Bashing forecasts and forecasting seems to be in vogue lately. Not only have recent years seen a number of political upsets, but the current World Cup has seen similarly notable
surprises (and not just England winning a penalty shootout).

But is the criticism of forecasting fair? Should we junk them and bring back Paul the Octopus, whose football “predictions” brought him global fame as some kind of marine oracle?

Or is the real problem with the way forecasts are being interpreted? To answer that, we need to think about what a forecast or a prediction is. Essentially, it’s an assessment of the likelihood of an outcome (or outcomes) at some point in the future. And how those estimates are communicated and reported can have a big impact on how they are perceived.

Sometimes this can be harmless fun – one need only think back to Paul the Octopus, whose football “predictions” brought him global fame as some kind of marine oracle.

Quite often the outcomes will not be binary. To take the World Cup as an example, ahead of the quarter finals, there are eight possible outcomes for the tournament victor, corresponding to the eight remaining teams. Suppose a model gives World Cup win probabilities for each team of Brazil 25 per cent, France 20 per cent, and so on.

In this case, Brazil is favourite because 25 per cent is the highest probability. But if there’s a 25 per cent chance of something happening, there’s a 75 per cent chance of it not happening.
This means, perhaps counterintuitively, that Brazil are favourites to win the World Cup and also that Brazil probably will not win the World Cup. The two statements are not contradictory – where no team has a greater than even probability of victory, the favourite is really the least unlikely.