![]() The study shows the extent of the capability of MLPs in finding ordered patterns in chaotic events. The study found that an MLP can predict the return of each player with an RMSE of approximately 2 points. This is then compared with the actual FPL gameweek return of the selected team and evaluated. The study uses MLPs as a means to optimise FPL team selection and thus predicts an average point return for the team through the summation of point average predictions for each player individually. This study does the same by predicting, based on multi-dimensional data, the point return of English Premier League (EPL) players in the official Fantasy Premier League forum (FPL). Any sporting event is dominated by chaos, where small changes in the environment can drastically affect the outcome. This study aims to analyse the power of Multi-Layer Perceptrons (MLPs) in predicting the outcome of sporting events, in particular, a football (soccer) game. Such environments include the prediction of economic trends and weather phenomena to the modelling of human behaviour. ![]() ![]() Most real-world uses of multi-layer perceptrons are in highly chaotic environments. With the passage of time, the ability of intelligent software in making predictions of seemingly random, chaotic events increases. Actual Multiple Monitors fills up the gaps in Windows® user interface when working with several monitors at once. ![]()
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