2nd Evaluation of Oxford Mathematical Model during the Knockouts

We are into the business end of the sporting event, FIFA 2022. As we have been doing for last couple of weeks, let us evaluate the Oxfor MAthematical Model. Even though the much anticipated semi-finals are yet to be kicked off, we can do the full evaluation. It is because, even now we know that the oxford predication for the final wont be a correct, as Brazil and belgium are out of the competition. 

Let us analysis the stage wise accuracy rates. 

Problem with this accuracy calculation is that the error is propagated. Since Oxford predicted that the Belgium will feature in the final in which they were out of the competition from the first round, that is reflected at every stage. 

Would you accept this model with just over 50% of accuracy. That means it is just over the ad-hoc  probability prediction. As we have been insisting, predicting the results outcome of a sport event, is not yet successful, it least for the moment. 

Evaluation of Oxford Mathematical Model after First Round

We have been discussing the FIFA results prediction that was developed by Oxford University. Since the first round is completed, we can now do a model evaluation with the actual data vs. predicted data. Oxford mathematical model has two components, predicting the teams for the next round and the teams' position at each group. 

As we saw in FIFA 2022, there were many surprises. While Japan, Australia, Morocco, and South Korea advanced to the next round, we saw Belgium (The number 2 ranked team), four times champions, and Germany out of the world cup in the first round. 

Following is the final 16s.

Out of the Oxford predictions for the next round, 9 out of 16 are correct, which is 65% of accuracy. Let us look at the group-wise rankings. Out of the 32 positions, only 11 were correct, meaning the accuracy is less than 35%. 

When the group-wise analysis was made. All Group F position predictions were wrong, while there are no groups that all positions are correct. 

When the position analysis was made, there were a few notable observations.

We can see a higher accuracy for positions 1 and 4. That means it is easy to predict the best and poorest teams. This is not again a hard part. However, their model could be better when predicting the number 2 and 3 positions. In fact, the number 3 position prediction accuracy is 9%. 

Sport is all about fractions, inches, and moments. That is where the prediction of results is not difficult but impossible. If it is possible, it is not a sport.