June 13 brought us the first series of Major League Quidditch, and with it an early glimpse of the potential that such an organized level of gameplay can bring. Though not perfect, we had full film of each game played by the following Tuesday, a trend that should continue, if not improve throughout the season. As a part of this, MLQ has begun the process of developing and recording a new standard for stats that plans to bring a high level of objectivity and tangibility to individual players’ skill, rather than just that of teams.

As a part of this, I’m working with developing a system of measuring stats for beaters this season. With the increase in film quality—and hopefully camera angles—a wider array of data points and metrics can be determined for beater play specifically. Using these metrics, I have broken down game two from the Intensity vs. Innovators series as a way of looking at what beater stats can swing a game, and how I plan to measure these.

The first stats are pretty standard—drives, +/- and penalties—but when compared to other stats, these can open up a realm of understanding on the flow of the game. Following the hockey method of scoring, +/- is not tracked during power plays. One of the most important and most trackable stats measured for beaters is the Turnovers Forced metric. This stat is one of the most important things to track in determining how a beater interacts with the quaffle game. Turnovers come from beats on quaffle players that are recovered by the beaters’ team, beats on receivers that are recovered by the beaters’ team and direct pressure that forces the quaffle player to make a pass that is intercepted. In game two, Indianapolis’ Alex Leitch absolutely dominated this stat, with six total Turnovers Forced. Detroit’s Jim Richert also had three crucial Turnovers Forced, and this is likely one of the reasons that he was the only Detroit beater with a positive +/- that game. A beater who can force a high amount of turnovers, yet gives away bludger control on each time does not necessarily a good beater make, however. This is where the Control Lost and Control Gained and their combined total come in handy in showing a part of how the beaters act in the beater game. Here Leitch stayed slightly positive, with 2.5 gains (a .5 is awarded when control is gained with the help of a partner), and 2 losses. It was Tyler Walker, however, who stole the show for Indianapolis in this category. His net 2.5 gains in control during the game helps to echo his dominance in the beater-on-beater game last weekend. Equally impressive were the 2.5 gains a piece for Ashley Calhoun and Lisa Lavelanet of the Innovators, though each of those players ultimately had negative +/- ratings compared to Tyler Walkers +2.86 per drive.

We’re tracking a variety of other beater stats to help give insight into the game, and I encourage you to look through them all as they develop. Most stand on their own, though my tracking of Average Beat Range, or ABR, needs a bit of an explanation. This metric assigns a value of 1 to short beats (beats within roughly two yards), a value of 2 to mid-ranged beats (roughly two to eight yards) and a value of 3 to long-range beats (anything further than eight yards). This metric compiles all attempted beats, and then averages the number to create a value between 1 and 3. The higher that number, the longer range beats, on average, a beater makes. By itself, this stat does not mean much, but when viewed with Beat Percentage, this stat can help give value to the type of beats a beater makes. For example, a beater can make close range beats all day and have a very high Beat Percentage, but this will be reflected in their ABR, yet if they’re making longer beats, and missing more of them, their Beat Percentage may drop, but their ABR will be higher as a result. Indeed this trend is already somewhat shown in the stats from game two, as players with higher Beat Percentages tend to have lower ABRs. Ultimately this stat, along with many of the other ones, should not be seen as just a tree, but as part of the forest it will come to be a part of as the season progresses. With any luck, these metrics will show valuable results in determining beater skill from what once were “intangibles” but for that to be the case, only time, and games, will tell.