Choosing the wrong shape/model

The first possible error to make is to fit in the wrong shape altogether. A triangle might fit in a square if you really try hard or maybe if it’s much smaller, this still doesn’t make it a good fit.

This is equivalent to using the wrong model for the purpose. For example, while the normal distribution seems to be a good fit to goal differences, it may not is the best predictor for home team goals scored.

Errors betting models

With a multitude of potential models possible, the perfect fit may not be in use or, worse still, may not be available. The model is a necessary simplification of a real life scenario and is bound to be incorrect. Ways to diminish this is to apply judgment in selecting and interpreting a model as well as fitting the model to old data.

Going back to the shape sorting cube analogy, the correct shape might be picked but of a different size. For example, the wrong size square is being used. The errors in models can make your bet worse. This factor can make you lose bets.for more info visit at: