Our model ranks each of the 32 participating teams on each of these six categories, giving a total score for each one. Within each category each of the measures listed above are weighted differently based on how important we think they are in determining a team’s overall score in each category.



This is where you, the reader, comes in. To generate the winner of the tournament each category is given a weighting - from one to five - depending on how important you think it is when it comes to determining a World Cup champion.



These weightings are applied to the six categories, generating a final score for each team. Whichever team has the highest score in a match will win.



For example, if Germany has the best score for manager pedigree, and you give the manager pedigree category the highest weighting score of five, then it is quite likely that Germany will win the World Cup on this simulation.



If you can’t get your team winning in your simulation, try adding more weighting to the category that represents its biggest strength as per the table below. If you want France to win, for instance, you’d be best off giving player pedigree a higher weighting. If all else fails, bump up random luck to the maximum and hope.