Srikanth
Cricket and technology work simultaneously. Technology helps in tracking things like- ball speed, camera in the stump, third umpiring, and many more. And now this has got a new face. In this article, we will focus on IPL and the usage of analytics in it.
Automated Sports Journalism
AI-driven platforms have been designed that can facilitate in translating hard data into narratives using simple language. Multiple smart cameras can now detect on-pitch hits, misses, boundaries, scores, centuries, etc., and can relay the information directly to the network, without any intermediary to collate information.
Broadcasting and Artificial Intelligence Targeted advertisement
On a mission to revolutionize the world of sports for coaches and players, AI also has a beautiful impact on the pattern the audience experiences sports. AI systems can be utilized for automatically choosing the right camera angle to display on viewers’/ audience’s screens. They provide subtitles for live events in different languages based on the location of the viewer, and also enable broadcasters to utilize monetization opportunities through advertisements. Traditionally advertisements that flashed were globally published ads by the network that is relaying. However, targeted & localized ads are now being highlighted on the field side banners by overlapping the original ads.
Augmented Coaching and Data-Driven Analysis
On a continuous basis, AI has a significant impact on the strategic decisions created by coaches before, during, and after the game. With the help of wearable sensors and high-speed cameras, AI can detect things like a forward pass, a penalty kick, LBW in cricket, and a lot of similar actions while sporting. This data empowers coaches to prepare players for better competition. This data-driven analysis involves players with quantitative and qualitative variables that ultimately helps coaches to develop better training programs for their teams.
Improvement in the performance of Player
To enhance the performance of players an AI system can be used on the contrary. Some applications use computer vision and machine learning to assess basketball players’ skills, giving them a good medium of improvement. The recording of these performance metrics of an athlete is not only credible but also helps the players to understand the specific set of areas where they have maximum potential to excel and the areas that still need some sort of improvement.
AI in Match Predictions
Machine learning can be used to forecast the match results. Either it is the game of soccer, or cricket, where massive data is present. A model for releasing the outcome can be created to predict the upcoming confrontations. One of the best practical applications of the prediction can be conveyed by the student made projects at Great Learning on ‘IPL Cricket Match Outcome Prediction using AI Techniques.’
Chatbots
Sports teams are using virtual assistants to give a response to fan-based queries across a wide range of topics including game information, team information, team stats, etc.
Computer Vision
Researchers are training deep learning neural networks to predict things that are beyond human abilities. For instance, optimized player’s performance, analyze and give instant input reports in things like batting technique, stance, and shot selection.
