Recently, I came across an article on The Register discussing the simulated fight in the movie Rocky Balboa. Simulation was used to figure out if the current heavy weight champion Mason Dixon could defeat former champion Rocky Balboa. The outcome of the simulation was a win for Rocky via KO. When the two fighters finally meet at the end of the movie, Dixon wins countering the computer’s prediction although I have to admit that the simulation was about a young Balboa fighting and not the arthritis plagued 60-year old Rocky that entered the ring for his last fight.
Even though the events I just described are fictional, it got me thinking about the potential for intelligent software to predict the outcome of sporting events. I know that people who like to bet on sports would love to have software that can always make the correct predictions.
Although it is next to impossible to correctly model all the variables in a sporting event, current statistical approaches widely used in artificial intelligence can be utilized to analyze past results in order to make educated predictions about future events. Predicting the outcome of a boxing event choosing at random one has a 50% chance of guessing correctly. If an intelligent software agent considers the past history of the fighters including any previous meetings between the two, then it can improve its chances of guessing correctly. However, it can never be 100% certain because no matter how much past data are available, it could never account for all possible variables that can be relevant to the outcome. For example, one of the fighters might become sick the day before the fight and can’t get out of fighting because of pressure from his sponsors.
That said, researchers have used intelligent software to predict the outcome of real sporting events such as the winner of the Super Bowl and the FIFA World Cup. Last summer, Imran Fanaswala and Yashar Fasihnia from the American University in Sharjah collected data going back 20 years and using their FIFA Intelligence (FIFI) software, they predicted that Brazil and Italy would meet in the final of the 2006 FIFA World Cup with Brazil prevailing in the end. Their prediction was wrong since France and Italy were the last two teams with Italy taking the Cup home. Even though their final prediction was incorrect, they did manage to guess one of the two teams in the final game correctly.
Most recently, Electronics Arts (EA) run a software simulation of last Sunday’s Super Bowl game between the Colts and the Bears. They predicted that the Colts would win and they were correct. Although I bet this was more of a publicity stunt for EA than a demonstration of the state-of-the-art in artificial intelligence, it shows that educated predictions of sporting events based on statistical data are possible but not bullet proof. I say this because the same software failed to predict the winner of the Super Bowl last year.
In the future, as we develop algorithms that can discover patterns in large amounts of historical data then we will be able to improve our ability to correctly predict the outcome of sporting events. However, one cannot expect that any future artificial intelligence program will be able to correctly predict the outcome of such events every time.