Lacrosse Analytics

[laxreference]

Duke looked good. The 34.4% offensive efficiency just edged out the mark they put up against RMU last year in their first game (32%). The difference is that the Blue Devils never made us nervous that the game was ever actually in doubt. In last year's matchup, RMU actually had a win probability above 50% with about 4 minutes left in the first half.

This year? No such luck. With a 10-3 first quarter, this game was over before it really ever got started. And you probably credit the Duke defense for that. Last year, they gave up 29.3% efficiency day to RMU. Tonight? 24.5%. And if you want to throw the ride in there too (9 failed clears), the defense never gave the Colonials a chance to put up a fight.

If you are on the Duke NCAA Champs 2022 train, I doubt you saw anything tonight to make you wonder whether you want to keep your seat.

Good analysis. On the defense vs ride how does that work into the number? Thought the ride was strong (and/or ROMO poor on clears) but 6 on 6 defense less strong. Could also be a factor of ROMO missing some clear dunks.

Failed clears do not count against an offense (or for a defense) in terms of efficiency. The denominator in the efficiency calculation is (total times they gained possession in the play by play - failed clears). So no, the 24.5% efficiency for the Duke defense is not affected by the number of failed clears for ROMO.

What happens when a team clear the ball over the mid-line and then gets stripped of the ball before getting it to the attack? With hard riding teams typically riding well into the offensive zone, I’m guessing there is grey area around a “successful clear” and a turnover in the offensive end.

That would count as a turnover for the offense and would count against their offensive efficiency. You are 100% right though that this is a grey area. Some teams actually adjust my data on the backend in situations where something is missed by the play by play.

[laxreference]

Thank you for your work, find your analytics very interesting despite my lean to subjective "eye test". The best coaches today incorporate both. Se. When coaching , I wanted the the explosive X factor who may measure as less efficient but can 'play up' to any level of completion. seen some talents play down to inferior opponents with efficient players ruling day only to see same X factor raise and assert themselves agaisnt superior opponents which their more efficient teammates cant do. Have noted that opponents views, from coaches and players when available tend to basically reinforce my assessments of own.. Who my opponent prepares for tells much.

100% agree with this. My stance has always been that the closer you are to something, whether it is an individual player or a game against a team you know really well, the more you rely on coaches intuition. The farther away your perspective is, the better the models and numbers can be complementary to a coach's understanding of a situation.

But it's gotta be both working in concert. Fortunately, we have a good crop of coaches in D1 that can put it all together.

[laxreference]

As always, here is the top individual EGA performances of the past week. The full post is here, but here are the highlights...

Josh Zawada (MICH) - 6.76 EGA


Here is how the rest of the top 10 shook out:

Evan McGreen (PC) - 6.34 EGA
Jack Myers (OSU) - 6.22 EGA
Michael Boehm (MICH) - 6.11 EGA
Brennan O'Neill (DUKE) - 5.50 EGA
Mike Robinson (DEL) - 5.49 EGA
Ted Sullivan (DEN) - 5.26 EGA
Mitch Bartolo (RU) - 5.26 EGA
Sean Goldsmith (MER) - 5.02 EGA
Jake Naso (DUKE) - 4.97 EGA

[laxreference]

If you are following the Marist vs Rutgers game, the win probability engine is up and running.

[laxreference]

We knew coming in to this year that Rutgers was going to have to fill a lot of holes on offense. Last year, the top 3 guys were Connor Kirst, Adam Charalambides, and Kieran Mullins. Collectively, they took 54% of the Scarlet Knights' shots and accounted for 54% of their assists.

It's been just 2 games, so don't think that the RU offense is a finished product by any means, but we can start to see the trends shake out. Through 2 games, Mitch Bartolo, Ross Scott, and Ronan Jacoby have been the 3 players with the highest play share. Collectively, these 3 have 57% of Rutgers' shots, but just 31% of their assists.

Something else to keep in mind; you might look at the efficiencies for the Scarlet Knights and think that they played better on offense against LIU. The efficiency in that game was 28.8%; it was just 26.0% against Marist. But that's why we adjust efficiencies for the quality of the opponent. After accounting for the defenses they faced, they actually ticked up today (28.9% adjusted efficiency vs 28.4% over the weekend).

[Farfromgeneva]

What’s the offensive efficiency standard for an at large team over the past 5-7yrs?

[laxreference]

What’s the offensive efficiency standard for an at large team over the past 5-7yrs?

I'm defining at-large as a top-10 RPI on Selection Sunday; otherwise, you aren't getting bubble consideration after the AQs take their slots. If we are using raw offensive efficiency, it has hovered in a narrow range a little above 35%.

In opponent-adjusted terms, it's a narrower range (a good sign for the model). The average top-10 RPI team's opponent-adjusted efficiency has been between 36.2% and 36.7% every year since I've tracked it.

(The first efficiency table is raw (goals divided by possessions); the 2nd table is adjusted to account for the strength of the opposing defenses)

2016: 35.9%
2017: 35.7%
2018: 35.9%
2019: 34.7%
2020: 35.2%
2021: 35.3%

2016: 36.5%
2017: 36.6%
2018: 36.5%
2019: 36.2%
2020: 36.7%
2021: 36.7%

[Farfromgeneva]

What’s the offensive efficiency standard for an at large team over the past 5-7yrs?

