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At young ages, a few extra months of development can make a big difference in size, strength, and athletic ability. A child who turns 5 years old in January will be nearly 20% older by the time a child born in December has their 5th birthday. In many sports, including hockey, children born in the early months of the calendar year get noticed by their coaches because of the superiority they demonstrate due to their age advantage. As a result, boys born early in the year are more likely to reach the professional ranks of the National Hockey League (NHL). The phenomenon just described has been labeled the relative age effect (RAE). Previous work studying the RAE in the NHL has focused on individual NHL seasons, often encompassing many of the same players across multiple seasons. We investigate the RAE using complete data on every player who has ever played in the NHL. We focus the majority of our analysis on Canadian born players and examine the RAE across hockey position and hall-of-fame status. For the first time, we provide strong evidence of when the RAE began to manifest itself in Canada. Our change point analysis indicates that the RAE began for players born since 1951. Finally, we make a case for what initiated this change in the way young hockey players develop, particularly in Canada, which produced over 90% of NHL players at that time. [ABSTRACT FROM AUTHOR]

On March 30, 2008, Samuel Arbesman and Steven Strogatz had their article "A Journey to Baseball's Alternate Universe" published in The New York Times. They simulated baseball's entire history 10,000 times to ask how likely it was for anyone in baseball history to achieve a streak that is at least as long as Joe DiMaggio's hitting streak of 56 in 1941. Arbesman and Strogatz treated a player's at bats per game as a constant across all games in a season, which greatly overestimates the probability of long streaks. The simulations in this paper treated at-bats in a game as a random variable. For each player in each season, the number of at-bats for each simulated game was bootstrapped. The number of hits for player i in season j in game k is a binomial random variable with the number of trials being equal to the number of at bats the player gets in game k and the probability of success being equal to that player's batting average for that season. The result of using non-constant at-bats in the simulation was a decrease in the percentage of the baseball histories to see a hitting streak of at least 56 games from 42% (Arbesman and Strogatz) to approximately 2.5%. [ABSTRACT FROM AUTHOR]