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Learn about the impact of late birthdates on player evaluations, the role of luck in drafting, and the debate between scouts and statistical rankings in the NHL Draft.
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Understanding the NHL Draft JUST a little better By Corey Pronman
Coverage Three topics: • Late birthdate effect • Drafting skill and role of chance • Scouts vs. Stats
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
Late Birthdate Effect • Hypothesis: The late birthdate rule is impact player evaluations. • Set-up: • Draft data from 1990-2010, 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
Late Birthdate Effect • Breakdown by month • Set-up • Every CHL forward picked from 1990-2010 • First year eligible • Had a CHL points/gm between 1.0-1.5 and > 20 GP
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
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?
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 1-210 an expected value point, based on games played • Assign each draft pick from 1990-2010 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.
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
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.
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
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 1990-2010. • 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).
Scouts vs. Stats 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
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.
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.