Sport Analytics: The Pipe Dream

imagesThis has been a big week for sport analytics on various websites. I read numerous articles praising and dissecting the new age sport analytics thinking. So what is sport analytics? Well the short of it is taking everything about the game, the players, the outcomes, the plays, and putting them into a spreadsheet to analyze in order to put together a better team. Professional teams are buying into this new line of thinking and hiring statistical analysts to crunch these numbers and turn players into assets, free-agency into risk management, and winning seasons into capitalizing market shares. To me, however, this emphasis on sports analytics is just a pipe dream.

Let me first say this, yes analytics can be helpful. They will tell you a hitter or pitcher’s tendencies, they can show where a player’s favorite position on the court is to shoot, you can see how a player fatigues throughout the game. The St. Louis Cardinals did a great job of rebuilding their minor league farm system based on these approaches used to draft pitchers and hitters. The original team that brought sport analytics to the forefront, the Oakland A’s, have made the postseason eight times since embracing the Money Ball thinking. The Spurs changed their team identity to better compete with the changing NBA game.

But if you are hoping to base your entire organization on sport analytics in hopes to win a championship, I simply say you are wrong. The A’s despite all of their continued success during the Money Ball era have NEVER made it to the World Series. (I  wrote about it in 2013 “The Myth of Moneyball“) And in fact the A’s reversed paths last year and went all in, still failing to win a title. The Cardinals meanwhile who built up their farm system through these analytical strategies, did win one title in 2011 thanks to those drafts. However other than draftee Allen Craigs’ incredible heroics that fall the Cardinals were a championship team that was guided not by analytics but by one of the sports all-time greats (Albert Pujols) and the postseason performance of a lifetime (David Freese). Same with the Spurs who were led by one of the most fundamentally sound big men in NBA history, Tim Duncan.

Most recently there have been numerous articles talking about analytics making their mark in the NBA. The prime example being the Philadelphia 76’ers current experiment. The 76’ers handed the keys of their franchise to Sam Hinkie two years ago, going 19-63  his first year and 12-41 this year. They have the league’s smallest payroll and have routinely traded away their best players for draft picks. The draft picks they have used far have been on injured players, whose stock fell because of concerns, and on European players yet to suit up in the NBA. The 76’ers covet draft picks, and in fact could have four top 20 picks in this year’s draft.

That may seem like a great position to be in but given the fact that the NBA draft is not a sure thing, it is a risky move. Hinkie himself said “We will not bat a thousand on every single draft pick.” Yet this is his strategy. He is putting all of his hopes in selecting a player that will hit it big. He feels that having more picks gives him a better chance at landing that player, and it does. But he is simply foregoing any type of progress now for a chance at winning in the future. As far as his analytics actually on the court, well he emphasizes length and athletic ability because you can’t teach that. In a recent story on the 76’ers the reporter in reference to the team’s lineup said “These Sixers are conspicuously long-limbed, and with the remarkable exception of forward Robert Covington, approximately none of them can shoot.” To me being able to shoot the basketball is an important trait in the game. But Hinkie runs his team like a day-trader, looking at numbers and upside while collecting stocks and hoping to hit it big.

As I mentioned analytics can be useful. It helps to show trends. It can help track  a player’s fatigue. Analytics should be used to help improve players performance or a teams efficiency but when you focus an entire organization’s system on something other than on the field or the game, instead focusing on just the numbers to build a championship team; I think that is a pipe dream.

The A’s analytics helped them build a consistently competitive team, one built to win during the 162 game season. But in the playoffs it is often players who have extraordinary performances that lead their teams to titles. The 76’ers are collecting draft picks but a team with one pick could hit the lottery next year while the 76’ers go broke. I saw an interesting conversation in one of these analytical articles between a traditional scout and an analyst. The analyst was talking about his system he developed to grade and predict a player’s performance. He was touting Jonny Flynn as a good defender because of his steal rate. The scout noted that the rate was increased because of the Syracuse defensive system he played in. The analyst saw the numbers, the scout saw the big picture.

To me sport analytics is a tool, not a mindset. As with anything I feel one needs to look at the whole picture. Sport analytics can provide some really neat graphics to show but in the end sports is more than just what you see in numbers and graphics, its about what’s inside the player. That is what makes the all-time greats. They aren’t always the most physically dominate player, they are the player that does the most with what they have and rise to the occasion. So while some of you may go to your charts and numbers, I will stick with my eye-test and go with my gut.

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