Hello again, it’s been a while. I’ve been calling this blog a “sports analytics blog” when talking about it. However, you may have noticed that it’s been a “football analytics blog” so far. I’ve been trying to do an analysis of another sport so that I can stop feeling disingenuous when I call it a “sports analytics blog”. The perfect candidate is my other love – hockey. And this is how this blog was born.
A lot of Rangers fans are concerned about the fact that the Rangers are picking up a lot of points right now and that they won’t be able to finish top 5. The theory goes that in order to win you need elite players and in order to get elite players you need to have a top 5 pick. So that had me wondering, is a top 5 pick really that much better than the other picks? This led to this latest analysis where I compare top 5 picks with 6-10, and all first round picks that aren’t top 5. I also compared the 6-10 picks with all first round picks that weren’t top 10 to see their value. I used a Chi-Squared test to do the analysis, more on this later.
The criteria I used was players that were on the “All-Star Team”. This designation is not the same as being an all-star and playing in the all-star game. If my understanding is correct it seems to be analogous with an All-Pro in the NFL. The players that made the “All-Star Team” are more likely to be the elite type of players that fans are hoping to tank their season for. The other criteria were Hall of Fame players.
The methodology was to compare how many of these AST and/or HOF players were found at specific draft positions compared to what’s expected if the results were proportionate. I then used the Chi-squared test to see if the results were significant.
Below is a comparison of picks 1-5 to 6-10 from 1990 through 2015. I used 2015 to give the draft picks times to grow and mature their game.
I compared the AST/HOF players drafted in the top 5 vs. 6-10 from the aforementioned time frame to what would be expected if these players were drafted proportionately. The expected values are calculated one of two ways. For example to get 18.5 top 5 players that made the All-Star Team and/or HOF you can take total top 5 players (130), divide it by all players (260), multiply it by all AST/HOF players (37) divided by all players (260), and multiply it by all players (260). Then do the same for every intersection in the crosstabs. (It would look like (130/260)*(37/260)*260). Or you can simplify and just perform the following calculation: (130*37)/260.
Here we see that the actual vs. expected differs significantly with an extremely small p-value that isn’t even close to the 0.05 threshold. This means that the top 5 picks overperform on this metric significantly compared to players chosen 6-10. The probability of having this difference be random is far less than 5% and is very close to 0.
Next, I compared the top 5 players with players chosen in the first round but not top 5.
Once again, the players chosen in the top 5 overperform significantly with a tiny p-value.
We saw that picks 6-10 were indeed significantly less likely to produce elite talent than the top 5, but are they at least more likely to produce this type of talent than first round picks that are not in the top 10?
The answer is no. It’s almost shocking how close the actual is to the expected +/- 0.2 off across the board. The p-value is very high at ~0.90.
It must be noted however, I was just looking at only elite players. Picks 6-10 may still be more likely to produce higher-end players that aren’t elite and/or consistent NHL players. However, based on this analysis if you want your team to draft elite players having top 5 picks is indeed the way to go and picks 6-10 don’t offer an advantage in drafting such players vs. not top 10 first round picks.
Sources:
2015 NHL Entry Draft Selections
(Note: These selections are for 2015, I looked all the way back to 1990)
Igor Zolotusky's Analysis 