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.
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