Predicting The Outcome of Sports Competitions Using Poisson Distribution

Sports are either fast or slow, soccer and hockey fall into the fast category. When watching sports that are fast, people tend to be more intrigued and want to guess who will win, lose, or even draw. What if there was a way to make that guess into a proper guess? This paper will explore the Poisson distribution method and demonstrate how its predictive model can be used to prove that it is the most accurate formula for predicting MLS (Major League Soccer) and NHL (National Hockey League) matches involves estimating the probability of different outcomes for each team based on their historical performance and other relevant factors. The key parts being taken into deliberation are the home and away form while including the attack and defense strengths and scoring patterns (goals scored and goals conceded) in past matches, of the 29 teams in the MLS, and the 32 teams in the NHL. The probabilities are used to accurately show how the Poisson distribution is the most accurate compared to other formulas. Comparing the linear model, a very basic predictive analysis model, to the Poisson distribution method, a simple and effective model, predicts more accurately and can show more scenarios. Poisson distribution is a valid formula for predicting soccer and hockey matches since it meets the criteria for the formula’s variables, whereas linear models have more uncertainties in producing results for its variables. This research should maintain the Poisson distribution as the best method for predicting soccer and hockey match results.