How can you evaluate the accuracy of your soccer score prediction model? What are some common metrics used for this purpose?

Evaluating the accuracy of a soccer score prediction model is an essential step in determining its effectiveness. There are several common metrics that can be used to evaluate the accuracy of a soccer score prediction model. One of the most commonly used metrics is mean absolute error (MAE). This metric calculates the average difference between the predicted score and the actual score. The lower the MAE, the more accurate the model is. MAE is useful because it provides an absolute measure of error and is easy to interpret. Another commonly used metric is mean squared error (MSE). This metric calculates the average squared difference between the predicted score and the actual score. Like MAE, the lower the MSE, the more accurate the model is. However, MSE can be....