Here’s How Ai Will Change the World of Sports!
The movie Moneyball, among many things, can be considered as the prime example of data-driven performance optimization in sports. For those who haven’t watched the movie or read the book it is based on, it depicts the story of how the Oakland Athletics’ general manager, Billy Beane, used statistical data and analytics to build a competitive team despite the team’s small budget. His team, which was assembled by analyzing individual statistics of players, data mainly acquired free, went on to have an unexpectedly prolific season and reached unprecedented heights. During the historic season of 2002, the Oakland Athletics competed with and held their own against the best teams in Major League Baseball (MLB), whose budgets far outweighed their own. The team’s achievements — the most remarkable being their famous 20-game winning streak — showed how a data-driven approach can, to a great extent, compensate for a lack of resources and enhance performance by enabling effective decision-making.
Now, more than a decade and a half after the events of Moneyballthe world of sports has evolved by leaps. It has increasingly incorporated different forms of technology, the most significant being the use of big data for sports analytics. Now, with the introduction of artificial intelligence in sports, we are witnessing another wave of change from the way games are played to the way they are experienced by fans across the world.
There are few things in the world that cannot be quantified. E everything that can be quantified, can be predicted with precision using data analytics and artificial intelligence. The world of sports is abundant in such quantifiable elements, making it ideal for the use of artificial intelligence. The applications of artificial intelligence in sports have become a common sight in recent years. Considering the positive impact they’ve brought about through their growing capabilities, they will continue to make inroads into the realm of sports. Following are a few areas in sports where artificial intelligence is set to become a mainstay component:
Although humans are far from being evaluable using objective, quantitative metrics, their performances can definitely be subject to quantitative scrutiny. Sports teams, be it baseball, soccer or any other game, are increasingly using players’ individual performance data as a measure of fit and potential. However, the performance data used for scouting potential recruits doesn’t mean just using the openly known stats like home runs, goals, or passes, but using more complex metrics that take into account multiple factors. However, the perceptual limitations of humans can keep them from accurately recording and assessing these metrics. With the entry of big data and artificial intelligence in sports management, the process of recording and measuring these indicators of future success is becoming easier and more reliable.
AI can use historical data, which in sports is well documented, to predict the future potential of players before investing in them. It can also be used to estimate players’ market values to make the right offers while acquiring new talent.
Like mentioned above, using general metrics such as runs scored passes made, goals scored, etc. isn’t the best way to accurately assess performances, both individual and collective. To gauge performances in any sport, analysts and coaches need to analyze a multitude of datapoints pertaining to individual players and collective performances. This helps them to identify the areas where players excel and those where they lag. epending on the role of the individual players on a team, the metrics to assess their contribution varies. For instance in soccer, the key performance indicators of forwards or offensive players are different from those of midfielders (creative players) and defenders (defensive players).
