Recently I saw The Projection Project’s post on their draft projection data , and I wanted to see the differences between their projection and the Central Scouting Service’s. There’s also some additional information about the TPP model that sheds some light on the logic behind draft projections.
There’s a more in depth explainer on the TPP site , but in short, this model uses data on past prospects to compile cohorts of players which are grouped using height and NHLE points (a model that translates points from junior/college/european leagues into NHL points).
The first dashboard shows how the TPP and the Central Scouting models agree on which prospects should be highly rated, but then they diverge after the fairly obvious characters. What’s interesting is that the two models rank centers fairly similar, while they diverge significantly on wingers and defensemen.
The second chart focuses on which prospects are favored by which model.
The function here is simply (TPP Model Rank # – CSS Model Rank). Players with negative numbers (like Mitchell Stephens) are more favored by the TPP model, while players with positive numbers (Kevin Stenlund) are favored by the CSS model.
This chart just shows the height and weight of each player on a scatter plot. I don’t think it tells us anything particularly, but it’s fun to look at.
This chart shows the average height and weight for each position. The height doesn’t vary across the positions, but we can see that defensemen are clearly the heaviest position. There’s probably some prior selection bias happening here, going back to which player was bigger in a youth league.
This may be counter intuitive, since usually the larger sample size is better. However, players like McDavid and Eichel are rare (generational?) talents, so there are very few comparable players in their cohorts. The players with large cohorts are likely to be run-of-the-mill talents with nothing to separate them from their peers.
We see the same phenomenon with PCS. The more elite a player is, the fewer comparables there are to that player https://t.co/HjSM5qwGES
— Money Puck (@MoneyPuck_) June 25, 2015
MoneyPuck, who’s PCS draft model I hope to address soon, sees the same phenomenon in that model.
The last chart shows what types of past prospects a player’s cohort is composed of.
You can see that the players with the largest probability of turning into an NHL player are on the bottom right of the chart (the size of the bubble is the indicator there). That is because their cohorts are made up of more players that turned into NHL players.
I had some fun looking through the TPP data, and I hope you learned something about how projecting NHL talent can be done. Thanks for reading.