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.

The folks at USA Lacrosse Magazine offered me a chance to share some of my observations in a weekly column, and I jumped at the chance. Come back every Tuesday to go beyond the box score in both men’s and women’s lacrosse.

Memory is a funny thing. Doesn’t the 2021 Boston College national championship feel obvious at this point? It’s hard to imagine an alternate reality where Charlotte North didn’t become a lacrosse sensation, where UNC or Cuse had managed to knock off the Eagles and write a different ending for last year’s season.

But when the NCAA tournament started, it certainly didn’t feel inevitable. BC didn’t even have a bye in the first round. In last year’s Bracket Challenge, just 7 percent of all entries picked the Eagles to win. (A whopping 55 percent picked North Carolina.)

Postseason success is what defines a season, but it can sometimes obscure the memory of what came before it. So think of today’s article as a bit of a time capsule. As we sail into the turbid waters of the 2022 postseason, let’s leave a snapshot for future historians so that they know what the 2022 regular season was like.

And, this being Beyond the Basics, of course we are going to use numbers to figure out the most salient parts of that story. Before the season started, I ran my simulator through all of the scheduled games a couple thousand times to get a sense for what sort of outcomes we could expect for each team. This gave us a handy value for each team, the number of “expected” wins they would come up with prior to Selection Sunday.

In parallel, I also created a contest where fans could predict whether each team would end up winning more or fewer games than the expected number.

This gives us two variations on the expectations for each team: what did the model expect them to do and what did the lacrosse community expect them to do? What follows is a look at five teams, what we all thought they’d do, and an analysis of just how they managed to outperform those expectations by so much.

IONA (8.5 wins over expectation)

Nobody has beaten expectations more than the Gaels. Perhaps we were justified in having low expectations; they did win just one game in 2021 and finished the year on a six-game losing streak. In the Win Totals Contest, 37 percent of entries picked Iona to win more than 2.5 games.

Now, while you wouldn’t necessarily say that they are the class of the MAAC, I don’t think there’s an argument that another MAAC team has had a better year relative to expectations. And if you want to give one “why” for this team’s improvement, it’s the offense, which is among the MAAC leaders and ranks 48th nationally in efficiency.

Going a bit deeper, ball security has been the strength; the Gaels have turned it over on just 26 percent of their offensive possessions. Siena is next best in the MAAC at 31 percent, but the gap is large. Siena is closer to Manhattan with the sixth-best turnover rate than they are to Iona in first.

The tone has been set by freshman Kira Varada, who has the highest usage rate on the team and a ball security rating of 95 (out of a possible 100). She’s got 37 goals on the year and just 18 turnovers. None of their top rotation players rates lower than a 72 on ball security.

The impressive ball security ratings have allowed them to overcome a so-so shooting record (59th-best shooting percentage) and put up a 31.4-percent opp-adjusted efficiency rating (24th-best nationally). That is progress.

 

 

RUTGERS (8.4 wins over expectation)

The Big Ten is always going to be a tough slog with Northwestern and its death grip on the top spot. With all the incoming talent, you might have expected Maryland to over-perform its projections (which don’t account for transfers). But no, Rutgers has been the biggest surprise.

The models had the Scarlet Knights winning 4.5 games and the fan entries were pretty much in agreement. As of this writing, they are projected to out-win those projections by a whopping eight victories. And this is the culmination of a multi-year positive trend for the Scarlet Knights.
 

It’s a bit tough to decide whether the offense or the defense has been more integral in their rise. Both units are up about 20 places in the opponent-adjusted rankings since last year. And it makes the per-possession advantage that Rutgers enjoys so much more pronounced. On an opponent-adjusted basis, the 2021 team scored 31 goals per 100 possessions and allowed 27 goals per 100 possessions. That works out to a four-goal advantage per 100 possessions. This year, that same number is 13.

