Lacrosse Analytics: A Look at the Professional Faceoff

Lacrosse Analytics: A Look at the Professional Faceoff

The faceoff has been a contentious topic in recent history. The rule changes in NCAA Men's Lacrosse, requiring standing neutral grip (SNG), were made leading up to the 2021 season after complaints of the debated competitive advantage that a dominant FO men gave their team. To support their claim, those opposed to the faceoff cited dominant FO men on successful teams like Trevor Baptiste and, more recently, TD Ierlan. 

While the faceoff has its detractors due to the supposed lopsided advantage, there is plenty of evidence to the contrary. The nation's best FO men before the rule changes have remained dominant and improvements to league parity were negligible at best. Examples of dominant faceoff performances in losses include Lehigh vs. Rutgers, Denver vs. Loyola, Lehigh vs. Villanova and Bellermine vs. Mercer in 2021. A more systematic analysis, although from 2013, conducted by College Crosse showed a weak relationship between faceoff percentage (FO%) and overall team performance (R2 = 0.11). This feels unsurprising as teams like Mercer have traditionally not been able to compete with the top teams in NCAA Division 1 and just having a fantastic athlete at the stripe (or changing the rules, clearly) will not be the solution.

While the debate continues at the collegiate ranks, we wanted to see if the same could be said about professional lacrosse, where the talent gap across the league is much smaller. With the incoming pool of talent at the position, it is a buyer’s market and many PLL teams entered the offseason leaving many FO specialists unprotected.

The Cannons were the first to go heavy on faceoff talent, drafting three in the 2021 PLL Expansion Draft. Likewise, the Redwoods entered camp with four faceoff men, including the NCAA Div. I career leader in faceoff percentage, TD Ierlan. Even the Atlas drafted another faceoff specialist in Gerard Arceri to give Baptiste some help after two years without a dedicated backup. Will the increased flexibility at the stripe benefit these teams?

Photo courtesy of the PLL

The Impact of the Faceoff on Win Percentage

We can look at the past two seasons, which were used to calibrate the PLT Win Probability Engine. This model was created by looking at a team’s aggregate stats within a season leading up to a game and determining the importance of each statistic in the context of winning their next game. The importance of a statistic is governed by a number, called a "weight." If the weight is high and positive, you want more of that stat and vice versa if the weight is high and negative. For context, the weight of the score, goals including two-point goals as 2 scores, is 1.2. So a team wants more goals to win, as we might expect in a competition. In our model, the weight associated with FO% is -0.11, a tenfold decrease in magnitude compared to scores. This says that faceoffs, in a vacuum, are not good predictors for winning. But, why? Do faceoffs not help at all (on average)?

Interestingly, over both PLL seasons, FO% is strongly correlated with average scores (AS, r = 0.61), but not correlated with scores against average (SAA, r = -0.09). Winning faceoffs, intuitively, helps your offense score more often. However, winning faceoffs, a.k.a winning possession time, does not help your defense on average. While the latter feels counterintuitive, faceoffs would have to be a better predictor of winning if it significantly helped both your offense and defense. If it were that easy, the 2019 Atlas, for instance, would have had a much better season.

Redwoods' Head Coach Nat St. Laurent’s offseason decision to bring four FO men to training camp, including rookie TD Ierlan, looks somehow even better after this analysis (although only two remained after cuts). The Redwoods have arguably the second best defense in the first two years of the PLL when considering CTOs and SAA (70 and 10.5 in 2020, 67 and 11.5 in 2019). Their offense has not shared the defense’s success ranking in the bottom three for AS (and total scores) in both the 2019 and 2020. Interestingly, the Redwoods also won the lowest percentage of their faceoffs in both regular seasons. Their success in the 2019 playoffs, on their way to the championship game, also came with a sizeable increase in FO% and AS. Bringing depth to camp and picking the best possible option for the 19-man gameday roster was likely the best offseason decision for the Redwoods’ upcoming 2021 season.

So based on the data, we can see a correlation between faceoff success and offensive production, but their correlation with a team's success in the win column is still dependent on the strength of a team's defense. In the case of the Redwoods, who statistically have one of the strongest defenses in the PLL, the addition of strong faceoff options like Ierlan and Charlie Leonard should help them increase their offensive production and eventually correlate to wins. Their biggest rival, the Whipsnakes, are a prime example of a team that has dominated at the stripe and on defense, and found success in the past two seasons. On the flipside, teams like the Cannons and Atlas, both of which will feature defensive units with new pieces, will need their defenses to perform at a high level before seeing the benefits of their faceoff units.

Looking forward to the first matchup of the 2021 season, the Cannons' three FO men in Drew Simoneau, Tommy Kelly and Brendan Fowler (currently on the injured list), collectively have won only 46% of their draws during their time in the PLL, giving the Redwoods arguably their best first matchup to test their FO group. Assuming the Redwoods’ defensive unit continues its success, this first matchup will be a great case study for the effect that the faceoff will have on their offensive performance.

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