Peanut butter and jelly. Peas and carrots. Forest and Jenny. Bert and Ernie. Abbot and Costello. Sports and data? Of course.
By now we all have probably heard of Billy Beane and his Moneyball. The main idea is that as GM of the tightly budgeted Oakland A’s, Beane was tasked with assembling a competitive team while contending with very tight purse strings. So what did he do? He determined a player’s potential fit on the team by examining stats like OBP (on base percentage), spray charts showing what part of the park hitters tend to hit the ball, hot zones that show what part of the strike zone the hitter uses the most for hits, and so on, processing unstructured data.
In doing this, Beane constructed teams that were always competitive, but never great. Although Beane was using stats for his own team, the use of data didn’t actually take off until the least athletic people in the world made it popular: Fantasy sports nerds.
Now before fantasy nerds get their imaginary jocks in a twist over my use of the word nerd, I’ve been playing fantasy sports for a good 20 years. In fact, my first fantasy baseball league was a scoring system devised by a man we’ll call Nino. Before Yahoo, CBS, MLB.com, and all the others had their robust systems, Nino League utilized various ratios to value certain players. Two stats immediately come to mind, WHIP and K/9. WHIP stands for Walks and Hits per Innings Pitched. This is an overall indicator of the efficacy of a pitcher, by measuring the average amount of hitters the pitcher allows to get on base per inning. So if a pitcher has a WHIP of 1.3 or lower, he’s doing ok. Anything below 1.2 is really good, and once we’re below 1.0 you’re looking at a real stud.
K’s per 9 is a ratio that takes the amount of strikeouts a pitcher has, divides it by the amount of innings pitched, and multiplies that figure by nine. Basically, the higher the K’s per nine, the better.
Not only is this data used for figuring out fantasy points, but these days, owners want to see what’s happening to their teams in real-time. This means that robust systems are using technologies like Hadoop to take real time stats and display them so fantasy managers can see exactly what is happening to their team the moment it happens.
But stats are just for nerds anymore. The real league has picked up on it as well. Now teams have real time heat zones so they can relay to their pitchers the best way to avoid a hitter’s sweet spot and what pitch to throw and where to get him to swing and miss. Want to see how a team will respond to you putting a lefty on the mound? Just do some sorting and filtering to see only the games in which they faced a lefty, bust out those handy heat zones and spray charts, and you have a pretty decent idea of what the game plan should look like. This is not to take anything away from the athletes themselves. Games aren’t played on paper (or in cyberspace). These guys will always continue to excel in spite of the advantages afforded to their opponents. It’s called making adjustments.
Baseball isn’t the only sport to embrace big data usage. Car racing teams have been doing this for quite some time. They put sensors on their cars to measure everything from gas consumption to tire grip.
Bicyclists monitor heart rates and wheel rpm. Just to name a couple.
Heck even cricket teams use big data to measure, um, whatever it is that cricket players do.
The use of big data in sports has become so widespread that universities have departments devoted to it. Take the University of Arizona for example. They have a sports data mining section of their artificial intelligence department.
Websites like Sportstechie are devoted solely to the use of technology in sports. Companies like SAP, who aren’t sports oriented, are jumping in as well. SAP has signed a deal with the NBA so that all stats are readily available and visible to the fans. What better way to get fans involved than to have them see what exactly is going on at all times? Some people may argue that all of the data use is taking the fun out of sports, that they yearn for the days of yesteryear when people relied on gut instinct. I personally think there is a right mix of both, that will make sports more and more competitive, and as a result, more fun to watch.
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Now if you’ll excuse me, my fantasy baseball team is in the playoffs, and I have to set my roster for today’s games.
Related reading about other industries using big data: