Machine learning models can make predictions in real time based on data from numerous disparate sources, such as player performance, weather, fan sentiment, etc. Some models have shown accuracy slightly higher than domain experts. These models require a large amount of data that is comparable and well organized prior to analysis, which makes them particularly well suited to predicting the outcome of Esports matches, where large amounts of well structured data is available.
Bookmaker's interest - In order to guarantee a profit for the house, a bookie needs to create even action on both sides of a particular game. In a perfect world the bookie would have 50 percent of the handle come in on the underdog and 50 percent on the favorite. This ensures that the sports books are guaranteed a profit because of the 10 percent commission or "vigorish" charged on most sports wagers. This is why there is "movement" on the point spread. If one side on a game is being bet more heavily, the bookie must move the number in order to attract interest on the other side in order to balance action.
Total: Also called the over/under, it is a number set by the sportsbooks that proposes a number of points that will be scored in the game by both teams combined. Then, fans predict whether there will be more points or less points than the Â‘total.Â’ If you bet the under 41.5, you are hoping for a tough defensive battle with lots of running game. Pick the over, and presumably you feel this will be a high-scoring game. In short, you are predicting whether the combined total score will be more than (over) or less than (under) the total.