is that as a team improves the players around a player with a high IPP, his IPP will fall as the burden of scoring is more evenly distributed. However, his point totals will either remain at the same level or increase as his team scores more goals with him on the ice.
4. All five players with an IPP of 80% or above could be considered vital team catalysts for even strength scoring while on the ice.
5. Players in the mid-to-high 70s could be considered essential contributors to even strength scoring, who happen to play alongside equally strong even strength scorers. For example, let’s look at Bennett’s linemates:
This gives you a clear sense of what a relatively evenly balanced even strength scoring line looks like from an IPP perspective (note: again, this does not mean these three players ought to be ranked as roughly equivalent to one another in terms of who the best hockey player is).
6. Those toward the bottom of the graph could be considered lesser contributors to their team’s even strength scoring while they are on the ice. This does not mean they are poor even strength scorers. De Leo, for example, despite an IPP of 60%, scored an impressive 55 even strength points. What it does tell us, however, is that De Leo’s Winterhawks scored a lot of goals while he was on the ice and he only figured in on a modest number of them. That is, the Winterhawks are an exceptional team and De Leo was, to some non-trivial degree, out-paced by his linemates.
To reiterate, IPP does not tell us who the best player is. Though valuable, this information has to be used properly and appropriately contextualized.
It does, however, give us a record as to which players are driving even strength scoring for their team while they are on the ice. This record can be used to indicate who might be more of a driver of team scoring and who might be more of a passenger on the gravy train.
It is another tool we can use to evaluate draft eligible prospects as we try to isolate individual player success from team success and get a read on the true talent of each player.