Sports used to be simple. In baseball, the players went out to the field and hit the ball while in soccer the strategy was X and O on a blackboard. Even poker, a game reduced to 52 cards, was just a person and his cards. But things have changed.
The rise of computers has brought a new era to sports and the world of information and data analysis has changed the way it is played.
Here are three examples of these changes:
Billy Bean and the rise of Sabermetrics
If you have seen the movie Moneyball, starring Brad Pitt, then you will have met Billy Beane. According to IMDB, this is the synopsis:
“The success of Oakland A’s CEO Billy Beane in forming a baseball team on a limited budget using computer analysis to sign his players.”
It does not seem very exciting. How do you make a movie interesting about data analysis? But it was a critical and public success.
Beane is an ex-player and manager who succeeded as a player but managing the team has changed the sport using statistical analysis. He used what is known as Sabermetrics, the empirical analysis of the game by measuring statistics during the game.
This includes the analysis of batting, throws and field plays, which reuses statistics such as Value Over the Average Player (VORP), Wins Above Replacement (WAR), and Average of Batting on the Balls in Game (Batting Average On Balls In Play, BABIP).
There is a lot of advanced math and calculus, so if it seems complicated, see the movie we’ve told you or read the book it’s based on, to see how baseball has changed.
As Beane said: “Adapt or die.”
Poker is not just an individual game
In 2008, the World Series of Poker (WSOP) began with the concept of “November Nine”. The game was stopped when the WSOP Main Event reached the final table of nine players, giving the players a hiatus of almost four months. This was done to increase the excitement among fans and the media, but it opened the door for players to change their game.
With a first prize of more than eight million dollars, the players needed to take advantage of any advantage they had. They often hired a coach to improve their game, iron out mistakes and study rivals. With hundreds of poker books, online training sites and tools like the odds calculator at your disposal, there was no time to relax.
It also meant forming a team that will help at the final table. Despite being an individual game, poker changed and players asked for help from their friends. As the November Nine was broadcast live with a delay of fifteen to thirty minutes, the players could ask their friends to watch the broadcast and in the breaks to tell them what was happening at the table and the cards of the rivals.
With so much information in their hands, the VPIP% (percentage of hands in which the player voluntarily puts chips into the pot), PFR% (percentage of times the player raises before the flop) and WTSD% (percentage of times that a player arrives at the showdown after seeing the flop) are just three of the many statistics that have appeared in poker. They only make sense for those players who use the power of data to make their decisions.
NFL teams start hiring analysts
In early 2016, the Cleveland Browns hired expert analyst Paul DePodesta, If you’ve seen Moneyball, you’ll be interested to know that Peter Brand, the character played by Jonah Hill, is based on DePodesta.
He was hired, according to Browns owner Jimmy Haslam, to have a fundamental vision in the board. This is because the team, which had been among the worst in the NFl for years, was trying to apply data analysis.
“My idea is to contribute my experience and perspective to collaborate with the team, with the intention of helping us to make more informed and adequate decisions”, said DePodesta.
It was a fairly unorthodox movement for a football team, but it is clear that they hope that the data analysis can help change the game as much as it did with baseball, especially helping in the development of players and the science of sports.
Unfortunately for the Browns, the results were not immediate and they finished last with 1 win and 15 losses in 2016, this gives them the opportunity to choose the first in the 2017 draft. We will have to wait to see their DePodesta and his team become worth, but what is certain is that they will use data analysis to make their decisions.