Matthew Shaer explores how science is transforming the sport of MMA fighting — using a rather loose definition of “science”:
Greg Jackson, the single most successful trainer in the multi-billion-dollar sport of professional mixed martial arts fighting, works out of a musty old gym in Albuquerque, New Mexico, not far from the base of the Sandia Mountains. On a recent morning, the 38-year-old Jackson, who has the cauliflowered ears and bulbous nose of a career fighter, watched two of his students square off inside the chain-link walls of a blood-splattered ring called the Octagon.
Producing a notepad from his back pocket, Jackson sketched a spiderweb of circles and lines. It was a game tree, he explained — a graph game theorists use to analyze a sequence of decisions. In a traditional game tree, each circle, or node, represents the point at which a decision can be made. Each line, or edge, represents the decision itself. Game trees eventually end in a terminal node — either a tie or a win for one of the players. This game tree, Jackson told me, showed the exchange between Jones and Jordan from Jones’s perspective.
At the start, the two men stood a few feet apart. Jackson drew a circle. The node had three edges, or moves that Jackson was training Jones to use. He could execute a leg kick, or a punch, or he could shoot for a takedown (attempt to grab Jordan by the backs of his legs and drive him into the ground). But the initial node was not “optimal,” he said, because it allowed Jordan to swing freely with both fists. Although it seemed counterintuitive, the fast track to what Jackson calls the “damage” node (in this case, Jones’s advantageous position following his hard knee) was to move in close, where Jordan would not be able to fully wind up. Another circle, representing Jones’s inside position, and a series of edges, representing his potential decisions from there, appeared on the notepad.
“From inside,” Jackson said, “he can do a knee, he can do an uppercut, he can do elbows. He could have done anything there, and done it effectively.”
Since 1992, when he opened his first gym, Jackson has been using math to inform his training techniques. Unlike other MMA coaches, he continually collects data while watching live bouts, logs old fight videos to determine which moves work and when, and fills notebooks with game trees to determine the optimal nodes for various situations in a match. “I’ve always seen the ring like a lab,” he says. “I’ve tried to think rigorously, logically.”
Perhaps “analytics” would be a better term than “science”:
Among the many die-hard UFC fans was Rami Genauer, a journalist based in Washington, D.C. Genauer had read Moneyball, Michael Lewis’s best seller about Oakland Athletics general manager Billy Beane and his statistics-driven approach to player evaluation. He dreamed of analyzing mixed martial arts in the same way.
“There were no numbers,” Genauer says. “You’d try to write something, and you’d come to the place where you’d put in the numbers to back up your assertions, and there was absolutely nothing.”
In 2007 Genauer obtained a video of a recent UFC event, and using the slow-motion function on his TiVo, he broke each fight down by the number of strikes attempted, the volume of strikes landed, the type of strike (power leg versus leg jab, for instance) and the finishing move (rear naked choke versus guillotine, and so on). The process took hours, but the end result was something completely new to the sport: a comprehensive data set.
Genauer titled his data-collection project FightMetric and created a website to house the information. Some UFC fans registered their disapproval on Web forums. “‘We don’t need math with our fighting,’ people would say. I disagreed,” Genauer says.
In 2008 he managed to persuade the UFC to use FightMetric data from past matches to support a televised event in Minneapolis. “The idea was that this would be good for the producers, who could use the numbers to illustrate the story,” he says. “It’d also be good for the broadcaster — they’d have ammunition, something to rely on just like they do in other sports.”
Officials liked having Genauer’s fight data, and when the UFC began spiffing up its broadcasts with more graphics and statistics—part of an effort to make MMA seem like a real sport instead of a series of cage brawls — it hired FightMetric as its statistics provider. Genauer quit his job and opened an office in D.C.
Today FightMetric has five full-time staffers and a rotating cast of 15 specialists who collect a large data set for each fight using a video feed, proprietary software and a video-game controller with which they can record every type of strike. Among the statistics they track: each fighter’s number and type of strikes, number of significant strikes (defined as all strikes landed from a distance, as well as power strikes landed from close range) and the accuracy and location of kicks and punches.
The FightMetric team collects the strike and location statistics in real time. The UFC uses some of the data for graphics during broadcasts and on its website. FightMetric goes into even greater detail on its own website, presenting statistics over outlines of a human body. Colored lines indicate the accuracy of each type of strike, and boxes show which ground move, whether arm bar, kimura lock or triangle choke, each fighter used to try to induce a submission. The analysis is strangely disconnected from the violence of the Octagon—a savage fight broken down into simple, neat figures.