For baseball fans, particularly baseball fans in the Oakland area of northern California, the name Billy Beane is a special one. Immortalized by a hit book, a motion picture feature, and a string of American League titles, Beane will go down in history as one of the Oakland Athletics’ most prestigious managers.
His approach went against the grain. There was no heart-on-the-sleeve-caution-to-the-wind mentality from Beane, only a commitment to data and a dogged faith in the dividends it could provide. Beane ran the Athletics like a business, assembling an incredible machine from the finest cogs and components on the market and actively searching out assets which he knew to be undervalued. The data told him what to do and it was seldom wrong.
Love or loathe Billy Beane’s pragmatism, the results can’t be argued with. That Beane and his team were able to balance financial stability with competitive performances on the field (and impressive league standings to boot) will be the envy of many a club owner. The fact that he did all this with data just makes him all the more dear to our hearts. So, what’s next for analytics in sport? How is data science driving success in the competitions we all love?
At its core, any sporting competition is a physical activity. There is movement, there are collisions, there are jumps and falls, and there is a heck of a lot of wear and just as much tear. However, at its highest level, sporting competition is also big business. It figures that major sports clubs would want to keep their best players fit, healthy, and in the field for longer.
This is where data collection measures like those developed by BlackBox Biometrics come into play. Already being trialed in the NFL, this piece of hardware compiles and stores information from tackles and collisions to help coaches better understand where changes need to be made to training regimes and to safety equipment. Similar developments are also undergoing testing in the NFL, as well as in the English soccer Premier League, showing just how important such analytics could be to the future of sports.
Shaving Vital Milliseconds and Millimeters
It’s rare that sporting contests, particularly the big ones, are won and lost by margins you could drive an oil tanker through. This is because great teams and athletes have a habit of cancelling each other out. With the exception of Usain Bolt’s semi-superhuman exploits, 100m Olympic finals generally come down to a final, desperate dip on the line. The difference between a World Series-winning catch and an embarrassing fumble is only a fraction of a centimeter.
This is why incremental improvements – improvements so minimal that they would seem almost futile in everyday life – are make or break in sports. This is why sporting clubs and organizations are willing to invest big bucks into making this happen.
So, don’t be surprised when these organizations invest increasingly large sums in analytics. Everything from the angle of take-off employed by a hurdler when he meets that first obstacle, to the position of a basketball player’s fingers on the ball when she makes a lay-up, can and will be analyzed. And, if minuscule progress can be made, year upon year, it will be deemed a success.
Marketing to the Fans
People say professional sports are becoming more and more about business. However, there are aspects of sports which have always been, and always will be, purely business. Here we are talking about the marketing of the brand, the selling of merchandise, and the expansion of the global profile of a sports club or event.
Analytics is already well and truly deployed here. Everything from identifying target markets to launching and updating products and offers requires a profound level of commercial understanding. This, of course, can only be achieved with data.
Sealing the Deal
You are the manager of a sporting club. You want to win titles. To do this you need to attract the best players. You have your eye on a particular player but you have a rival in the market. You offer an attractive signing on fee and wage packet. Your opponent matches it. You go back to your bosses but they won’t budge. The money is already on the table. What do you do?
The answer is simple; you show the player why joining your camp is the best option. To do this, you go beyond the financial gain. You show him analysis of training facilities and the results they can achieve in terms of injury prevention. You show him your track record of growth, stability and expansion. You show fan interest and attendance reports – basically, you supply him with the data he needs to make a decision. Compiling comprehensive analytics just sealed you the deal.
Real Time Decision Making
Billy Beane showed us how analytics can be used to craft a winning side and to deploy that side in the field, but coaching is about more than this. The coach’s job is not put on hold while his or her players do the dirty work on/in the pitch/court/diamond/pool/track etc etc. There will come a time when the coach needs to make a big decision in the game.
Increasingly, coaches are turning to analytic methods to support these decisions. These methods can utilize existing datasets – such as substitute impact data or empirical data regarding the efficacy of different formations against different types of oppositions – or they can use data acquired in real time, either through wearable technology or through recording and observing data points at different stages of the action. Making major decisions during a game is becoming less about gut feelings and sporting intuition and more about concrete, statistically-justifiable data. A coach still needs to know the game and to know his or her team, but this knowledge needs to be bolstered by demonstrable analytic insight.
This is Moneyball 2.0. Essentially, an arms race in which sporting institutions from a range of different disciplines aim to outflank each other in terms of understanding and insight. Billy Beane might have kickstarted this approach but we are still to witness just how far it can go.