Adjusting the NCAA: Using Historical Scoring Data to Find Out If Lane Hutson, Matthew Wood, and More are Legit
In Part 1 of my 'Adjusting the NCAA' series, we answer, "Where do the 'historic' performances we just saw from the NCAA's U21 bracket actually sit in history?" by pulling historical scoring data.
Lane Hutson has turned college hockey onto its head, becoming the first defenseman to ever lead Hockey East in scoring.
Thing is, Lane’s a freshman. And he’s not the only young player doing incredible things. Adam Fantilli, Matthew Wood, Logan Cooley, and Collin Graf have set the league on fire this year, completely blurring the analytical weight behind point totals.
Wood, in particular, is an incredibly fascinating case. Despite underwhelming play, he’s continued to rack up the scoring, leading a lot of public sector scouts to give him the benefit of the doubt because “he always finds a way to put the puck in the net”.
But is his scoring really that notable? Is it that impressive? In fact, how impressive are any of the dominate performances we’ve seen this year? I can’t get these questions out of my head, so I pulled all U21 NCAA scoring from the last decade (since the 2012-13 season) and decided to find a way to answer them. Let’s dive into how I did this and some notable information from what I found.
Adjusting NCAA Scoring: A Series of Prospect Deep-Dives
Pulling the Data
Gathering stats from the NCAA is a bit trickier than any other league. For some reason, there’s no website that let’s you easily sort by age and see class – and no site seems to have every stat that I need. So to get the full range of information for this article, I had to pull off a few different tricks.
First step was pulling all U21 scoring from EliteProspects. Since we’re looking at point-per-game scoring, I only pulled players who played in 10-or-more games. This data was cleaned and separated by season in a spreadsheet that’ll become publicly available in a later article. After everything was organized, I included an additional sheet that compiled all 10 seasons together, giving us a full view of our sample (n=3,931 for those curious).
Awesome, we got everything we need. Except, since EliteProspects can’t track what class players are in (they should add a column to their tables for years of experience in a league!), I needed to find a way to add that in. And unfortunately, even finding clean data featuring players and their class in the same table is difficult. So for the sake of my sanity, I decided to instead use some nifty Excel work to decipher a player’s class in each season, by counting how many previous seasons they appeared in. This ended up working – it seems – perfectly well but it’s worth mentioning because there may be a few errors, particularly if a player had an awkward college path or such.
After bearing through the night-long journey of getting class data cleaned up, I was finally ready to pull this all together. Which means we’re at the fun part: math. First, I wanted to average out point-per-game scoring, to give us a sense of how it varied over the decade. If it was too consistent, our point would be a bit defeated. Luckily, it swayed a decent amount:
This is great! And lines up with what I had assumed the chart would look like. But just using the average point-per-game of our whole sample would undermine the amazing seasons that Adam Fox and Cale Makar gifted us during their collegiate careers. To get a more telling variable, we’d have to break up this average by position. That looks something like this
And to round it out, here’s a view of the number totals that we came up with:
Awesome. With all of this sectioned out, we can get to our main variable. And luckily, it’s relatively easy to get to. Our goal is to find just how impressive Lane Hutson, Adam Fantilli, and other company’s scoring actually is relative to the last decade, so all we need to do is compare a player to his year’s average, to see where each performance lays on its respective season’s theoretical bell curve.
That means that all we need to do is divide a player’s P/GP value by the correct average value, based on season and position.
And with that, we’ve landed at our era-adjusted variable, all ready for analysis!
What We Found
Finally, the exciting part. Based on the new variable we’ve created, the Top 40 U21 NCAA scoring performances of the last decade are…
Ha! This graphic gets me excited. Going down the list, it all seems to check out. Adam Fox’s ability to destroy the NCAA during what we previously determined as the lowest-scoring season for defensemen is incredible. He not only wins the #1 spot, he’s a significant margin ahead of anyone else. The gap between Fox’s #1 and Gaudreau’s #2 (0.657) is nearly the same as the gap between Gaudreau’s #2 and the rest of the Top 10. That’s nuts. And speaking of Gaudreau, it’s absolutely no surprise to see the NCAA legend topping this list either. And for the same reason that Fox’s season makes sense, it’s no shock to see that year’s scoring leader, Cale Makar, coming in at #3.
What’s fascinating about this Top 40 is Lane Hutson’s inclusion. The pessimist in me was prepared to see him well down this list, even with his incredible year. But nope, Lane Hutson didn’t just have a jaw-dropping year, it was one of the best performances we’ve seen in the last decade. In fact, it was the second-best season from a freshman in that time. That’s incredible.
And it’s side-by-side with David Farrance, who recorded a top-five year and reminds us to do our best to separate collegiate careers from NHL careers. Lest we forget the genuinely dominant campaigns achieved by Farrance, Tyler Madden, Tyler Motte, Dante Fabbro, and Nic Kerdiles back in the day.
I could talk about this graphic for a while. I’m fascinated by its results – and the ways that it could be refined further to spit out truly trackable information (some of which we’ll touch on later). I’ll be doing multiple articles on this dataset, so make sure to subscribe to the Substack. But for now, we’ll focus on answering the question we started our journey with.
Finding Our Answer
We already touched on perhaps the most exciting answer: Lane Hutson’s scoring was legit. To emphasize it once more, he managed the second-best performance from any freshman, and the best performance by a freshman blue-liner.
The graphic also shows us that comparing Fantilli to Eichel is still relatively reasonable. In addition to all of their other similarities, the duo also both recorded top-10 seasons. But as with Hutson, this answer isn’t all-that-surprising.
So let’s answer a question that isn’t so obvious: what should we think of Matthew Wood’s scoring? Well, by the metric we made here, he’s worth respecting. His scoring variable comes out to 2.057 and sits in the 90th percentile of our data set (202nd/2,448 Forwards, 352nd/3,931 all). I haven’t found a correlation between this variable and NHL-scoring (yet, look for that in a future piece!) but for some context, Josh Doan (2022-23, So.), Blake McLaughlin (2020-21, Jr.), and Andrew Copp (2014-15, Jr.) all have performances in that range.
That’s mighty fine ground for a freshman Matthew Wood and vindicates those who want to use his scoring to find promise in what’s been an interesting year.
Headed Home
This data, surprisingly, really enjoys the 2023 NHL Draft class. Three (Fantilli, Wood, Brindley) of the four draft-eligible forwards rank in the 89th-or-greater percentile of the past decade. That’s despite the fact that the 2022-23 season has generally been a high-scoring year for forwards, speaking to the place that this year’s class has in the room.
That’s encouraging for those championing this year’s Draft. And while it satisfies my frustrating quest to answer the question of ‘how impressive were this year’s high-scoring performances?’, it feels like we’re just scratching the surface of this data’s potential.
In future articles, I plan to adjust this data by conference, stretch it back to 2000, find how these adjusted stats correlate to NHL-scoring to give us a sense of projectability, and make an interactive tool where fans can see how their favorite player, schools, and eras match up against the rest. These steps will be recorded in their own articles, so make sure to stick around the Substack!
Who did I miss? What other questions do you have? Let me know on my Twitter (@NHLFoley)! And don’t forget to subscribe for more NHL and prospect content moving forward!