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Sports Intelligence - The Role of Technology in Professional Sports

Sports Intelligence - The Role of Technology in Professional Sports

The role of analytics in professional sports

In advance of the current European Soccer Championship, there was a controversial debate about the role of technology in professional sports ­– especially regarding the use of goal-line technology that helps the referee to decide if a goal was an actual goal. Despite many doubts, the “Hawk Eye” goal-line technology is now in use and already has proved itself in some tricky situations. This discussion was somehow surprising, since technology is already ubiquitous in the modern sports and there has always been a strong connection between professional sports and the idea of data analytics.

However, in the past most analytics happened intuitively (e.g. in the brain of the coach) and were usually based on rather general empirical data, like winning/losing a match or the subjective feeling about the performance of an athlete. With the rise of information technology, there are new possibilities to collect and process data in sports. Coaches can now make decisions based on tons of detailed data. Furthermore, there are a lot of technologies and algorithms that help them to make sense of the data.

One game changer in this context is the Internet of Things where information technology becomes ubiquitous. Wearable technologies that enable a continuous monitoring of vital data (or other KPIs that are essential for professional athletes) have gained a lot of attention recently. Wearables not only refer to well-known fitness wristbands popular in private use, such as the FitBit [1], but rather to smart clothing with accurate (and invisible) sensors [2].

In the context of professional sports, not only vital data of the athletes are relevant, but also environmental data. It is therefore not surprising that all other physical objects (e.g., bats, gloves, balls or even the floor) are increasingly enriched with sensors that collect data and provide insights to players, coaches, fans and regulators.

Figure 1 shows a framework that illustrates various perspectives on analytical applications in the context of professional sports.

  • Operational analytics

The operational use of analytics is probably the most obvious application in professional sports. Gathering more data during training and competitions enables athletes and coaches to optimize training programs. With real-time performance data, for instance, a coach can monitor the health and performance of his or her athletes and can adjust training programs accordingly. In the last years, smart sport utilities, such as smart bats or balls that analyze player technique (e.g. swing angle, strength) and give instant feedback [3, 4, 5], became a big market. These tools help athletes to bring their technique to perfection.

  • Strategic analytics

Despite operational uses, analytics can also be of use in the strategic area. If you’ve seen the movie “Moneyball”, you know that mathematical methods can help a team to identify the right players to acquire. Data Scientists analyze the collected data of a team to identify weaknesses and then screen the available athletes with matching skillsets.

This shift to more data-centric decisions also holds new business opportunities. College teams can for instance sell their collected player information to talent scouts that then can choose on a mathematical basis which teams to visit and which players to investigate closer.

  • Regulation

The new analytics technology is not only useful for athletes and teams, but also for leagues, referees or regulators. Exact tracking via “Hawk Eye” type technology (see above) can help referees make right decisions. If you push this idea to the limit, one can imagine that in perhaps 15 years there are no human referees and matches are supervised by autonomous machines.

In relation to this, sensors and smart objects can also be used to identify cheating and doping in sports. Smart Chemical Sensors could for instance enable a real-time doping control, which would eliminate manipulation during today’s doping control processes or fraud inside doping labs. Besides that, monitoring of vital data could also increase safety and help to prevent injuries or serious overexertion of athletes [6].

When talking about safety, the security in stadiums is also a big topic. There is a lot of research about “Real Time Crowd Tracking” that monitor crowds and identifies possible threats. Current approaches are mostly based on video feeds or cellphone data.

  • Fan insights & experience

Another interesting and more commercial application are fan insights. The main goal here is to identify what fans want and how a team or league can transform that into revenue. The methods here are very similar to classical customer intelligence. Sentiment analyses can help teams mine social media networks to discover what fans think or identify potential candidates for season-tickets.

Another important aspect here is customer experience: New technology enables a real-time interaction with fans. This might allow TV hosts and merchandising manager to react to the mood of the audience to deliver a better experience and have the right articles in the stores. Despite of security matters, additional sensors in seats and Crowd Tracking (see above) can also help to improve fan experience. After a match the stadium manager can see at which position how many people are leaving the stadium and can control visitor streams by motivating people to stay a few minutes longer (e.g. with showing highlights on certain screens or intelligent couponing, like free parking if you stay 10 minutes longer or get a beer at half price) [7].

Figure 1. A classification of analytical application in sports

This article shows that analytics is becoming an integral part of sports. We will probably see many developments in this sector in the near future. However, there are also concerns that too much technology will ruin the competition and thrill of sport, but this is a philosophical topic for another discussion.

Further reading

[1] Fitbit wristband:

[2] More about Smart Clothing:

[3] 94Fifty Sensor Basketball:

[4] Zepp Smart sport utilities for Baseball, Golf, Tennis and Softball: 

[5] Blast: A sensor for many sportive uses

[6] NFL taps big data to study concussions, but major game changes far off

[7] SAP Live Stadium Experience:

Julian Ereth

Julian Ereth is a researcher and practitioner in the field of business intelligence and data analytics.

In his role as researcher he focuses on new approaches in the area of big...

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