Welcome to Beyond the Basics!

My name is Zack Capozzi, and I run LacrosseReference.com, which focuses on developing and sharing new statistics and models for the sport.

I do not envy the people who need to decide who gets on the Tewaaraton Award lists. It’s so hard to be consistent in applying whatever framework you decide to use across the thousands of Division I women’s lacrosse players.

And then how do you balance career achievement versus the accomplishments of the current season? Fortunately, this is the type of decision (especially for the finalists and eventual winner) where a committee approach is generally going to get you to the right result.

Still, I think it’s interesting to look at the selections as a group to try and identify what sort of factors that voters held in highest esteem. What do they tell you about what makes a consensus top player? Within the group of selected players, what sort of differences do we see?

Today we are going to go through several different ways of divvying up the candidates to see what the advanced stats have to say about their 2022 seasons.

SCORING VS. ASSISTING

The first way that we can look at the list is by role. Are the players selected generally finishers or distributors? Goals get the glory, but most of them wouldn’t have happened without someone getting an assist. In the chart below, the players who generate assists at a high rate (after accounting for their usage) are to the right side. The players who have shot better are on top.

To make the list as an offensive player, you have to be a great finisher or a great distributor (although some players have been both). In the finisher group, Isabella Peterson, Charlotte North and Ellie Masera stand out. Maddie Jenner probably makes the list because of her draw dominance, but as we saw against Boston College, she’s been a phenomenal finisher as well.

On the facilitator side, it’s been wild to see Jamie Ortega fill the role that Katie Hoeg played last year for the Heels. Of the players on the list, she, Aurora Cordingley and Catriona Barry have generated a lot of their value by creating offense for others.

And then there is Meaghan Tyrrell. Just wow. The shooting metric we are using here is excess shooting, which looks at how many shots you’d expect someone to make given the profile of the shots they’ve taken. So, this is saying that she’s one of the top facilitators in the country, and she’s scored way more than you’d expect for her shot profile. Clearly the statistical favorite among the offensive players.

PRODUCTION VS. EFFICIENCY

I also like to dig into a player’s production and figure out whether it’s the result of increased chances or whether it’s more about being efficient with the chances she has. This is starting to change, but there has historically been an overreliance on point totals to determine who’s had the best season. But an inefficient player can have a very high point total if she takes more shots than anyone else. Usage rate matters. And that’s why it’s good to differentiate whether a player’s production is usage-driven or efficiency-driven.

Now, in this definition, I am using EGA (expected goals added) as my metric for production. That means that we can capture all of a player’s contributions, especially those that come from things other than scoring. And that is where Charlotte North really stands out. She doesn’t have the highest per-game EGA totals this year (Sydney Watson is a bit higher), but nobody has the combination of production and efficiency that she’s shown. In part this is due to her contributions in the draw control game, which not many top scorers can match. And in terms of efficiency, her 2022 season has actually been better than her 2021 campaign.

At the same time, you can’t really fault a player like Jamie Ortega for being a member of the most loaded roster in Division I women’s lacrosse. She’s never going to have the same raw production totals that a player like North or Watson generate simply because those players have higher usage rates. UNC has so many stars and such amazing depth that a player like Ortega just won’t have the opportunity to rack up crazy numbers. And that is why a stat like usage-adjusted-EGA is so critical.

uaEGA measures production after accounting for a player’s play share (essentially how many touches she gets). And on that count, only Tyrrell among the Tewaaraton candidates has a higher efficiency rating.

AVOIDING TURNOVERS

Now as you’ve seen above, to make the list, you don’t have to be a star distributor. Plenty of players make the list thanks to their ability to score. But it’s very hard to make the list if you are a finisher who also turns the ball over a lot. No amount of scoring makes up for those lost possessions. Just note the absence of dots in the lower righthand quadrant of this chart (low assist rate/high turnover rate).

This is also partly why first- and second-year players don’t tend to be recognized on this list as much. The general pattern for younger stars is to be effective in scoring but to have ball security issues. I suspect it’s about the skills that translate to the college game best. It seems to take longer for a player’s vision to adjust to the faster pace at this level where shooting seems to translate more easily. Sydney Watson is a great example of this. She’s always been a great finisher, but her ability to create offense for others while avoiding turnovers has been on quite the rocket ride.

When I look at the career arc for younger players, it’s not uncommon to see prolific scoring numbers. It’s that next step, becoming a well-rounded player that can do many things, that is where the real challenge lies.

SOME EXTRA SPOTLIGHT

I think they should add a few names to the list. I get that these players are not playing in marquee conferences, and they may not be playing against the best defenses week in and week out. But still, the seasons they’ve put together deserve notice.

First and foremost is Ashley Humphrey of Stanford. This is the same chart that I opened with, but instead of limiting ourselves to the Tewaaraton players, I’ve expanded the sample to the top 100 usage-rate players in the country. Humphrey has the highest assist rate in this sample, and her shooting percentage is right on par with Lauren Gilbert (among others). She’s a redshirt freshman and a player that I would expect to see on this list next year.

A few other names that fall into the “great player, terrible competition” bucket; Siena Gore (Kennesaw State), Lilly Siskind (ODU) and Abby Hormes (High Point). Gore and Hormes have been among the leaders in raw EGA-per-game all season. Siskind has put together a nice well-rounded statistical profile as well.

Don’t get me wrong; the committee picked an amazing group of 25 women. I’m not suggesting that anyone be replaced by these four, but that doesn’t mean we can’t use the stats to shed some light on some other players who deserve a look.

LACROSSE STATS RESOURCES

My goal with this column is to introduce fans to a new way to enjoy lacrosse. “Expand your fandom” is the mantra. I want you to walk away thinking about the players and stories presented here in a new light. But I also understand that some of these concepts can take some time to sink in. And part of the reason for this column is, after all, to educate.

To help this process along, I have several resources that have helped hundreds of lacrosse fans and coaches to internalize these new statistical concepts. The first is a Stats Glossary that explains each of my statistical concepts in more detail than I could fit here. The second is a Stats 101 resource, which provides context for each of my statistics. What is a good number? Who’s the current leader? That’s all there.

And last, I would love to hear from you. If you have questions or comments about the stats, feel free to reach out.