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With the release of the book and the movie ‘Moneyball’, data analytics in sports has caught up and is now the biggest trend in the world of sports. It was popularized by baseball and now has found its way into basketball, cricket, American football, football, tennis and many other sports too.
What is sports and data analysis?
Chelsea’s Czech goalkeeper Petr Cech dives and saves the penalty taken by Bayern Munich’s Croatian forward Ivica Olic. Data analytics had a big part to play in Cech’s choosing a direction to dive.
Sports and data analysis is heavily used by leagues in the US, but is still in its early stages of adoption worldwide. Let us try and understand what data analytics is, and then later relate it to sports.
Data analysis is a mechanism to collect and analyze data to deliver better information for effective decision-making.
Let us make it simple by taking the example of Facebook, the most used social networking website. You would have observed the ads that appear of the right side of the page. Now you must have wondered how the ads are so relevant to you, It is because of data analysis. Facebook stores most of your personal information, your age, location, sex, marital status, interest, pages you like, places you visit and so on.This information is then used for ads targeting. For example, a dating website ad is shown to people who are ‘single’ and not to people who are ‘married’ or ‘in a relationship’. Or a women’s inner-wear brand will be targeted to women and not necessarily to men or boys. The ads shown to you depend on your personal information. These examples are simple and straightforward. However, professional data analysts would try and extract richer patterns using more parameters to take decisions or to come up with valuable insights.
Data analytics in sports
Let’s try and map it to football, the most popular sport in the world. Do you remember the penalty shootout in the match between Bayern Munich and Chelsea in the Champions League final in 2012? If you are a Chelsea fan, you definitely would. Nonetheless, Petr ?ech, the Chelsea goalkeeper, dived in the correct direction every single time in the penalty shootout before finally stopping one from Ivica Olic. How do you think all this happened? Petr ?ech is a competent goalkeeper, no doubt, but part of the credit goes to data analysis. He had watched hours of penalty videos of most Munich players before the match, and the team analyst provided him with exact data of each Bayern player. Most football clubs in the world analyze their opponents from their previous matches or from training sessions; in case of penalties, the direction in which he is most likely to score, which is very helpful information. However, few players like Fernando Torres mix it up well. He scores almost equally to the left of the keeper as to his right. So, stats related to direction would not help the opponent goalkeeper as much. However, 76% of his penalties are low along the ground and not in air. And in a high-pressure match, he would use his most successful shot in all likelihood, and not experiment with less likely ones. But guess what? The opponent goalkeeper already has that information. Helpful isn’t it?
“In the future, footballers might not take free kicks trying to place it into the top corner, but pass the ball as the current success rate of scoring from outside the box during a free kick is a mere 2% or Liverpool might stop crossing the ball every single time as they used 421 open play cross to convert one in the season 2011-12, which is way too many wasted chances,” Simon Kuper, a well-known British sports journalist and author, stated at a Sports Analytics Conference earlier this year.
In cricket, stats about batsman’s high scoring areas, pressure-release shot, a bowler’s percentage of slower balls in a T20 match, stats on length, runs conceded against a left vs. right handed batsmen, and data about many other parameters can be collected, mined and provided to the coach by data analysts.
Combining this with sports bio mechanics to track player movements and physical characteristics such as heart rate to measure fitness and predict future performance of individual players takes sports to a completely different level. Player data can help the coach to take appropriate decisions in selection and strategies during matches.
Big question: Is science chosen over art?
This is the most frequently asked question asked by traditional coaches and former players who have played their game without the aid of such technology.
The answer is NO. Science is not here to kill the art of sport, but to complement it.
The science does not guarantee results in any case, but merely increases the chance to succeed, helping players and coaches to take well-informed decisions. It is important to know that this method of collecting and analyzing data in sports is not here to substitute a physical coach or a manager, but to complement the current coaching styles and take sport to next level.
It is most effective when instinct and detailed studied analysis are combined to take decisions.
Organizations and third parties
An example of data can be analysed and sorted
Such statistical data is used for in-depth match analysis, talent identification, scouting analysis and various other training programs. Most US-based sports franchises, European football clubs and IPL franchises in India are already making use of such analytics. Opta Sports has recently signed a contract with ICC and the Premier League as official data providers. Prozone Sports and SportsMechanics are some of the companies who provide video and data analysis services to various elite sporting clubs and organizations.
The Future
Technologists around the world predict that concepts such as big data (in simple terms: ability to collect and analyze the vast amounts of data) will be bigger than the internet and will impact everyone’s life. The most commonly-used phrase is “Data is the new oil”. It’s valuable; but if unrefined, it cannot really be used. Data needs be broken down and analyzed for it to have value. You might be intrigued to know how US retail giant Target used data analysis to know about pregnancy of their customer before her family knew it. Check it out.
All in all, interesting times ahead and it is only a matter of time before sports and data analytics becomes an intrinsic part of all sporting clubs and organizations across the world.
