We used to think that sports were about skill, talent, and physical prowess. We still do, to a degree. However, it turns out that the stereotypical nerds from the comedies were right, you can calculate anything. Data science has influenced the world of sports and we get to see how.
Marketing and PR
A team or athlete is just a part of the whole business enterprise we find in sports. There are sponsorships, venues, brand building, and other ways to appeal to the fans of the game and keep them engaged.
Data science gives us a way to handle the way socio-economic factors influence buying tickets, the likelihood of betting on sports, and to calculate the prudence of the next investment. We can also use it to determine what steps need to be taken in order for the company to maintain its image, especially in the face of adversity. Different demographics, social media engagement, and keywords in marketing campaigns are the key elements in climbing to the top and staying there.
The Machine’s Advice
Old-school businesspersons sometimes rely on their gut for the biggest decisions. On occasion, this works out fine, but other times not so much. A proper processing of data can lead to some pretty interesting and useful pieces of advice, like which player to sign on, which one to let go, how much money needs to be invested into a player to make them stay, and what the best course of action should be while the athlete or a team of players are out there on the field.
Imagine a chess game, for a second. If you are playing against a machine that has gone through all the variables, even the experienced players are at a serious disadvantage. Only true professionals can take the machine on. It is a situation akin to what many sports teams and clubs will experience soon in terms of strategy. Data science can identify everyone’s strengths and weaknesses, and come up with the best possible strategy.
Why Bother, Then?
Don’t worry, the spirit of the sport remains intact, it is just the tempo of the game that has changed. There are still many factors that data science cannot account for, especially if the athletes are hiding something, or some important data gets overlooked.
For example, it is difficult to imagine a computer factoring in fear, stage fright, pressure, or the morale of an underdog on a roll. Data science is, in fact, science, but it shows what is likely to happen, not what is definitely going to happen. Still, major players and companies are going to have to prepare to use this new tool at their disposal quickly and efficiently, before their competitors do.