Big Data & Sports
Using statistics in sports in not a new thing. Team’s win rates and a basketball player’s shooting rate are for example terms that often come up in a sport-related conversation. However with the fast-growing ability of acquiring data, statistics are becoming a huge part of every single sport that is out there.
Data has become such a big part of competitive sports that it’s starting to sound crazy not having a analytics team alongside your doctors, physicist masseuses and nutritionists. With endless streams of cameras and sensors, big soccer clubs like Arsenal have recently been investing millions of dollars in analytics. Their system records on average 10 data points per second for every player on the field, or about 1.4 million data points per game. [1] But what is to do with all this data? Putting decision making and physical form analysis aside, analysts now claim to be able to prevent injuries by detecting patterns that lead to long-term injuries. [2] Keeping track of all your team’s activities like ingestion, sleeping patterns and daily habits has been proved to enormously enhance its performance. Personal data analysis is also an ever-growing subject. To improve your swing-technique, you can get tennis racquets and golf clubs that detect swing patterns and ball-contact measurements, where the equipment is connected to analysis-software.
Data analysis changes the way we look at sports but they aren’t excluded to enhancing team’s and athlete’s performances. Sports-betting has been changing drastically in the recent years. The growing computational power, alongside the ability to use big data, has made it possibly for the biggest gambling companies to offer real time services. . Those companies calculate odds and prices from both the market’s demand and all their data to provide user-acceptable odds that still ensures their stable (and big) profit. Marketing and organizing is getting easier by the minute as well. Feeding data to, for example, IBM’s “Fan Insight” should make your organizing and predictions for an event much easier.
But is Big Data ruining the nature of sports? The answer probably depends on whom you ask, but it surely is changing the nature of sports. This process really is inevitable and sport-associations are realizing that. Every month we have more and more examples of associations making rules regarding measuring devices and such more flexible. With data-collecting methods slowly but steadily growing to match our analytics abilities, sports will only become more data-dependent so we better get used to it!
[2] https://insidebigdata.com/2017/06/04/big-data-sports-going-gold/
7 comments on “Big Data & Sports”
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Pursuing further education in AI-related fields such as Neural Networks and Machine Learning.
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Hey Helgi! Thank you for this article, I am really fond of tech applications to the sports industry, and I really found your researches very interesting. Another application and usage Data in the sports industry is for all the betting business: football, equestrian etc… The more we can collect qualified data and the most sophisticated the betting system will become which also challenges the choice of deciding which type of data will be disclosed publicly or not!
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Helgi, great overview of how Big Data is used for sports. After a couple of years of hiatus from golf, I decided to take Intermediate Golf for 1 unit here at Stanford. I needed a new Driver (because my brother indefinitely borrowed my old one) and was really surprised by the fitting services nowadays offered when you buy a new club. Through a combination of at least Trackman 4 and Swing Catalyst I was able to see stats on swing speed, ball trajectory, impact etc. for every shot. This was the first time that my decision on which club to select was not dependent on what feels good, but what actually works for me. In the end I chose between two clubs that both felt good but I hit 20 meter longer on average with the other making it an easy choice in the light of statistics.
You make a great point when saying that it is crazy “not having a analytics team alongside your doctors, physicist masseuses and nutritionists.” We’re working on a telemedicine service leveraging emotion recognition for SVIA, and it has made me wonder, how can I get so much help from data when choosing a new driver, but psychiatrists only rely on their own knowledge and senses when making life altering treatment plans for people with mental health conditions.
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Hi Helgi,
Thank you for your post – I completely agree with your opinion that as time goes on sports will only become more and more data-driven. I just wanted to raise a question that is related to your last paragraph entitled ‘but is big data ruining the nature of sports?’. My personal passion for sports certainly encompasses data, because I love to analyse statistics behind matches and can spend hours trying to make predictions and observe oddities. However, this is far from a universal characteristic of sports fans. Betting companies in the UK often try to market their service by categorising their users into two – the impulse better and the thinker. It seems to be me though that there are far more people in the former category, who either follow the game casually, and therefore don’t delve into data, or simply believe that betting is about intuition and not track record. My worry stems from this: can you see a large disparity emerge between those working in the industry as they continue to inject sports with stats and the fans who simply enjoy the game in isolation? Will it ruin the nature of sports for them?
Shiv
(MS&E 238A Student)
Hi Shiv and thanks for the comment.
I’m not sure I understand what you mean by disparity emerging. Are you talking about bookmakers taking advantage of instinct-betters more because their edge grows with data availability?
Or do you mean that the typical fan really doesn’t care about statistics so he’ll be bothered with the endless stream of statistics, facts and predictions?
Hi Helgi – I mean the latter. Some fans revel in the endless data and statistics, but my concern is that the casual fan who is not will be left behind. They will find it harder to associate with the game they enjoy, because it is being reduced to numbers perhaps. Do you think sports should be worried about losing these casual fans as they increase the role of data?
Hi Shiv, I see your point.
I don’t think the corporations that profit from the fans will bother those fans with statistic so much that it’ll chase them away. It is also possible to present these statistics in a “fun” way so that’s probably the challenge for the media in my opinion. I’m more afraid of the typical athlete-thinking is drastically changing and might maybe scare some potentials away.
Helgi,
Good introduction to big data applied to sports. You briefly mentioned the different types of sensors being employed in sports. It’s incredible how quickly sports teams have adopted computer vision to capture a large amount of useful statistics and data points. In regards to machine learning, generative adversarial networks may become extremely effective at devising game strategies. For example, Real Madrid creates a virtual model of a soccer game against Barcelona based on a training set of real sports film. They employ a deep learning algorithm in order to discover the set plays that would potentially be most effective. The set plays, which theoretically have the highest chance of scoring, are used in the next match. This type of modeling could creatively devise dozens of new set plays that a coaching staff could test out. There is tons of potential in this space and it will be exciting to see how big data changes sports!
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