Assessing Team’s Back ‘4’ for Predicting Match Draw

Abstract

Many researches have tried to predict soccer outcomes using
different methods such as supervised learning and unsupervised
learning approaches. Many factors and features have been used to
carry out this prediction. However, none so far has predicted the
outcome of match results with emphasis and information on critical
position of play in the entire team. Most teams lose by a slim margin,
and this is vivid in the fact that 81.57% of matches have a goal
difference per match that is less than two goals. This research
critically considered the back '4' of teams, and was able to predict
whether the match will be won, lost or end in stalemate with much
emphasis on deadlock. Support Vector Machine was used to predict
the result of matches using only the back '4' information of the team.
The result was evaluated by predicting the whole of 2018/2019
season of the English Premier League. The prediction results give a
76.8% accuracy and error rate of 0.23.