NELJ 2022 Season Preview (Ivy League)
Today we’ve got installment #3. The Ivy League. And this one, as you can imagine, was uniquely challenging.
So far, we have used the LacrosseReference lens to take a spin through the America East and NEC. My goal is to give you a sense of where each program is heading into the 2022 season and which players and games are likely to determine their success or failure as the season unfolds.
So without further ago, let’s run through the Ivy League teams that fall into the New England coverage area. The teams are presented in order of their current LaxElo ratings. Let’s go…
But first, let’s do something specific to the Ivy League. One of the ways I like to look at a team at the start of a season is the amount of production they are bringing back. My EGA (expected goals added) metric is the preferred way to measure this because it captures all the things that show up in the box score, good or bad, and puts them into a single number (it’s like WAR in baseball). Since we haven’t seen the Ivy League teams in 2 years, it’s useful to see how much they are bringing back relative to each other.
To calculate returning production, you simply add up the EGA for every player on a team’s roster. Then you add up the EGA just for those players that are on the team in the following year. Divide the 2nd number by the 1st and you get their returning share of production. We can do this for EGA generated by offense vs defense. The chart below shows the 6 Ivy League teams. Teams to the right return a larger share of their defense. Teams to the top return a larger share of their offensive production.
Harvard returns the least on defense and the 3rd least on offense. Princeton returns quite a bit on defense but they are at the bottom of the chart because of a Michael-Sowers-sized hole in their offense. Yale, Dartmouth and Brown seem best positioned to maintain some degree of continuity. Of course, this chart is just offense and defense, which misses the fact that their faceoff unit is inexperienced.
Yale MLAX
As with all the Ivy League teams, I feel like I’m on thin ice doing a statistical preview of Yale. We haven’t seen them on the field since March of 2020, and at the time TD Ierlan was taking draws. He’s since moved through the Big East, the Premier Lacrosse League, and now to the staff of Syracuse. Talk about a time-warp.
My general philosophy is that in the absence of evidence, you should assume things are what they are. In the case of a team like Yale, it means that I’d expect them to be at the top of the Ivy League, like they were pre-COVID. Andy Shay is still the coach. The facilities are still the facilities. The draw of Yale is the same as it ever was.
So while I don’t feel comfortable projecting that they will be better (or worse) than when we last saw them, I have to admit that the possible range of outcomes is greater for the Ivy teams than for the teams that played last year. And more specifically, in no area is the potential range of outcomes larger than at the faceoff X.
TD Ierlan ended his career with the 1st or 2nd best faceoff statistics ever, depending on how you want to measure it. In 2022, Yale has one guy on the roster (Joe Neuman) who has taken a faceoff in his career. And he’s taken 6.
Schedule Round-up
Strength-of-Schedule is estimated using the LacrosseReference Lax-Elo model, which assigns every team a rating based on their wins-and-losses and the scores of those games. For reference, the average team is assigned a 1500 rating.
Yale MLAX Overall SOS: 1590 (14th nationally)
Non-Conference: 1590 (17th)
The toughest 3-game stretch for Yale MLAX comes between Mar 13th and Mar 26th. Their average win probability in these 3 games is 61.0%
Opponent | LaxElo | Rank | WP |
---|---|---|---|
vs Villanova | 1642 | 17th | 75% |
@ Penn State | 1588 | 26th | 81% |
vs UMass | 1611 | 21st | 79% |
@ Denver | 1783 | 7th | 58% |
@ Cornell | 1808 | 3rd | 54% |
vs Princeton | 1680 | 12th | 71% |
vs Penn | 1670 | 14th | 72% |
vs Boston U | 1533 | 37th | 85% |
@ Dartmouth | 1314 | 62nd | 95% |
@ Brown | 1602 | 23rd | 79% |
vs Albany | 1578 | 30th | 82% |
vs Quinnipiac | 1402 | 53rd | 92% |
vs Harvard | 1464 | 44th | 89% |
Games in blue are part of the critical stretch for Yale MLAX |
Returning Talent Breakdown
It’s not that the cupboard is bare; it’s just that the players that filled it before aren’t here anymore. In fact, 60% of the team’s total production is no longer on the roster this year.
Players-to-Watch
This section may not always show the best or most well-known players on a roster. We’re really trying to shine a spotlight on the players that will determine each team’s overall success or failure.
Below is a selection of players likely to have an out-sized impact on the success of the Bulldogs this year
Player | Notes |
---|---|
Matt Brandau | TOP SKILL: the thing that most stands out is Points/Gm; his performance in his last season puts him in the 98th percentile nationally. |
Brian Tevlin | TOP SKILL: his most impressive statistical category in his last season was Points/Gm, where he ranked in the 82nd percentile among qualifying players nationally. IMPROVEMENT FOCUS: He was the weak-link when it comes to ball security on the team last year, coughing the ball up a total of 14 times. |
Thomas Bragg | TOP SKILL: the thing that most stands out is Points/Gm; his performance in his last season puts him in the 92nd percentile nationally. |
Christian Cropp | TOP SKILL: the thing that most stands out is Points/Gm; his performance in his last season puts him in the 82nd percentile nationally. |
Brown MLAX
I’ll forever be making one-off adjustments to my models to account for Brown having a season with just one game last year. That database record is going to haunt me forever. Of course, it does mean that they are the one Ivy League team where we can look at what they bring back from last year.
