1st March 2017 by | Data

Sports analytics – the game changer

Sports analytics

In today’s thriving technological world, how can sporting individuals and teams harness technology to succeed in their respective fields? We know that sporting success is determined by results, so it is vital to be fully prepared to compete with as much knowledge of the opposition as possible. Sports analytics offers one way to achieve a deeper understanding of how to gain an advantage against the competition.

The use of analytics in sports has become more prevalent in recent years, with various methods of capturing the relevant data available. Data driven decision making has become something of a must have, as the value of higher positions and trophies results in better reputations and more importantly, more financial reward.

Let’s start with a quick summary of the main method of capturing this data, Radio-Frequency Identification (RFID) tags, which originated with the military in World War 2. In comparison to the military RFID tags, today’s equivalent are much smaller and barely noticeable – meaning there is no effect on the individual who wears the tag. RFID tags provide numerous data-sets and real-time analysis for analysts to manipulate, such as accelerometers to track the acceleration of a moving body in real-time.

So, once the data is collected, how is it turned into actionable information and utilised? Take Leicester City Football Club, who achieved the seemingly impossible by winning the Premier League with a 5000/1 chance. One, arguably underrated, reason for their remarkable success is that the team harnessed the power of sports analytics.

The club’s first team performance analyst Peter Clark commented on how LCFC turned their collected data into actionable information for the team’s manager to act upon:

If a player is losing individual battles and aerial duels, we can help provide the evidence for the manager. Or if the opposition’s chances are being created from similar situations, we can bring that to the manager’s attention as well.

(you can read the full article here, if you’re interested)

Football was one of the first sports to see the value of Sports Analytics, however now a plethora of others have realised the value of the emerging technologies that can enhance their game. The American football National Football League (NFL) partnered with Zebra Technologies to find the best analytics option for them, with the method of placing RFID tags into the player’s shoulder pads being deemed the most appropriate.

Twenty-two sensors are placed around the respective stadium that can locate a player to within six inches and the RFID and sensors combination allow statistics to be collected such as speed, distance and acceleration. This data then provides team management with actionable information that was not previously accessible. However, as this data is fresh, there is limited historic data for comparison, which means that it can take months to provide any meaningful information.

As sports analytics continues to develop, one sport and league in particular has excelled – basketball and the NBA. The NBA sees the importance of keeping any data that is collected open to the public to draw their own conclusions, and the American Sports broadcasting company ESPN has a whole section dedicated to the analytical side of the sport on the ESPN site.

In summary, here are my main points. Firstly – that sports analytics is important because it provides sporting teams and individuals with actionable information to gain a competitive advantage, as Dr. Ben Alamar, Director of Sports Analytics ESPN states.

As data-sets grow larger in sports, teams and leagues have increasingly recognized the value that analytics can play in creating a competitive advantage.

And secondly, that presenting fans and viewers with raw facts and figures is an important side of sports analytics that is often overlooked, as Jeff Bennet, VP, Stats & Analytics at ESPN, sums up.

Sports Analytics is not about finding an interesting number through rigorous analysis and modeling. It is about communicating the complex as simply as possible in the language sports fans can understand.

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