With games left against Penn State and Ohio State, there is still some question about where Rutgers will end up in the Big Ten tournament. In 56 percent of the simulations, Rutgers got the third seed; in 30 percent, they ended up with the fourth seed. And there is still a 12-percent chance they get the sixth seed when the Big Ten bracket comes out.

YALE (6.7 wins over expectation)

The fans had a good feeling about Yale. Seven in 10 entries picked Yale to win more than the 3.5 games that the model predicted for them. And wow were the fans right.

Against a schedule that ranks 17th in the country, Yale has already run up nine victories and will take a five-game winning streak into the battle for Connecticut against UConn on Wednesday.

The Yale defense has made a bigger jump than the offense when compared to the 2020 season, when the D finished 96th in the country. This year, with a 28-percent opponent-adjusted efficiency mark, the Bulldogs’ defense currently ranks 48th. But I’m of the opinion that offense is more important for teams trying to level up, and with the 26th-ranked offense, Yale is in the conversation both nationally and in the Ivy League, it ranks second behind Princeton.

Olivia Penoyer (41 percent of team assists; 14 percent of team shots), Fallon Vaughn (14 percent of assists; 17 percent of shots) and Olivia Markert (13 percent of assists; 19 percent of shots) have been the top-three options for coach Erica Bamford’s squad.

And they are getting better. Since the loss to Notre Dame, the offensive efficiency trend has been steady and going in the right direction.

Now, keep in mind, this list of most surprising teams was compiled using projected end-of-season win totals. Yale is expected to win just one of its final four regular season games. Even accounting for that, the Bulldogs have had one of the most surprising seasons. If they can steal a few more wins down the stretch, this will be an even more impressive campaign.

OHIO STATE (6.0 wins over expectation)

Seeing a pattern? Across men’s and women’s lacrosse, three of the 10 teams that most outperformed their expectations were Big Ten teams. I’m not sure what the exact explanation for that is, but I suspect that the Big-Ten-only conference season they played in 2021 may have something to do with it.

Of course, the alternative is that the three Big Ten teams all happened to make serious strides this year. It’s not as if all 10 of our out-performers were from the conference.

As for the Buckeyes, the surface story here looks like one of defense and possessions. In terms of raw efficiency, coach Amy Bokker’s team ranks 66th in offensive efficiency, 30th in defensive efficiency and 10th in draw control win rate. The raw stats view is a team with a strong defense that relies on keeping the ball out of its opponent’s stick to cover up a weaker offense.

This is why we adjust the raw stats for the quality of the opponents. After we adjust for the relatively difficult schedule the Buckeyes have faced, their draw control win rate ranks ninth and their defense moves up two spots from 30th to 28th. The offense, however, moves from 66th in the raw rankings to 35th in the opponent-adjusted rankings. Thanks to games against Denver, James Madison and their Big Ten slate, the Buckeyes have one of the largest gaps between their raw offense and their opponent-adjusted offense.

Looked at through the opponent-adjustment lens, the story changes. In reality, it’s the offense that has made the biggest strides this year. Within the Big Ten, there are three tiers that have emerged. Northwestern and Maryland are in the top tier. Then there’s a next tier that you’d put Rutgers and Michigan in. The question over the next few weeks is whether Ohio State’s surprising 2022 season will end with them joining that group.

DUKE (5.5 wins over expectation)

Did you catch that Duke win over Boston College? The win probability chart gives you a pretty good sense of what a tense game it was, especially once BC tied it up late.

And now the Blue Devils have one game against UNC to determine who gets the top seed in the ACC tournament. I’m sure that the Duke players and coaches are not surprised by their record, but they certainly over-performed what the models thought they’d do this year.

Cat Barry has been the top option. She’s got 24 percent of the team’s assists and 18 percent of the team’s shots (both team highs). Her individual player efficiency rating is a 91 (out of 100). And while she’s been the top option, the offense has climbed to be the third-rated offense in the country on the strength of their depth. Against BC, for example, five different players scored at least three points.

As it stands, the Blue Devils are a lock for the NCAA tournament, so we’ll get to see how this depth plays in May.

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.