When Data Helps Predict a Result and When It Can’t

Predictions run off data, and though predictions are just educated guesses, the data helps build context around a specific decision. Some games produce enough data to make somewhat accurate predictions; however, there are outcomes that cannot be predicted and are completely random. Knowing which is which is the first thing any prediction has to get right.

Where Data Earns Its Place

Football is an excellent sport to make predictions on because there are millions of points of data circulating online. Opta’s expected goal model alone is trained on nearly one million shots, weighing more than 20 variables for each one, including distance, angle, goalkeeper position, pressure from defenders, shot type, and more.

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That's why the daily football predictions on our site use these types of numbers. They are updated, accurate, and can give us valuable insights into different possibilities. Using this data helps build context behind our predictions.

Any popular live sport, in fact, has a good enough database to be used to predict outcomes. Cricket predictions, for example, can be made using data like run rates, wickets in hand, and the history of similar chases.

Why It Stops Short of Certainty

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Predictions aren’t 100% accurate; they’re just a bit better than guesses. A guess is a random choice; a prediction, on the other hand, uses data to back up that guess, which can increase its accuracy slightly. The main thing is the quality of the data and the experience of the predictor. Good predictions come from professionals using updated, real-time data.

The reason it never reaches certainty is that data describes what has happened, not what will happen. An xG figure may tell you that a shot from a specific position goes in one out of ten times; however, it doesn't tell you whether this specific shot is the one that will happen next.

Outcomes Data Cannot Predict

Some outcomes are completely random by design, and no data can be used to predict a possible outcome, regardless of the data collected or math used.

Cup draws, for example, can’t be predicted. The FA Cup fourth round draw gives each tie a numbered ball, one to 32, and the balls in the pot carry no form. Because of this, it's impossible to develop a model that suggests who gets drawn first, last, or against which team.

A coin toss is another. It's commonly used in tennis games to decide who serves first. It’s a 50/50 chance, and nothing more can be added to that.

Slingo games UK players find on casino sites are, again, random. Games like Slingo Starburst or Slingo The Godfather use random number generators (RNG) which are verified by third-party testing laboratories like eCOGRA to ensure they’re completely random for players and operators.

How to Tell the Two Apart

The main telltale sign is whether past events change future ones. A loss on a game using an RNG doesn’t tell you whether the next result will be favorable. A striker on top form who’s scored three hat-tricks in the last three games tells us that they’re playing well at the moment and we can expect them to score in the next match.

Still, whatever data we have, the prediction is random, to some extent. Past data doesn’t guarantee us future results. It does, however, enable us to paint a picture of what may happen, which is another way to turn a guess into an educated guess, and that could put the odds in our favor ever so slightly.