Crunching fantasy football numbers to become big business
Big data firms looking to help fans of fantasy football as Premier League launches ‘pay to play’ model
Romelu Lukaku (right) during his loan spell from Chelsea to West Bromwich Albion’s last season
It’s not often that several million people will be concerned over whether Chelsea’s Romelu Lukaku starts a match against Hull City.
However, as the first week of the Premier League season arrives – and with it the dawn of a new fantasy football year – Lukaku’s relatively low fantasy league price (£8 million), married to having a “double game week” due to a midweek fixture with Aston Villa, means many will agonise over whether he will usurp the misfiring Fernando Torres at centre forward.
Fantasy sports is a “billion dollar industry” in the US thanks to more than two decades of fantasy baseball, NFL and NBA games, with this side of the world slowly catching up on the idea.
New England-based Soccermetrics chief executive, Howard Hamilton, says the decision by the official Premier League fantasy game to launch a “pay to play” format this season means a number of data analytics companies may now see fantasy football leagues as a “viable route to make money”.
Soccermetrics itself specialises in creating algorithms and software to build products such as “player prospect reports” where data is collected on player performance from leagues around the world in order to judge the current and potential worth of each player, with Premier League clubs among its clients.
“We view fantasy sports as a testing ground for some of the algorithms and approaches we want to implement,” says Stanford graduate Hamilton. To create a predictive model which helps fantasy players’ view how their team will perform over a season is difficult though, he adds, due to a lack of access to the “right data”.
Founder of Wisconsin- based fantasy sports data company Rotowire, Peter Schoenke, says that “access to proprietary data is the issue” when it comes to creating a fantasy football version of the predictive analytical tools now commonplace in finance and other areas of business.
“Premier League clubs don’t usually release that data,” adds Schoenke, who notes that while American sports teams previously viewed sharing player information as being part of “a type of open-source project” they too have now become more secretive as the “power of analytics” has grown.
So without a piece of software to help you judge your best team, what’s the best way to go about spending an imaginary £100 million on 15 players for your fantasy squad?
“Believe it or not there’s a science to [fantasy football] rather than just a bunch of people sitting around a table in a pub arguing about how much Gareth Barry is worth,” says Jon Trigg, MD with Silent Manager.
A UK group which has spent a decade building fantasy leagues across 14 sports for newspapers and major brands, the science employed by Silent Manager begins with predicting final league table positions and dividing the league into five tiers from Champions League certainties to relegation fodder.
“There’s a probability in a team’s performance and that influences each player’s rating,” says Trigg.