Certainly, one game isn’t enough to draw conclusions about how good last year’s team would have been.
But given the trend, it’s clear that one of the key tasks is going to be replacing Luke McCaleb. In 2020, he took 19% of the Bears’ shots and had 14% of their assists. His 12.0% play share meant he was the highest usage player on the team.
Statistically, replacing McCaleb’s production is going to come from some combination of George Grell, and Reed Moshyedi. Both had equivalent ball security ratings in 2020, but Moshyedi was the better shooter. It’ll probably be easier to replace McCaleb’s shooting relative to his ability to create offense. That will be the primary offensive challenge for the Bears staff heading into 2022.
Schedule Round-up
Brown MLAX Overall SOS: 1604 (13th nationally)
Non-Conference: 1586 (19th)
The toughest 3-game stretch for Brown MLAX comes between Apr 9th and Apr 23rd. Their average win probability in these 3 games is 28.1%
Opponent | LaxElo | Rank | WP |
---|---|---|---|
vs Quinnipiac | 1402 | 53rd | 76% |
@ North Carolina | 1778 | 8th | 27% |
vs Vermont | 1604 | 22nd | 50% |
vs Villanova | 1642 | 17th | 44% |
@ Providence | 1508 | 39th | 63% |
vs Stony Brook | 1559 | 33rd | 56% |
@ Harvard | 1464 | 44th | 69% |
vs UMass | 1611 | 21st | 49% |
vs Princeton | 1680 | 12th | 39% |
@ Penn | 1670 | 14th | 40% |
vs Yale | 1837 | 2nd | 21% |
@ Cornell | 1808 | 3rd | 23% |
vs Bryant | 1585 | 27th | 52% |
vs Dartmouth | 1314 | 62nd | 84% |
Games in blue are part of the critical stretch for Brown MLAX |
Returning Talent Breakdown
It’s not that the cupboard is bare; it’s just that the players that filled it before aren’t here anymore. In fact, 49% of the team’s total production is no longer on the roster this year.
Players-to-Watch
Below is a selection of players likely to have an out-sized impact on the success of the Bears this year
Player | Notes |
---|---|
Darian Cook | TOP SKILL: his most impressive statistical category in his last season was Points/Gm, where he ranked in the 95th percentile among qualifying players nationally. TEAM LEADER: He was the top distributor on the team last year; no one had more assists last year than his 8. |
Ryan Aughavin | TOP SKILL: his mark of 7.0 Assist:Turnover tells the story of his in his last season. That figure works out to the 99th percentile nationally TEAM LEADER: He was the primary marksman on the team last year having taken a team-high 54 shots. |
George Grell | TOP SKILL: his mark of 6.5 Offensive EGA tells the story of his in his last season. That figure works out to the 86th percentile nationally |
Adrian Enchill | TOP SKILL: the thing that most stands out is Ball Security; his performance in his last season puts him in the 84th percentile nationally. |
Andrew Geppert | TOP SKILL: his mark of 3.4 Defensive EGA tells the story of his in his last season. That figure works out to the 97th percentile nationally |
Harvard MLAX
It is wild to me that Gerry Byrne has coached 4 games at Harvard. It feels like he’s been there for 5 years. Maybe it’s just me; maybe it’s a prolific social media account. Either way, the 2-2 mark that the Crimson put up in was not driven by the defense, as you might expect from a Byrne-coached team.
Instead, the offense was the story in those first 4 games, putting up the 24th best offensive efficiency rating in the country (after adjusting for the strength of the opposing defenses). The 33.8% mark, albeit over just 4 games, was the best for the Crimson since the 2016 Morgan Cheek/Devin Dwyer squad.
So the offense was pretty good, but we can break down offensive performance into two main buckets: shooting and ball security. The best offenses do both well, but Harvard did not. Their adjusted turnover rate was 43.5% which was 52nd nationally. Their shooting is what redeemed them, with a 35% mark that was 10th best nationally.
Keep an eye out for whether this team is able to ramp up their ball security without losing the good opportunities that led to that high shooting percentage. Better ball security may mean being less aggressive, and being less aggressive can lead to a more conservative offense that shoots at a lower rate. But if the lower shooting percentage is offset by more overall chances, they could come out ahead.
