Another Way to Present Tempo-Free Lacrosse Statistics

I have always been a casual college lacrosse fan, never watching the sport until Memorial Day weekend, but it always intrigued me. This year, I found myself watching some more regular season games than I ever had and heading into the national tournament, wanted to learn more about the sport.

I've been a follower of Sabermetric stats in baseball for around five years now, and have done some writing for other SBN blogs like Beyond the Boxscore and the Tigers-centric SBN blog Bless You Boys giving my advanced-stat slant on things (and have done some tempo-free basketball fanposts over at Michigan State's SBN blog, The Only Colors). So, I'm a complete numbers geek who tends to learn more about a sport through the data mining.

In wanting to learn more about college lacrosse I went on the hunt for advanced statistics -- I knew enough that a per-possession-based stat would tell me more than a per-game rate for obvious reasons that HoyaSuxa has explained numerous times on here. As of a couple weeks ago, I started estimating possessions and tempo-free data before stumbling upon HoyaSuxa's work and now I'm hooked.

All of that was a long way to just say a couple things: 1) I am relatively new to the sport, but have a semi-decent understanding of strategy and most rules and 2) I love to toy around with statistics.

One thing that baseball doesn't lack is the ways in which you can present data. I like to apply a particular method from baseball into basketball and now I'm going to do it with lacrosse.

The problem I had reading HoyaSuxa's posts is that I didn't have proper context. Sure, I knew that Cornell had a great Efficiency Margin, but how much better than average was it? Sure, Maryland played a slow-down game, but how much slower than the D1 average were they? The raw data doesn't help me a lot, so I want to use a method from baseball that I like to call the "Plus Stats."

An example of a Plus Stat is OPS+. What it does is puts the league mean at 100 and every point above or below 100 is a 1% difference from the average (in theory; some things like ERA+ at Baseball Reference aren't calculated correctly so that a 1% change is 101 on this scale, but mine are). So an 80 would be 20% lower than average and 120 would be 20% higher. This helps me get a better grasp of the particular statistic I'm looking at because it gives me context.

A cool 430+ words in and I'm ready to get to the data. Here's a few random statistics -- some I've seen used on College Crosse and some that I haven't -- in Plus Stat form -- for the 2011 season.

Face Off Percentage

Yale, VMI, HObart and Hopkins all dominated on the draws this year. Unfortunately, that doesn't guarantee success given that VMI, Hobart, Hartford, and Bryant all had negative efficiency margins this year.

Ground Ball Percentage

GB% is simply ground balls gathered divided by total ground balls. Here, Maryland shows one of their signs of dominance in the tempo-free battle. Maryland grabbed more available grounders than any other team in the country (marginally, ahead of Bryant who shows, once again, that grabbing GB's doesn't come with success).

Turnover Percentage

Here, you don't want to turn the ball over so a lower number is better. Maryland grabs the most ground balls in the country and when they had the ball they didn't give it away at all. They were 32% better than the national average.

Possession Percentage

Add up Maryland's good face off ranking (seventh best), their penchant for getting ground balls (first), and how well they take care of the ball (least turnovers per offensive possession in the nation) and it's easy to see why Maryland possessed the ball 58% of the available possessions in their games. I have data for both 2010 and 2011 and Maryland was still far-and-away the best in this category with Hopkins and Yale both right behind them. Fourth place was the 2010 North Carolina Tar Heels.

Now, the caveats here are that none of my values are adjusted for a strength of schedule like the numbers generally presented around these parts are. That's the reason I haven't presented the offensive or defensive efficiency data. In the raw data, Robert Morris had an Offensive Efficiency of 38.0 which becomes a 135 Off Eff+. Surely, though, they were benefiting from playing in the Northeast Conference.

Questions or suggestions?