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There are some things in life that should never be left entirely to guesswork.
Cashflow. Forecasting. Month-end. Whether someone has “just one quick finance question” that definitely will not be quick. And, most importantly, whether England are finally going to bring football home.
As a 27-year-old aspiring accountant, Tottenham Hotspur fan and proud Yorkshireman, I like to think I know a thing or two about numbers, patience and misplaced optimism.
Supporting Spurs has prepared me well for predictive analytics. You learn very quickly that historical performance, emotional resilience and blind hope do not always point in the same direction. You also learn that the phrase “this could be our year” is not, technically, a reliable forecasting method.
So, with the World Cup approaching, I have decided to put my football opinions, finance brain and emotional baggage to good use.
How We’re Using PiPredict for World Cup Predictions?
Alongside Persis, our Brazilian Presales Consultant, I will be using PiPredict to analyse the World Cup and see whether data can help us predict what might happen. Persis brings technical expertise, Brazilian football heritage and the quiet confidence of someone whose country has won it five times. I bring spreadsheets, Yorkshire realism and the lived experience of watching Spurs turn promising situations into character-building exercises.
It feels balanced.
Over the coming weeks, we will be sharing how we are preparing the dashboards, choosing the data, shaping the predictions and getting ready for the tournament. We will show some of the thinking behind the build, what we are choosing to measure, and how PiPredict helps turn football data into something useful, visual and, hopefully, less emotionally damaging.
The idea is simple. We will use PiPredict to look at the data behind team performance, form, goals, defensive records, attacking threat and other useful indicators to see what patterns emerge. Rather than relying on punditry, pub chat or someone saying “I’ve got a feeling about this one”, we want to see what the numbers actually suggest.
Although, to be clear, if the numbers suggest England are going out early, I will be asking Persis to check the model again.
Why Football Is a Brilliant Test for Predictive Analytics?
Football is not always logical. That is what makes it brilliant and, frankly, painful. A model can highlight trends, risks and likely outcomes, but it cannot fully prepare for a last-minute winner, a dodgy VAR decision, or England facing penalties while the entire country collectively forgets how to breathe.
That is why this is such a good test for predictive analytics.
PiPredict is not about pretending we can know the future. It is about giving us a better view of what could happen, why it might happen and which factors are worth watching. In business, that might mean forecasting demand, identifying customers at risk, spotting operational issues or understanding where action is needed before it is too late.
In football, it means asking important questions like:
- Can England actually do it?
- Will Brazil cruise through while Persis pretends to be humble?
- Can I remain objective if a Spurs player starts?
- Is there a dashboard powerful enough to explain England’s penalty record?
Once the tournament begins, we will be sharing dashboards so people can follow the predictions, challenge the analysis and see how the model performs as the games unfold. We will track where the data gets it right, where football makes a mockery of everyone, and whether my Yorkshire pragmatism survives beyond the group stage.
The dashboards will be available for others to view because analytics should be shared, questioned and explored. Also, if England do finally win it, I will need documented evidence that I believed all along.
Behind the football banter, there is a serious point. Data is at its best when it helps people understand what is happening, spot patterns and make better decisions. The World Cup gives us a brilliant way to show that predictive analytics does not have to feel dry, complicated or locked away in a technical team. It can be visual, useful, engaging and, in this case, highly likely to cause office arguments.
So, whether you are backing England, Brazil, or just hoping for goals, drama and a decent office sweepstake, Persis and I will be using PiPredict to follow the action.
My hopes are simple.
For England: progress, composure, no nonsense at the back, and absolutely no penalties.
For Brazil: a respectable tournament, ideally without Persis becoming unbearable.
For Panintelligence: a great way to show how predictive analytics can turn complex data into something people can actually use and enjoy.
For me: proof that finance people can forecast more than revenue.
Over the coming weeks, watch this space as we build the dashboards, test the predictions and get ready for the tournament.
Let the data decide. Unless the data says England are doomed. In which case, as any good accountant would, I will be reviewing the assumptions.
