Read More about DataRobot in Sports Analytics
Automated Machine Learning: The Competitive Edge You Need
Professional sports is a cutthroat industry, on and off the playing field. The smallest of competitive advantages can have a significant impact, sometimes translating to the difference between a championship and failing to compete. To beat the competition, today’s sports franchises need to embrace artificial intelligence (AI) to automate and accelerate all aspects of their performance in order to:
Optimize Player Performance
Imagine knowing if a pitcher is about to throw a changeup or a slider, or if a point guard is going to shoot a three-pointer or drive to the rim when he goes left. That is the power of automated machine learning and predictive modeling. All athletes have tendencies, and those tendencies are historical data points that can be collected, analyzed, and used to predict the future. Knowing what your opponents are going to do is the best way to optimize player performance, and can be the difference between a win and a loss.
Predict — and Prevent — Injuries
Nothing derails championship aspirations like an ill-timed injury to a star player, and teams are focusing more than ever on formulating the best training and injury-prevention techniques. With wearable technology delivering extensive performance data, and more emphasis paid to sleep and diet research, automated machine learning is the next step for organizations to protect their player’s wellbeing. Predict the breaking point for individual players…and prevent them from ever getting there.
Project Prospect Improvement
The goal of most scouting departments in professional sports is to project how effective a young player will be at the next level, or how much any player is likely to improve during their career. In every sport, drafting is a notoriously inexact science, despite decades of historical draft data that are readily available. Deep within all that data are hidden gems – those underexposed players who are ready to produce at the next level. With the help of automated machine learning, scouting departments will be well positioned to find those diamonds in the rough.
Consolidate Valuable Data
Never in the history of sports has performance data been collected like it is today. But in order to identify the most important signals, analysts must first wade through a lot of noisy, less-impactful metrics. DataRobot’s automated machine learning platform consolidates all of the factors influencing performance to highlight the metrics that actually matter.
Increase Profit Potential
Automated machine learning has the power to not only impact on-field performance, but also off-field success for teams, primarily at the box office. Predicting season ticket renewal rates, attendance, or the price elasticity of certain events will help front offices at sports organizations increase and maximize their profit potential, which can then be reinvested into on-field performance.
Improve Operational Efficiency
Sports teams and huge stadiums often go hand-in-hand, and running events at these complex arenas can be an operational nightmare. Automated machine learning can drastically improve operational efficiency by predicting how the event might unfold, allowing the venue to make the right staffing and inventory decisions.