To be a winning team with a competitive edge, many sports teams are taking the moneyball approach: by using data analytics. It’s not just about goal scoring, but about how often they touch the ball, how fast they run, strengths, weaknesses: an overall score of each player and what other players in the team can do to bring the best out of each other.
This lens permeates all competitive sports from baseball, basketball, hockey, and of course the beautiful game: football. It's analysis that has been going on for years but is now growing with intensity.
Earlier this year, in the ever-increasing battle to gain an edge, Manchester City teamed with a former Hedge Funder to lead the AI Insights team at parent company City Football Group. According to reports, former Winton Capital Management staffer Laurie Shaw will focus on building machine-based models to better manage player fatigue, injury and illness, as well as player identification, recruitment and individual development, pre and post-match analysis and recruitment of coaches.
These days, every move is scrutinised both on and off the pitch, diets, sleep patterns and exercise plans are poured over to ensure each player is at their peak, both physically and mentally. Expected Goals (xG), Successful Dribbles, Pressure Regains, Chances Created, Progressive Passes... it’s all data collected. All of this can be turned into numbers, numbers which can then be evaluated, weighed, measured, analysed and turned into information that will develop the players and propel the sport forwards.
The wild times of footballers dressed to the nines in double denim, attending all-night parties, being papped on the way home and then struggling onto the pitch the next morning are long gone in this era of continual analysis and dissection.
Man City isn’t the only UK based football club heavily invested in data science. Liverpool’s 2020 league title - their first in 30 years - is heavily credited to investment in this space. But with their new acquisition, bookies are hailing Man City to be victorious this year.
But it’s not only the clubs with money utilising data, take Championship team Brentford: a small club currently punching far above their weight and close to being promoted to the Premier League this season. Using huge amounts of data analytics they buy unknown but promising players - much like Billy Beane - then when the time is right, they sell these players for large sums. Their strategy, a twist on the standard Moneyball approach, means the club is sustainable with the transfer of players and managers.
At Upside, we’ve taken this analytical approach to traditionally unmeasurable things too, but rather than speed or fatigue, we’re measuring investment ideas. Our analytics help investors to develop their skills through feedback - we show why ideas succeed and fail, and when they’re just a lucky stab in the dark.
The focus is on the skill levels in the different disciplines of investing - whether you’re an emerging player or a seasoned pro, an analyst or a portfolio manager. We look at luck versus judgement, repeatability and show users ways they can improve. We do this by breaking down the ideas into everything that has gone into them.
With the backdrop of the ever-changing markets, investing is finally catching up. There’s a science to kicking a ball, and a science to being right.