This is probably one of the greatest months of the year for sports fans, with the World Cup, NBA Finals (which reached a regrettable conclusion June 17) and Stanley Cup finals all at more or less the same time. Major League Baseball is also going on too, of course. All this means that it’s also a great time to think about analytics in sports. It’s well known, of course, that some sports have become more analytical. But what’s not so clear is where the analytical focus is for particular sports and teams. A quick review may be useful.
Major League Baseball: This is the king of analytics in sports, largely because there is so much individual performance data. We can also thank Bill James, the god of Sabermetricians (baseball statisticians) for creating lots of great new performance algorithms for the sport. The primary targets are:
1. Player performance analysis and selection—Oakland pioneered this—Moneyball (http://www.amazon.com/Moneyball-Art-Winning-Unfair-Game/dp/0393057658 )and all that—but the Red Sox probably lead now; they go back to NCAA college records to identify bargain players
2. Game strategy (e.g., simulations)—again, Red Sox probably lead, but even the Yankees do it now—see Joe Girardi interview here (http://hbr.org/web/2010/06/girardi)
3. Injury analysis—I believe the Dodgers are the leaders here
4. Fan loyalty analysis—This is just getting started—not sure who is best at it
National Football League: This sport is probably second in its use of analytics. The primary targets are:
1. Player performance analysis and selection—the Patriots are probably in the lead here
2. Game strategy—again, Bill Belichick and the Patriots are probably best at using analytics to choose plays
3. Fan satisfaction analysis—again, I think the Patriots take the lead here I will leave it to you to speculate on why the Patriots didn’t win the Super Bowl last year with so much analytical focus, but they did win three times in the last decade.
NBA Basketball: Coming on strong, but modeling performance is tougher since it’s a group effort and the play is more dynamic. Targets consist of:
1. Player performance analysis and selection: I’d go with the Houston Rockets as the leader here, with their general manager Daryl Morey—see this great article (http://www.nytimes.com/2009/02/15/magazine/15Battier-t.html?pagewanted=all) by Michael Lewis
2. Injury analysis: I have heard there is some of this, but I’m not sure who’s best at it
European Football (aka soccer):European teams seem to be the only ones with a strong analytical bent. The primary targets are:
1. Injury analysis: AC Milan’s “MilanLab” is the leader here; see video here (http://www.microsoft.com/video/en/us/details/2ac51e6a-ccb0-4996-acbf-47b0f9a00682)
2. Play analysis: Not sure if this is used by coaches or just fans, but analysis of who kicks to whom seems to be growing; see this blog post by Bruno Aziza (http://blogs.technet.com/b/microsoft_blog/archive/2010/06/10/improving-football-with-analytics.aspx)
3. Player selection: the English manager Sam Allardyce supposedly did this analytically for Bolton and then Newcastle United, but now he’s inactive
4. Fan loyalty—again, supposedly Allardyce did this at Bolton
Cricket: I don’t know much about cricket, but the late coach of the Pakistan team, Bob Woolmer, is reputed to be the analytical innovator of the sport.
NHL Hockey: If there are any analytics in this sport at all, I have yet to hear about them.
If you know of anything I’ve missed, by all means let me know!