Drafting over-agers is something that is highly contested. Yes, scouts get an extra year to watch the players and get a better idea of their potential, but this is also a player who has had an extra year of development compared to his peers in that draft class. As a result, over-agers are typically avoided. The Over-Ager project was a project created based on a trend that I noticed from analyzing NHL drafts. After seeing so many successful Over-Age drafted players from the mid to late rounds of the NHL draft, I decided to produce an in-depth analysis on whether Over-Aged draftees actually had more success at the NHL level than 1st year Draft Eligible draftees.
Hypothesis
Once the top talent from 1st-year draft eligible draftees has passed (typical steep drop off after rounds 1-2), Over-Age draftees have greater success at having a significant NHL career than 1st-year draft-eligible draftees due to rapid maturation that occurs during the teenage years as well as increased viewings from NHL scouts.
Measures
In order to measure for a “significant NHL career” across all positions, the measure of a successful NHL career is based on reaching a statistically significant number of games played. Statistical significance refers to being 1 standard deviation above the mean (Explanation below). In other words, a significant number of NHL games played would be the top 15% of drafted players. This allows the model to measure the top performers of every draft against the whole population of draftees.
Sample
While it would be amazing to know if the most recent drafts have found similar trends to those throughout the 2000s and early 2010s, unfortunately, there is no way to know that yet. As a result, this model used data collected from the 2003-2013 NHL drafts. Having the 2013 draft as the latest draft year allowed players selected, regardless of 1st year or over-aged eligibility, to have at least 10 NHL seasons to reach the number of significant games played. In the end, the data collected a total of 2,500 players drafted between the 2003 and 2013 NHL Draft.
Method
All of the Draft data was collected from HockeyDB. Once the data was collected and placed into an Excel file, data was collected manually, placing each NHL player into the 1st year eligibility category, or into the Over-Ager category as well as their birth year. This was done for all 11 drafts, and then all players were placed into a master sheet in Excel, where the analysis began.
To determine the significant number of games played, the mean (x̄) number of games played for every drafted player between 2003-2013 from rounds 3-7 (excluding rounds 1-2, which heavily favours 1st year-eligible players and rounds 8 & 9 from 2003-2004 draft due to inconsistency across all following NHL drafts) was calculated where x̄ = 83. This was followed by calculating the standard deviation (SD) from every player drafted between 2003-2013 from rounds 3-7, where SD = 206. By adding these 2 values, you get the 1 standard deviation above the mean (+1 SD) from games played for every drafted player between 2003-2013 from rounds 3-7, where +1 SD = 289. This means that in order to be considered in this model, a player would have to have played a minimum of 289 NHL games.
x̄ = 83 GP
SD = 206 GP
+1 SD = 289 GP
Significant # of GP = 289
Data was then collected with the variables of playing >289GP and whether draftees were a 1st year-eligible or an over-ager.
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
1st Year Eligible: Refers to a player who has been drafted to an NHL team in their first year of eligibility.
Over-Ager: Refers to a player who has been drafted to an NHL team, but was drafted a year or more after they were eligible to be drafted.
Mean (x̄): The statistical formula that calculates the average of the sum of all the games played by each player, divided by the total number of players.
Standard Deviation (SD): The statistical formula that calculates the average distance of each player's total games played away from the average number of games played by every player.
One Standard Deviation Above the Mean (+1SD): The score that is a marker for the specific number of games that it takes to be one full standard deviation above the mean. This means that x̄ + SD = +1SD. This score indicates that players who have reached a number of games played ≥+1SD are statistically significant.
To get a better idea of what this looks like, here is a visual representation:
This is a normal distribution. It represents all of the NHL players who have been drafted. At the middle of this curve is the mean (x̄). This also tells us that half of the drafted players (50%) are on the left of this curve, and half the drafted players (50%) are on the right side of the curve. At the far left would be players drafted who never played in the NHL, or who played very few games. On the right side there would be players who played 15-year careers in the NHL. According to this curve, the majority of players will be within one standard deviation from the mean (Approximately 68.2%).
This means that to reach statistical significance (+1SD), drafted players would have to be above 50% of NHL players + another 34.1% of NHL players, which equals 84.1% of all drafted NHL players. This tells us that any player who has reached a significant number of games is in the top 15.9% of all NHL players in terms of games played.
Successful Draft Pick: In this analysis, a successful draft pick is determined based on whether the draftee reached the 289-game mark during their career. If the player had a career games total ≥ 289 GP, then this player was considered a successful NHL draft pick as they played a significant amount of games.