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Understanding the NHL Draft JUST a little better

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Presentation on theme: "Understanding the NHL Draft JUST a little better"— Presentation transcript:

1 Understanding the NHL Draft JUST a little better
By Corey Pronman

2 Coverage Three topics: Late birthdate effect
Drafting skill and role of chance Scouts vs. Stats

3 Topic 1: Late Birthdate Effect
Hockey has a unique rule regarding draft eligibility--- Players born after September 15th are pushed back a year. Some recent big-name examples of players’ draft year pushed back: Leon Draisaitl Jack Eichel Taylor Hall Seth Jones Auston Matthews Nolan Patrick Sam Reinhart Matthew Tkachuk

4 Late Birthdate Effect Hypothesis: The late birthdate rule is impact player evaluations. Set-up: Draft data from , first year eligible, up to pick 210 All leagues All skater positions Split data into late birthdate players (“LBD”) and non late birthdate players (“NLDB) Omit pick slots where both groups aren’t represented Compare production by draft slot for both groups

5 Late Birthdate Effect

6 Late Birthdate Effect Breakdown by month Set-up
Every CHL forward picked from First year eligible Had a CHL points/gm between and > 20 GP

7 Late Birthdate Effect

8 Guess These Players: All Current CHL Forwards
Points/GP Prim Pts/GP Birth Date Mystery Player A “Draft-1” 1.42 1.10 Late Sept Mystery Player A Draft Yr 1.39 0.91 Mystery Player B Draft Yr 1.6 1.32 June Mystery Player C Draft Yr 1.48 1.17 August

9 Guess These Players: Answers
Points/GP Prim Pts/GP Birth Date Nolan Patrick “Draft-1” 1.42 1.10 Late Sept Nolan Patrick Draft Yr 1.39 0.91 Pierre-Luc Dubois Draft Yr 1.6 1.32 June Nick Suzuki Draft Yr 1.48 1.17 August

10 Late Birthdate Effect Takeaways
Always look at the month a player was born Draft -1, Draft +1 can be misleading terminology Late birthdate effect is not determinative, but it is important Simple adjustment, major implications

11 Topic 2: Drafting Skill & Role of Luck
Drafting is very important to NHL teams, most contenders have a high % of roster acquired through the draft Source of major investment by NHL teams, clubs spend up $2-3 MM per year on scouting Given importance and investment, two important questions How much consistency is this year to year in draft results? How much does luck affect draft results?

12 Drafting Skill & Role of Luck
Question 1: How much consistency is this year to year in draft results? Set-up: Assign each draft slot from an expected value point, based on games played Assign each draft pick from a surplus/deficit value based on actual games played minus expected games played Example: Scott Gomez was top 10 from the 1998 class in games played, picked 27th overall, but played twice as many games as expected as someone picked 27th. Credit: Neil Paine at 538.

13 Drafting Skill & Role of Luck: Minnesota/Dallas Franchise

14 Drafting Skill & Role of Luck: Detroit

15 Drafting Skill & Role of Luck

16 Drafting Skill & Role of Luck
Question 2: How much does luck affect draft results? Why is this important given answer to prior question? Skill can still be shown over a long period of time. Set-up: Use previous data and calculated values Calculate difference from sum of value of all picks for each team’s actual outcome subtracted from expected outcome Calculate standard deviation for each team’s outcome (every team has different picks) Finally, take difference and divide by standard deviation to get an index of improved outcome over expected, herein called Draft Score Credit: Andrew Thomas, now with Minnesota Wild

17 Drafting Skill & Role of Luck

18 Drafting Skill & Role of Luck
We expect a certain amount of variance in Draft Score due to chance If drafting was 100% luck, the variance of all the normalized Draft Scores would be 1, however here it is about 1.33. This suggests that 25% of draft results are due to skill when adjusted for standings, 75% are due to randomness.

19 Drafting Skill & Role of Luck
Takeaways: The effect of luck at the NHL Draft is fairly large Teams show talent over a long period of time, but over a short period of time skill isn’t identifiable Overreacting to individual picks or drafts is likely bad analysis

20 Topic 3: Scouts vs. Stats Common debate about which form of evaluation is superior Hard to completely separate, because scouts are biased by statistical performance. Set-up: Compare scout and stats rankings of first year eligible drafted CHL forwards from Basic definitions of ‘scout’ and ‘stats’ Scouts: Slot in NHL Draft where player is picked Stats: Most CHL points (Very simplistic approach) See relationship between the two rankings and NHL production Example: Brandon Dubinsky was the 12th CHL forward (60th overall) picked in 2004, but his 78 points was 2nd highest among eligible players. (He’s now #2 in NHL scoring among eligible players, 9th overall).

21 Table of correlation coefficients of Scout/Stat rank vs. NHL points
Scouts vs. Stats Table of correlation coefficients of Scout/Stat rank vs. NHL points Group Scout Rank Stat Rank All forwards 0.54 0.49 Forwards with 300+ NHL points 0.31 0.36 Forwards with 1+ NHL point 0.40 0.48 Forwards with no NHL points 0.32 0.29

22 Table of correlation coefficients of Scout/Stat rank vs. NHL points
Scouts vs. Stats Table of correlation coefficients of Scout/Stat rank vs. NHL points Group Scout Rank Stat Rank Average of Scouts/Stats All forwards 0.54 0.49 .58 Forwards with 300+ NHL points 0.31 0.36 .38 Forwards with 1+ NHL point 0.40 0.48 .50 Forwards with no NHL points 0.32 0.29 .35

23 Scouts vs. Stats Takeaways:
Correlation between ‘stat’ rank and actual NHL draft order/’scout’ rank was 0.49 yet, it achieved nearly identical results. Scouts and stats are identifying different players while achieving nearly identical results. A case for synergy of the scouting and statistical analysts. A simply average of opinions could produce significantly better results.

24 Summary Look carefully at a player’s birth month, be extra skeptical of players born after September 15th. NHL teams are not consistent in their year over year drafting. Luck is a very large part of NHL Draft results, but there is long-term skill. Scouts and statisticians perform comparably working alone, and can improve each other’s results with cooperation.

25 Questions?


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