The best sport tech companies taking advantage of Artificial Intelligence

The innovative infographic tool, — called Market Map — once again sheds light and clarity on a specific market: Sports Tech.

The infographic visualises the market of AI-based startups from all over the world operating in the Sports Tech sector. But let’s start by defining this relatively new term, SportTech, which has recently risen to prominence. It is a new area that arises from the encounter between sport and technology. In other words, all the technology aimed at finding solutions for sport is part of Sports Tech. It ranges from innovation in the field of Athlete Performance to new ways of Fan Engagement and the digitisation of clubs and federations business processes, as we will discuss deeper in the following paragraphs.

Our focus is certainly on a particular technology that Sports Tech relies on, Artificial Intelligence. So, let’s see how AI is used in Sports!

Preview of the Sports Analytics Lumascape Tool

Sports Analytics

Everyone should have seen at least once in their life, one of the most beloved cinematic cult classics of all time: Moneyball. The film is about how Oakland Athletics General Manager, Billy Beane (played by Brad Pitt), strapped with a minimal budget, built a competitive team relying on sabermetrics, a form of sports analytics, for player evaluation and making decisions.

The success of analytics-based decision-making in baseball was soon noted by other professional sports leagues and today it is widely adopted in other sports as well. According to estimates, 1,012 is the number of startups globally in Digital Sport, which offer digital solutions to monitor athletic performance, optimize event management, analyze and improve the involvement and experience of fans, and innovate club business processes.

But let’s take a step back and then clarify what is meant by Sports Analytics.

Sports Analytics is a collection of relevant, historical, statistics that can inform players, coaches, and other staff in order to facilitate decision-making both during and prior to sporting events.

There are two main areas of sports analytics — on-field and off-field analytics.

• on-field analytics deals with improving the on-field performance of teams and players (game tactics and scoring, athletes performance, players training, and fitness)
• Off-field analytics, instead, is applied to the business side of sports to increase ticket and merchandise sales, improve fan engagement, offer highlights of matches and digital content through both social media and operating platforms.
• alongside these ones, another distinct area of sports analytics use is sports gambling, but we do not treat it.

Now that we have mapped out a general framework about Sports Analytics, let’s move to the two main sectors that result from the pair of opposites on-field / off-field and in the different subcategories that Lumascape presents.

Download all Sport Tech Map data Get all the data (including website, mission statements, etc.) related to this Market Map here.

Activity & Performance

As mentioned, this category is closely related to the on-field activity, so that means two moments of analysis: during the matches and in training. It is also the most popular category, in fact, almost one in two digital sports startups (49%) operates in Athletic Performance, offering solutions to measure performance, prevent injuries and monitor the training and rehabilitation of the athletes.

Wearable & Equipment Tech

Through smart wearable systems equipped with sophisticated sensors, it is possible to monitor the player’s health and collect data about the performance in real-time. These are the technological solutions that some startups have successfully implemented. Innovative and comfortable designs characterize these devices, worn as clothing or an accessory, record health and fitness data during sports activities, and usually send them to a mobile app or a display, where you can see all the information in the blink of an eye. They typically track multiple metrics like blood pressure, speed, heart rate, calories burned, distance, etc. Wearable devices, such as smart shin guards, “intelligent” Sweat Band, and Smart Yoga Pants to name a few, are starting to gain popularity as consumers can now quantify their results on a daily basis. The benefits of wearable are both for those who train alone as a cyclist, or an amateur swimmer, and for the coach of an entire volleyball team for example.

Athletic Performance Tracking & Coaching

If it is not possible to make an entire football team wear tracking systems with GPS and other sensors, there is another way to mathematically analyze performance, it is Video Analysis. Cameras track the ball & player movements, generating huge volumes of data stocked in data-prep platforms able to deliver analysis and insights that truly support the coach’s and club’s decision-making process, or helps player agencies to scout new talents. Also, it can confirm a player’s objective value when buying players between clubs. Some startups have their own customized cameras among their offerings, which is certainly an advantage in terms of system compatibility and functionality for the use case, or rather the sport in question. Lastly, a much less used source of data for these sports analysis platforms is that of tabular data.

Fans & Content

It is probably the most known and exposed part of the Sports Tech ecosystem to the general public: this section is in fact about Fan Engagement, so how to entertain fans and build a long-term relationship with the aim of converting them into fans.

Fan Experiences & Social/Media Platforms

This category contains all those usefulI instruments to connect fans with teams and athletes, but also with other fans. We can find chatbots, ticketing, merchandise solutions, which are based on sentiment analysis and historical data analysis.
Another widely used technology is video analysis and motion tracking systems. which in addition to offering data on the performance of athletes, can enhance the fan experience. It is the case of the platform subscription formula, that though watchers micropayments, automatically provide highlights of matches, replays, and commentary. This happens thanks to Machine Learning technology being able to identify the best in a match, capturing the main events, and offering them to fans, without the need to see all the game. Also, Augmented reality is used slightly less to allow stadium visitors to see live match information and player statistics.

E-sport — Gaming

The last category which includes end-to-end content solutions for sports leagues that leverages computer vision and deep learning is about monetization platforms that feature gamification elements. Some fan platforms enable viewers to play along during live broadcasts, archive, and on-demand content (quizzes, predictions, challenges…). Alternatively, these platforms and mobile apps offer personal performance analytics for competitive gamers and e-sports.

Conclusion

In conclusion, the trend that emerges from the analysis of the sector is that AI and Machine Learning are increasingly requested by fans for a satisfying sports experience and by clubs and federations for a more objective and detailed analysis of their players. This shows that there is a profitable market for organizations willing to invest in “connected” stadiums and events.