Real-time prediction algorithm and simulation of sports results based on internet of things and machine learning

Machine learning is an intelligent technology that plays an important role in classification and prediction. In the field of sports prediction, the prediction results must be processed, because many events in large-scale sports events are linked to funds. Through inquiries on the internet, more and more sports-related data can be obtained. Using these data, people continue to develop intelligent models and prediction systems, optimise and innovate these models and systems, and then more accurately predict the results of the game. Sports event prediction can capture various attributes, including team game video, game results, and player data. Different stakeholders use different methods to predict the outcome of the game. This article is mainly based on basketball technical time series statistics, using a three-layer feedforward back-propagation neural network, and adopting a rotation prediction method to predict the most important technical and statistical indicators of the team. According to the team's forecast data, the average field goal percentage is 46.03%, the 3-point field goal percentage is 37.48%, the assists are 12.95, and the backcourt rebounds are 25.4.