Analyzing sports data to predict outcomes is nothing new, but could artificial intelligence accurately predict winners?
Over the years, bettors have implemented various methods to try and correctly predict sporting outcomes. Because we now have more access to sports data than ever, many people have created sports betting algorithms to choose winners. However, does this software work?
What Is a Sports Betting Algorithm?
A wagering algorithm is computer software designed to try and find valuable opportunities in bets. In theory, you can use these algorithms to gain an edge over bookies. Although there have been some success stories from using this type of software to make – including the gambler who beat the horse-racing system – many agree that this software is not as accurate as the odds given by bookmakers.
Are Sports Betting Algorithms AI?
Not exactly. The word AI is more of a marketing trick: it replaced the much less popular “machine learning” and “models” buzzwords, as it sounds much more innovative and reliable.
For an algorithm to truly be AI, the program would need to be able to adapt without outside input. At the moment, all algorithms designed to get the upper hand over online sportsbooks who rely on data fields determined by the developers alone.
Sports Betting Algorithm Flaws
This type of software can analyze some contributing factors that affect sporting events but not all of them. For example, imagine a footballer stays on the field despite being injured. In this case, the algorithm wouldn’t be able to pick up on this. Also, a sports betting algorithm can’t comprehend how in-game events could affect the psychology of players.
Another major flaw is that bookies usually require starting team information before this software can. Bookmakers and sports bettors agree that knowing the lineup is a significant predictive factor in any sporting event. For this reason, sportsbooks currently have an edge on predictive sports betting software.
Using Algorithms to Predict Injuries
Top soccer clubs are already employing data scientists to prevent injuries. Ex soccer player and postdoctoral researcher at the University of Pisa Alessio Rossi collects and analyses data to predict when team members could pick up an injury.
To collect the data, players – such as those in the English Premier League – wear jerseys fitted with GPS, an accelerometer, a gyroscope, and a digital compass while they train. These sensors track their heart rate, speed, and distance covered to make sure players don’t overstrain themselves.
The effectiveness of the system is impressive: it can predict 80% of injuries. Furthermore, the system can highlight the warning signs nearly 100% of the time with specific health issues, such as certain sprains and strains.
Soon, other sportspeople could use technology like Rossi’s to train more effectively and avoid potential injuries. Also, if sports bettors had access to the information, they could make more informed wagers. However, it’s likely that sporting organizations would closely guard this data.
Learning How to Make Prediction Models with Sports Data
Although there are many scams online claiming to teach you how to make successful sports betting prediction algorithms, there seem to be more credible options out there. For instance, you can now take a course to create prediction models with sports data at the University of Michigan.
However, using AI to predict the outcomes of sporting events correctly AND GUARANTEE consistent profit against the bookmakers (who also employ AI modeling) isn’t viable just yet.