I'm defining at-large as a top-10 RPI on Selection Sunday; otherwise, you aren't getting bubble consideration after the AQs take their slots. If we are using raw offensive efficiency, it has hovered in a narrow range a little above 35%.

In opponent-adjusted terms, it's a narrower range (a good sign for the model). The average top-10 RPI team's opponent-adjusted efficiency has been between 36.2% and 36.7% every year since I've tracked it.

(The first efficiency table is raw (goals divided by possessions); the 2nd table is adjusted to account for the strength of the opposing defenses)

2016: 35.9%
2017: 35.7%
2018: 35.9%
2019: 34.7%
2020: 35.2%
2021: 35.3%

2016: 36.5%
2017: 36.6%
2018: 36.5%
2019: 36.2%
2020: 36.7%
2021: 36.7%

Thanks that’s awesome.

BTW love your site. Not ready to financially commit-currently looking to cut some of the literally 9 digital (roku platform) tv apps, on top of cable at nearly $300/mo hammering my wife on do we need all of these so can’t turn around and add something at the moment but looks like you’ve put together a nice site that offers value to lacrosse fans.

[stupefied]

Rutgers has a Charmin soft schedule which makes assessing their team and players on stats alone difficult. How they fare agaisnt Maryland, Army and Loyola will be telling.

[Farfromgeneva]

Maybe but would one expect their offensive efficiency to improve against "tougher" competition? Some fans there think it's too easy against meek little teams by their own words.

[stupefied]

Maybe but would one expect their offensive efficiency to improve against "tougher" competition? Some fans there think it's too easy against meek little teams by their own words.
[/quote}

Based off scrimmage performances, Hobart is not one of those meek little teams but a sleeper . 11-11 with Yale true ?

[Farfromgeneva]

Scrimmages. I don't know but optimistic - 12-11 v Mich, 13-8 v Prov after starting really slow and then that Yale score. Don't want to overrate scrimmages but three respectable outings for a team that is somewhat barbelled with very experienced handful of Sr/5th yrs and a lot of Sophs who will be playing with limited experience the last two years. Cansius, Lehigh, Cornell to start so we will know by march how it's looking.

[stupefied]

"I'm pickin' up good vibrations"

respect for a historical program with posters here who are optimistic yet based.

[Farfromgeneva]

https://tenor.com/view/beavis-and-butth ... f-15174543

[laxreference]

<b>NCAA D1 Men</b><br>Updated list of Live Win Probability Links

- Duke vs Manhattan
- Colgate vs High Point
- Richmond vs North Carolina
- Johns Hopkins vs Towson

[laxreference]

Updated list of Live Win Probability Links

- Siena vs LIU
- Quinnipiac vs UMass-Lowell
- Lehigh vs NJIT
- Merrimack vs Boston U
- Cleveland State vs Ohio State
- Loyola vs Maryland
- UMass vs Army
- Bryant vs Providence
- Utah vs Vermont
- St. Bonaventure vs Saint Joseph's
- Canisius vs Hobart
- Fairfield vs Stony Brook
- Marist vs Binghamton
- Mercer vs Navy
- Marquette vs Bellarmine
- Lafayette vs VMI
- Holy Cross vs Syracuse
- Rutgers vs St. John's
- Air Force vs Denver
- Bucknell vs Robert Morris
- Detroit vs Michigan
- Sacred Heart vs Hofstra
- Mount St Marys vs Delaware
- Villanova vs Penn State

[laxreference]

Updated list of Live Win Probability Links

- Siena vs LIU
- Quinnipiac vs UMass-Lowell
- Lehigh vs NJIT
- Cleveland State vs Ohio State
- Mercer vs Boston U
- Loyola vs Maryland
- UMass vs Army
- Bryant vs Providence
- Utah vs Vermont
- St. Bonaventure vs Saint Joseph's
- Canisius vs Hobart
- Fairfield vs Stony Brook
- Marist vs Binghamton
- Mercer vs Navy
- Marquette vs Bellarmine
- Lafayette vs VMI
- Holy Cross vs Syracuse
- Rutgers vs St. John's
- Air Force vs Denver
- Bucknell vs Robert Morris
- Detroit vs Michigan
- Sacred Heart vs Hofstra
- Mount St Marys vs Delaware
- Villanova vs Penn State

[laxreference]

Updated list of Live Win Probability Links

- Colgate vs North Carolina
- Jacksonville vs Duke
- Johns Hopkins vs Georgetown
- High Point vs Virginia

[laxreference]

Here are the 3 Stars for February 13th

daily_stars_20220213_NCAAD1Men.jpg (115.92 KiB) Viewed 1108 times

[laxreference]

As always, here is the top individual EGA performances of the past week. The full post is here, but here are the highlights...

Jacob Alexander (BRY) - 7.90 EGA

Alexander had a couple points in this one, and he's been part of a larger trend of aggressive point-scoring FOGOs over the past season and change.

Here is how the rest of the top 10 shook out:

Luke Wierman (MD) - 7.05 EGA
Josh Zawada (MICH) - 6.94 EGA
Justin Inacio (OSU) - 6.37 EGA
Demitri George (QUI) - 6.30 EGA
Conor Foley (UML) - 5.85 EGA
Chris Gray (UNC) - 5.74 EGA
Bryce Ford (FFL) - 5.73 EGA
Brendan Curry (SYR) - 5.70 EGA
Joey Epstein (JHU) - 5.66 EGA