"Play or Rest" uses machine learning techniques to predict how likely a player will get injured, and how long a player will get recovered if they are currently injured, based the data set we are given. It also evaluates your training plan to see how risky the train session arrangements are for potential injuries.
Athletes, parents and coaches can use the recovery prediction, risk assessment information from "Play or Rest" to better plan the players' practice schedules and decide if they are safe to play a match, and thus prevent injuries.
Our machine learning platform is Microsoft Azure ML Studio and Web Service, which provides API service to deploy the model and analyze data in real time. We used Multiclass Neural Network algorithm for data prediction.
The challenges we encountered include too many missing data in the data set, troublesome data type .xlsx and limited time for selecting best features and develop a sophisticated machine learning model.
A potential feature for "Play or Rest" is matching the players to the best-fitting insurance based on their information.
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