Can a mathematical model predict FIFA?
An English analyst named Joachim Klement from Liberum Capital had “accurately” predicted the winners of 2014 & 2018 FIFA World Cup. In 2022 too, he has built out an economic model for the outcome of this year’s nail biting World Cup.
The prediction is that Messi’s dream would come true & Argentina would lift this year’s Cup.!!
But what has it to do with me and LinkedIn?
As Management Consultant / Investment Bankers, Financial models are our bread and butter. And more often than not, a significant portion of our conversations with Founders and VCs revolves around the same. And to be honest it’s just fun to talk numbers!
But the fact it is all boils down to a few variables or assumptions so to say. Taking the FIFA example again, Klement had considered the 4 factors for his model: climate, population size, GDP/capita & culture.
In business models, these levers or assumptions form the central core of the further build up. Getting these right thus becomes extremely important. To make things extremely basic, these two are the sales funnel and pricing strategy.
Assuming out of the world sales enquiries or 100% conversion is just downright crazy in most situations.!
One more important aspect that studies show is that complex predictive models having multiple variables & hypothesis may not be as accurate as compared to their simpler versions.
According to us, the sweet spot is max. 3-4 key input variables. The advantage it brings it is easy to comprehend for most people and simpler to undertake simulations for enhanced decision making Unless, obviously it is an operational model, where the objective might be something else altogether.
Coming back to Klement’s FIFA model, the economic model did throw out India, China & Netherlands, which he pre-emptively labelled as outliers.
While it was all hubris in the end, it just model making is more of an art than an exact science!