Common Mistakes Bookmakers Make in Modeling Esports Outcomes Revealed by DATA.BET

Posted : 05 July 2024

Esports disciplines have always posed greater challenges for modeling than traditional sports due to the complexity and frequent changes in game rules, and Counter-Strike 2 (CS2) is no exception. This complexity often results in bookmakers struggling to account for all the nuances of the game.

Accurately predicting the outcome of a game requires a multi-layered analysis, considering various factors such as team statistics and map choices. Today, Yurii Lysenko, Lead Data Scientist at DATA.BET, will highlight common mistakes made by bookmakers when setting odds for CS2 and the reasons behind these errors.

One prevalent issue is the disregard for map statistics and the impact of map selection. Bookmakers often overlook detailed map statistics or incorrectly treat the advantage of map choice as a constant across different match levels. In reality, the probability of winning on a selected map is higher in top-tier matches compared to lower-ranked ones, as professional teams make their map choices more strategically. This results in a slightly higher win probability for top-tier matches (55%) compared to lower-tier matches (54%).

Another common mistake is modeling subsequent maps independently based on the result of the first map. Although it might seem logical to model the next map autonomously, Bayesian statistics indicate that team strengths should be adjusted based on the outcome of the first map. Adjustments should be made after each won round to account for the cumulative effects, particularly when there is a significant difference in the number of rounds won.

Bookmakers also tend to neglect the team's level when adjusting team strengths after a won round. This often occurs because bookmakers lack complete confidence in their initial odds, leading them to refine their predictions during the game. However, confidence in the odds should be much higher for teams with extensive top-level match experience compared to new teams with limited data. As a result, minimal adjustments are needed for top matches, while more significant adjustments are necessary for new teams.

These mistakes can lead to incorrect predictions for the winner of the next map, particularly when one team has already won the first map, as well as inaccuracies in predicting the total number of maps played in a match. The chances of a 2-0 or 0-2 outcome increase because the team winning the first map is more likely to win the subsequent map.

Consequently, the probabilities of 2-1 or 1-2 outcomes decrease when these factors are taken into account. At DATA.BET, these issues are addressed through comprehensive map modeling techniques to provide more accurate esports betting solutions.

Common Mistakes Bookmakers Make in Modeling Esports Outcomes Revealed by DATA.BET

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