Each week, we will look back at the games that were to see which players had the largest individual performances. I say largest because the contributions that we can measure (from play by play) tend to be things that are easy to count. This includes, goals, shots, assists, turnovers, penalties, etc. We can’t measure a defender who shuts down an opposing player so completely that he doesn’t even touch the ball. Still, it is interesting to be able to identify the players that really filled it up each weekend and give them a shout out here.
For a bit of background, in order to rank single game performances, we needed a way to condense box score stats to a single number for each player. In order to do this, we relied on our expected goal values methodology, which assigns a goal value to each type of play depending on how often it leads to a goal in the next 60 seconds. By adding up all the expected goals added for each player, we can get to that single number and these rankings.
We have also tagged each performance with the opponent’s ELO rating. The higher the number, the stronger the opponent. This should help to give some context for each performance. Did the player feast on the dregs of D1 or did they put up these numbers against a quality opponent?
Click on any player’s name or the PRO logo () and you’ll head straight to the detailed breakdown on their LacrosseReference PRO page. As opposed to last year, all players appearing in the weekly rundown are unlocked and the information on their page is available to all readers.
I mentioned last week that the formula for ranking individual statistical performances has changed. I wrote about how that meant you were likely to see fewer FOGOs on this list each week. I don’t know if Jacob Alexander read that, but he seems to have figured out how to game the system.
Yes, he had 20 faceoff wins, but he was 2nd on the team with 3 points. For a FOGO to have 20 faceoff wins is no longer a guarantee that they’ll show up here. If you add 3 points on 4 shots, that’s a different story.
Really, I did change the formula. But again, we have another FOGO playing the role of offensive threat. Wierman scored 2 goals on 2 shots and added an assist for good measure. Who needs Jared Bernhardt, am I right?
So far, the Terps have been +10 as far as possession margin. Against High Point, they were +8, and in this one, they ended up +12. It’s hard enough to beat Maryland. It’s almost impossible if they are going to have 10 more possessions than you will. Feels like we might just be working towards Weirman vs Lasalla Round 2 at this point.
Through 2 games, Josh Zawada has a 14.5% weighted play share. That means that, factoring out faceoff plays, he’s responsible for 14.5% of the plays recorded in the play-by-play for Michigan. Last year, his mark was 10.1%. So through 2 games, he’s certainly playing a larger role than he did last season.
And so far, it’s working. Granted, Bellarmine and Detroit are currently the 38th and 45 ranked defenses, but Zawada’s numbers are still eye-catching. Most impressively, he’s tripled his assist rate from last season, while cutting his turnover rate by a factor of 3. There are many reasons for the early success of the Wolverine’s offense, but Zawada is first among many.
There were 20 points scored by FOGOs during the Saturday games. That makes it the 14th highest FOGO-scoring day over the past 7 seasons (measured on a PPG basis).
Justin Inacio contributed 2 of those points against CSU. In the Big Ten only 2021 season, the Bucks were about even in terms of possessions. In 2020, they were +2.7. I certainly don’t think that Inacio is going to continue to average an 88.4% faceoff win rate, but if he can help them to a faceoff advantage against their Big Ten slate, that’s going to vastly increase the chances that Ohio State can contend.
Demitri George also joined the parade of point-scoring FOGOs this weekend. His 2 assists against UML were the first 2 assists of his career. I can say with 100% certainty that the Bobcats don’t come back and win this game without the +12 faceoff advantage that George earned them by going 22-10 on the day.
QU got the victory, but Foley played the biggest role in putting the Bobcats into the hole that they ultimately dug out of. Of the Riverhawks’ 14 goals, Foley either scored or assisted half of them. In 2021, Foley averaged 5.2 shots per game. In this one, he took 11.
The offense put up a 40% raw efficiency mark in this one. This ties their best mark since I’ve been tracking lacrosse stats (7 years).
#7 – Chris Gray (North Carolina) – 6.24 goals added
Feb 11 vs Richmond Opp ELO: 1626
For all of his highlight goals, Gray’s best Madden rating comes from his ability to generate offense for his teammates. Last season, on a 0-100 scale, his assists-per-touch put him in the 92nd percentile; his shooting percentage put him in the 72nd. That is not to say that he’s not a good shooter, but I would say he’s a pass-first player who shoots when it’s the right thing to do. Not much higher praise for an attackman. Here is the player card for Gray from last year.
It really looked like Fairfield was going to start 2022 with a win. They led 4-2 after the first period and 7-6 at halftime. Even entering the 4th quarter, they still were up 10-8. A 5 goal outburst from Stony Brook swung the game their way. Fairfield’s 1st shot in the 4th quarter came with an average of 38 seconds left on the shot clock after come with an average of 49 seconds left earlier in the game.
Interestingly though, their average possession in the 4th quarter lasted just 35 seconds, the shortest average of any quarter. So they seem to have tried taking the air out of the ball and working the clock, only to have it completely backfire as their turnover rate shot up and their average possession was actually the shortest of the game.
Makes you wonder what would have happened if they’d just kept their foot on the gas.
The fact that Syracuse scored 28 goals and only had one player on this list speaks to the fact that a) this was a balanced attack and b) that they were able to empty the bench in their blow-out win over Holy Cross.
With the injuries and graduations, the huge question facing Syracuse fans was who is going to step into those roles. Dordevic is one, Curry is certainly one as well. In 2021, he had an 85th percentile assist rate and a 64th percentile shooting percentage. I’m always interested to see how a player’s role aligns with his metrics, so keep an eye on whether Curry ends up contributing more through offense generated for others or as a finisher on the receiving end.
Our No. 10 slot this week is a good chance to demonstrate the new algorithm I’m using to rank these games. You’ll notice that Epstein’s raw EGA number (6.12) is actually higher than the player in the slot above. And it’s because the ranking is based on composite EGA, which combines raw EGA and usage-adjusted-EGA. Usage-adjusted-EGA accounts for the usage rate for each player. For example, the more shots you take, the higher your usage rate, and all things equal, the lower your usage-adjusted-EGA.
Epstein had 7 points to Curry’s 6. But he also took 16 shots, compared to 5 for Curry. So yes, he did produce more value, but he had a lot more chances than Curry. So adjusted for their usage rates, Curry’s performance was deemed more impressive.