Schedule Round-up
Harvard MLAX Overall SOS: 1516 (31st nationally)
Non-Conference: 1382 (66th)
The toughest 3-game stretch for Harvard MLAX comes between Apr 9th and Apr 23rd. Their average win probability in these 3 games is 19.3%
Opponent | LaxElo | Rank | WP |
---|---|---|---|
vs NJIT | 1007 | 75th | 93% |
vs Ohio State | 1581 | 29th | 34% |
@ Fairfield | 1309 | 64th | 71% |
@ Michigan | 1464 | 45th | 50% |
vs Brown | 1602 | 23rd | 31% |
vs Boston U | 1533 | 37th | 40% |
vs Dartmouth | 1314 | 62nd | 70% |
vs Colgate | 1398 | 55th | 59% |
@ Cornell | 1808 | 3rd | 12% |
@ Penn | 1670 | 14th | 23% |
vs Princeton | 1680 | 12th | 22% |
@ Yale | 1837 | 2nd | 11% |
Games in blue are part of the critical stretch for Harvard MLAX |
Returning Talent Breakdown
It’s not that the cupboard is bare; it’s just that the players that filled it before aren’t here anymore. In fact, 49% of the team’s total production is no longer on the roster this year.
Players-to-Watch
Below is a selection of players likely to have an out-sized impact on the success of the Crimson this year
Player | Notes |
---|---|
Nick Loring | TOP SKILL: his mark of 2.2 Points/Gm tells the story of his in his last season. That figure works out to the 90th percentile nationally |
Austin Madronic | TOP SKILL: his mark of 3.5 Points/Gm tells the story of his in his last season. That figure works out to the 96th percentile nationally TEAM LEADER: He was the leading goal-scorer on the team last year with a total tally of 9 goals scored. |
Kyle Massimilian | FACEOFF ELO: He enters the season as the 25th-rated faceoff guy based on the faceoff Elo model. |
Steven Cuccurullo | TOP SKILL: his most impressive statistical category in his last season was Ball Security, where he ranked in the 99th percentile among qualifying players nationally. |
Isaiah Dawson | IMPROVEMENT FOCUS: He was the weak-link when it comes to ball security on the team last year, coughing the ball up a total of 6 times. |
Dartmouth MLAX
As an observer of college lacrosse, 2020 felt disappointing for the Ivy League teams. Several were looking good for NCAA tournament berths and I don’t think there was another conference in the country with more star power. I can only imagine how it felt for fans of the Ivy League teams.
Dartmouth’s 2020 doesn’t have the same feel because even after a strong start, they probably weren’t going to end up in the NCAA conversation. They finished 3-1, the only blemish a one-goal loss to Vermont in their last game. We’ll never know how they would have fared in Ivy League play. That said, there may not be a team in the country that is on a stronger trajectory than the Big Green.
I think it’s critical to adjust for the quality of the teams faced. And when we do that for Dartmouth, their 2020 start is remarkable in its contrast to 2019. Using the opponent-adjusted marks, their offensive efficiency was 10 percentage points better (32.8% in ’20 vs 22.7% in ’19). Their defense was 4 percentage points better (27.5% vs 31.4%). Their faceoff game was 20 percentage points better (49.9% vs 30.0%). And their keepers were 6 percentage points better (59.3% vs 53.2%).
If Dartmouth can even just maintain what they were doing in ’20, this is going to be an interesting team.
Schedule Round-up
Dartmouth MLAX Overall SOS: 1563 (19th nationally)
Non-Conference: 1466 (52nd)
The toughest 3-game stretch for Dartmouth MLAX comes between Apr 9th and Apr 23rd. Their average win probability in these 3 games is 9.0%
Opponent | LaxElo | Rank | WP |
---|---|---|---|
vs Merrimack | 1449 | 48th | 31% |
@ Bryant | 1585 | 27th | 17% |
@ Siena | 1260 | 68th | 58% |
vs Vermont | 1604 | 22nd | 16% |
vs St. John’s | 1230 | 70th | 62% |
@ Ohio State | 1581 | 29th | 18% |
@ Harvard | 1464 | 44th | 30% |
vs Cornell | 1808 | 3rd | 5% |
vs Stony Brook | 1559 | 33rd | 20% |
vs Yale | 1837 | 2nd | 5% |
@ Princeton | 1680 | 12th | 11% |
vs Penn | 1670 | 14th | 11% |
@ Brown | 1602 | 23rd | 16% |
Games in blue are part of the critical stretch for Dartmouth MLAX |
Returning Talent Breakdown
While every team is going to have some gaps; they have more than most. They return just 64% of their overall production from their last roster.
Players-to-Watch
Below is a selection of players likely to have an out-sized impact on the success of the Big Green this year
Player | Notes |
---|---|
Matt Paul | TOP SKILL: his most impressive statistical category in his last season was Saved Shot Rate, where he ranked in the 99th percentile among qualifying players nationally. TEAM LEADER: He was the leading goal-scorer on the team last year with a total tally of 11 goals scored. |
Mitchell Myers | FACEOFF ELO: He enters the season as the 38th-rated faceoff guy based on the faceoff Elo model. |
George Prince | TOP SKILL: his mark of 4.0 Points/Gm tells the story of his in his last season. That figure works out to the 98th percentile nationally TEAM LEADER: He was the top distributor on the team last year; no one had more assists last year than his 7. |
Tommy Rogan | TOP SKILL: his mark of 61.5% Shooting Pct tells the story of his in his last season. That figure works out to the 99th percentile nationally |
Peter Rizzotti | TOP SKILL: his most impressive statistical category in his last season was Defensive EGA, where he ranked in the 83rd percentile among qualifying players nationally. |
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