College hockey has players ranging from 17 years old all the way to the mid-20s, but how fans value and perceive their production is very similar, and it shouldn't be that way. How do these players produce on the same playing field, and how different are the players' point totals at different stages
One of the biggest challenges when evaluating NCAA hockey players is age. Unlike junior hockey, where most players are in a similar stage of development, NCAA rosters can feature freshmen ranging from 17 to 21 years old. That is due to the fact that a lot of programs like recruiting older players who have played a lot of junior hockey and have developed not only their skill, but their size and physicality.
But when you look at point totals, it can be very misleading when you look at production between a teenager and someone who’s body and overall game has had a lot of time to develop.
This case study will go over the top ten in total point scorers in the 2025-26 season, and how the stats would look if they were on the same playing field.
For this exercise, I created a simple age-adjustment model that assigns a multiplier based on a player's age. The younger the player, the larger the multiplier, reflecting the increased difficulty of producing against older competition. This isn't a finished statistical model, but a way to show how age can change the way we interpret player production.
Ethan Wyttenbach (1.48)
Gavin McKenna (1.46)
TJ Hughes (1.43)
Porter Martone (1.43)
James Hagens (1.38)
Hayden Stavroff (1.37)
Michael Hage (1.33)
Max Plante (1.30)
Zam Plante (1.25)
Felix Trudeau (1.23)
These are the raw points-per-game of the top ten in points last season, and you can see there are multiple teenagers, headlined by Gavin McKenna, who was both 17 and 18 during the season. On the other end of the coin, there’s T.J. Hughes, who was 24 for the season. So how do these numbers look with the new model?
Gavin McKenna (1.94)
Ethan Wyttenbach (1.85)
Porter Martone (1.67)
James Hagens (1.61)
Michael Hage (1.56)
Max Plante (1.52)
Hayden Stavroff (1.45)
T.J. Hughes (1.39)
Zam Plante (1.33)
Felix Trudeau (1.23)
Mckenna’s stands out as he made a 0.48 jump which is insanely significant. You’ll notice that the older players don’t drop by very much, but they also didn’t have elite point totals to begin with.
This shows how these younger players are still producing at an unreal level even if they don’t lead the NCAA in points.
In the 2023-24 season Macklin Celebrini as a 17 year old won the Hobey Baker where he was third in points and had a 1.68 points-per-game. Using this model his production jumps to 2.27, read that again, he was that good.
If you were to go outside of the top point producers last season, Adam Valentini at the University of Michigan had a 0.68 points-per-game as a 17 year old, but if you adjust it he had a 0.92, which seems way more impressive.
Age-adjusted production is not meant to replace traditional statistics, and this model is only a first step. The multipliers used here can be improved by using historical NCAA scoring data to create a more exact aging curve.
But even in its current form, the exercise highlights an important point, context matters.
A 17-year-old producing at a high level against players who are five, six, or even seven years older is doing something extraordinary. Raw point totals can tell us who scored the most, but age-adjusted production helps tell us who may have achieved the most relative to where they are in their development.
NHL teams have understood this concept for years. Scouts are not just evaluating who the best college player is today, they’re trying to determine who will be the best player five years from now.
That is why a player like Gavin McKenna producing at 17, or Macklin Celebrini dominating college hockey before turning 18, stands out so much. Their production is not simply impressive because of the numbers themselves; it is impressive because of the age at which those numbers were achieved.
