X Factor: Dissecting Data for an Edge


In the twenty-first century of sports, knowledge is power. Athletes have always been on a quest to get bigger, faster and stronger than they were. However, the rapid rise of machine learning, complex statistics, materials science, and biomechanics have driven the modern athlete to new heights and generated a new support industry for sports. Collecting and understanding the data produced by an athlete in practice and when the game is live is the X-Factor that defines modern sports.

In college football, the premier teams in the country are spending millions of dollars on analysts—Alabama and Clemson combined to spend over $6 million, more than those teams spend on their offensive and defensive coordinators combined. The massive budgets of the powerhouses are leading the charge, but local schools are starting to catch up, employing analysts and assistants who store and analyze data on every snap. Utah football has graduate assistants meticulously film and track data from every practice and game, evaluating the results of play types, route structures and other information against the defenses they go up against. Over the course of the season, this data allows Utah’s coaches to call the most likely play that will give the offense the greatest probability of success.

In the NBA, multiple cameras are installed in every arena, tracking the movement of the ball and all ten players on the court. With an expert analyst, this data provides crucial insights into how coaches space their players on the floor and who they send out to fight for points. Every shot, every post up, every pick-and-roll is tracked and entered into massive databases. The truth is that there’s so much data for the NBA that the analysts haven’t discovered how to use it all yet. They burn the midnight oil, searching for the most minute edge to give to their team.

Our state is the home of many Olympic training facilities, and here too, science has become an invaluable asset to teams looking to secure the gold. Space age materials technology have created ultra-aerodynamic ‘flight suits’ that lend massive advantages to swimmers, downhill skiers, cyclists, and anyone who must contend with wind resistance. Olympic skiers spend hours in wind tunnels, honing the precise contours of their tuck until they have perfectly minimized the drag of the air, squeezing every last bit of speed they can from the mountain.

The science of biomechanics has advanced to track motions down to the millimeter. They do so, by using laser webs, light refraction, and suits with dozens of tiny motion-sensing computers to evaluate every motion for inefficiency. These track anything from a PGA pro’s golf swing, to a quarterback’s throwing motion, and everything in between. The University of Oregon Athletic Department has been at the cutting edge of this technology. Trainers there have learned to focus on an athlete’s symmetry, which is a variable the athlete can focus on maintaining and that imparts greater speed and power to each motion.

Wasted effort means you are a hair smaller, a bit slower or a fraction weaker than your opponent. The stakes in sports are so high and the opponents so well equipped and trained that even the tiniest fraction can mean the difference between the thrill of victory and the sting of defeat. The University of Oregon used these techniques to train Olympic hurdler Devon Allen.

Athletes are training with data, too. They track every mile run, weight lifted and calorie eaten. They carefully monitor them, seeking to pinpoint and avoid the moment when a seasonaltering injury becomes a likelihood. When their numbers start to dip, they recognize that they are struggling and give themselves a break. This confidence in avoiding injury allows athletes to push themselves to their absolute limits and maximize the results from each hour of training.

As the quantity of data has grown, so has the challenge of analyzing it. Data analysts continually seek new ways to sort through massive datasets, discovering the variables that share two traits—they must translate to results on the field and they must be within the control of the coaches and athletes who are trying to win. When the data threads that needle is when the athlete can make the crucial change—finding the perfect way to follow through off the tee, tucking the elbows out of the way of the roaring wind, or hitting just the right spot on the court as your opponent enters a pick and roll. That can mean the difference between victory and defeat.

Winning has always been about talent, but as data science has improved, it’s become clear that the best way to maximize your talent is to maximize your understanding of what allows you to excel.