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Analysis and Prediction of Football Statistics using Data Mining Techniques
Author(s) -
Anurag Gangal,
Abhishek Talnikar,
Aneesh Dalvi,
Vidya Zope,
Aadesh Kulkarni
Publication year - 2015
Publication title -
international journal of computer applications
Language(s) - English
Resource type - Journals
ISSN - 0975-8887
DOI - 10.5120/ijca2015907263
Subject(s) - computer science , football , data science , data mining , statistics , mathematics , history , archaeology
To solve the problem of loss of interest in Fantasy Football over the season, a game-changing strategy was thought of which led to the creation of this idea. Powered by an exhaustive dataset of all football statistics from 1992 i.e. the start of the Premier League era, it seemed exciting to allow the use of Data Mining techniques to forecast future statistics. A points system based on the success of predictions (explained later in detail), which in turn allow buying/auctioning better players adds a greater interactive feeling to the existing FPL system. This would prevent the churning of players of the season, since they would be attracted to getting more points and better players through such predictions.

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