Data and AI in Sport

Data and AI in Sport, Data, Data and AI in Sport
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by John Gale

The increased use of data and AI in sports has led to controversy of VAR in football, and has been the subject of much debate in recent times, however many athletes across all sports – and officials, have used artificial intelligence (AI) to improve their performance, in a number of different ways.

With sports science and wearables like Fitbit abounding in the sports market, AI is beginning to play a key role in allowing these devices to provide a ‘quantified self’ – useful statistics derived from performance measurements that allow athletes to improve their training, and therefore their performance.

Improving form and the use
of wearables

Often athletes will need a coach to give them direction on how to improve their form, and to spot mistakes and inefficiencies while watching a game. Coaches typically set targets and goals by making judgements based on what they can see. Wearables can provide insightful data on previously undetectable metrics to coaches, through readings – such as heart rate and movement.

Wearables contain electronic sensors, such as accelerometers or gyroscopes, which provide continuous movement information that shows variations when different events occur. For example, a wrist-worn device will read different movement patterns for a forehand shot in tennis, compared with a backhand equivalent.

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AI as a mediator in sport

If technology is a reformer, then Artificial Intelligence is a mediator. Not everything in the world can be quantified, and if there is something that can be quantified can be predicted with precision through data analytics and AI. The world of sports has abundant and quantifiable results that made it perfect for the application of Artificial Intelligence.

The integration of Artificial Intelligence in the sports domain

This has become a common sight in the past few years. And considering all the opportunities and positive impact it has brought through its capabilities, it will continue to encroach into the realm of the sports domain.

Real time assistance

Companies use AI technologies such as predictive analytics to forecast the result of world cup tournaments. For instance, in cricket, enhanced techniques are used to track the bowling speed and the proximity of the ball getting in contact with the bat. The data is transferred and is accumulated from the tool incorporated in the used materials like metrics. The parameters of the speed of the ball, a graph showing delivery dimensions are displayed.

AI Applications in Sports: Scouting and Recruitment

Sports teams are nowadays using the individual data of the player to identify his potential. It includes not only his runs, goals, or passes, but also more complex metrics that teams take into consideration. However, humans are confined to record this big data accurately.

Big data and AI increase in Sports

AI in sports has managed the entry of this big data and has promised a successful future because this procedure of recording and measuring the metrics has become very easy and more reliable. AI has the ability to store large current and historical data on the basis of which the future can be predicted. Additionally, it can also be used to determine the market value of a player to make the right offers. 

Training and Performance Analysis

To perform well in any sports, the coaches and the sports team needs to analyse a large number of individual and collective data. This helps them to identify those areas where the player excels and where he lags. The metrics of the players varies depending upon their role in the team. The games have now become quantifiable, implying that they are now measurable. Artificial Intelligence thus co-relates qualitative and quantitative measures that predict the overall value of players. AI can also be used to identify different tactics being used by opponents with their strengths and weaknesses helping coaches to plan according to their opposition assessment.

Training & Coaching

With the emergence of new technology, the training and coaching aspects like game performance analysis, preparing the team for the competition, player health examination, etc. have also been changing rapidly. The AI sports application contains a large number of data about the training and performance of the player integrated with the information and knowledge from different coaches and different experts that will help the player to work upon his current sports techniques and make it more professional. The information and knowledge the different sports scientists possess are uploaded in AI sports applications. Then this information is used in the training and education of the athletes resulting in better performance.

Reviews: VAR and Virtual Umpires

In sports like cricket, tennis or football, DRS (decision review system) and VAR (video assistant referee) are already being used. These are based on slow-motion replays. The emergence of technology has brought advancements in cameras as they are now integrated with AI software. This technology uses computer visualisation for speed analysis, placements, ball movements, etc. This has lessened the need for the umpire in critical decision making, and the umpires can concentrate on the analysis of players on the field.

AI Assistant Coaches

The machine here will take all the crucial decisions, and the coaches will just communicate the decision and ensure its enforcement. Developers are also working on adding features like realistic human communication and added emotion to completely eliminate the need of the coach in decision communication in the near future. Using new technology can be helpful to remove a cover from strategic insights that were not previously viewed and achieved, and due to these strategic insights, a team can achieve the desired goals.

Custom Enterprise Application

Every team is working to take their game a notch higher, requiring deeper insights. The fans are becoming more demanding as they want a more personalised experience and functional connectivity. AI can channelise all these demands. AI technology is growing faster and has become an essential part of the sports industry as it improves player performances, enhances learning methods, provides the ability to win the games, manage sports operations, serves and holds the fans, generating and acting on critical insights, Identification of talents, etc. This new AI technology will provide a broad set of benefits with unexpected results and unimaginable outcomes. The sports team with AI technology will make out of the box performance absolute.

AI, Software and Machine Learning

Machine learning – an area of AI – can help. Machine learning allows software to learn from incoming readings and to identify factors that affect the measurements. This allows software to decide which events are occurring in given measurements and to get better with more data over time. For example, with tennis data, machine learning can detect similar movement patterns and group similar data together – in effect, it creates movement classifications by itself for events like serves, and shots.

AI lets us process vast amounts of statistical data with less effort than ever – and can even identify factors affecting sports performance that are impossible for us humans to detect. Although machine learning can be effective, it brings its own set of challenges.

Data and AI in Sport, Data, Data and AI in Sport

John Gale

Editor In Chief at Belu Media, manages content and editorial across the porftfolio of websites and publications.

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