Predicting Football Match Results with Data Mining Techniques O. I. Aladesote, O. Agbelusi & M. Ganiyu Abstract- Data mining techniques are very effective and useful for forecasting in many domains or fields. In this research, prediction of Spanish la liga football match outcomes is carried out using various data mining techniques (Multilayer Perception, Decision Tables, Random Forest, Reptree and Meta. Bagging) to determine the most accurate among these techniques. The experimental results is done with Weka 3.9, shows that all the techniques performed well in terms of accuracy but multilayer Perception was the most successful with an average accuracy of 100%.. I. INTRODUCTION Football is a fast growing sport that is taking over as one the most viewed and richest sport therefore the drive to be more than just a spectator has led to this research of being able to predict the final outcome of any match and simultaneously making sport betting easier. One of the reasons for football being the most popular sport in the planet is its unpredictability. Every day, fans around the world argue over which team is going to win the next game or the next competition. Many of these fans also put their money where their mouths are, by betting large sums on their predictions. Due to the large amount of factors that can affect the result of a football match, it is incredibly difficult to correctly predict its probabilities. With the increasing growth of the amount of money invested in sports betting markets, it is important to verify how far data mining techniques can bring value to this area [9]. To solve this problem we propose building data-driven solutions designed through a data mining process. Data mining is an aspect of computing that is used for extraction of hidden information and to automate the detection of relevant patterns in a database. The data mining process allows us to build models that can give us predictions according to the data that is fed into the system. The study is aimed at using data mining techniques for the prediction of football match result. Every sport has particular rules, number of players, different styles, that is, a set of different features. For a beginner, carrying out predictive model from the scratch with considerable dataset could be somehow challenging. Finally, every individual especially football fans would be able to predict match result based on identified factor at the end of this research. We summarized the contributions of this paper as follows: • Forecasting of la liga football match outcome using data of five previous seasons • Comparative analysis to determine the most accurate technique. The remainder of the paper is organized as follows: section 2 presents the literature review. In Section 3, the method used to generate the results is presented. The experimental results for each data mining technique is presented and discussed in section 4. Comparative analysis is done in section 5 and finally, conclusion and future work are presented in section 6. International Journal of Computer Science and Information Security (IJCSIS), Vol. 18, No. 6, June 2020 46 https://sites.google.com/site/ijcsis/ ISSN 1947-5500