Using numbers and estimates to predict outcomes can either be a hobby or a profession. This data is the fingerprint of what has happened, and if used correctly it can guide us to increase the probability of what could happen. If a profession sees a hobbyist as a way to leverage a situation, these two worlds might mingle. And when they mingle, it may influence who the winners are.
There is a Professor of Management, Economics, and Strategy at the London School of Economics named Ignacio Palacios-Huerta. He is well known to have extensive data on sports and European football in general. He is a well-published author of many journals and has written two books, Beautiful Game Theory and In 100 Years: Leading Economists Predict the Future which celebrates the utilization of data. Within his wide range of hobbies consuming data, he had a heightened interest in penalty kicks. Somewhat like Jonah Hill’s character in Moneyball, here is a person that knew how to apply data to concepts and activities to increase the probability of accuracy in the future. Chelsea F.C. thought they could use the information.
Ignacio Palacios-Huerta was asked to work for Chelsea in 2008 leading up to the Champions League final against Manchester United. He was asked to prepare some statistics if the game was to go into penalty kicks. Emphasize “if.” Chelsea had no plans to go into overtime they wanted to win in the first 90 minutes. But if the game did go into a shootout, they thought some data points could be used to their advantage. Guess what, the final time has it 1-1 and goes into extra time. Still 1-1 after extra time, it goes to a penalty shootout.
The report presented by Ignacio Palacios-Huerta was known to have rules that were written under the assumption of what should happen if rational players and decisions are made in the game. These rules were written around the concepts of K-level thinking used within Nash’s Equilibrium game theory thinking. But one of the fallacies of Nash’s Equilibrium is that not all people are rational. But the Director of Football for Chelsea F.C., a friend of Ignacio Palacios-Huerta, thought to use the data.
K-level thinking refers to a class of logic problems in which all actors are perfectly rational and possess infinite intelligence. In other words, all actors are able to reason perfectly about their situation and know that everyone else shares the same capability. - Brilliant.org
Within the data presented, two players for Manchester United had a very strong bias. First was the keeper Van der Sar showed that he goes right when facing a right-footed kicker. Then to the left when facing a left-footed kicker. The second is Christian Ronaldo who showed he was that world-class penalty kicker. However, when he shuddered going up to the ball, he tended to kick to the right of the keeper.
Chelsea trusted they knew what Van der Sar was going to do for their first two penalty kicks. First up was Michael Ballack for Chelsa, a right-footed kicker. Anticipating that Van der Sar would go right, Ballack shot left. Van der Sar went the correct way but missed the ball because Ballack shot it just a little higher than the stretched-out arms of Van der Sar. Second up for Chelsea was Juliano Belletti another right-footed kicker. Trusting the data, Belletti scored by shooting to Van der Sar’s left.
Christian Ronaldo comes up for the third penalty kick and shudders upon the approach. And as the data showed, he did shoot directly at the keeper. Chelsea stops it. Back and forth with other dramatic shots and tense moments, the fifth kick presents Chelsea with a chance to win the game.
John Terry, a right-footed kicker for Chelsea is up. The data says that Van der Sar is going to go right. On the approach, John Terry slips, Van Der Sar dives to the right as predicted and Terry kicks to the left. But because of the slip, it went wide off the pole. The sixth penalty kick comes up and both scored so on to the seventh penalty,
BleacherReport does a fantastic job explaining Nicolas Anelka’s approach and the convoluted chaos of game theory tactics for the seventh kicker. Inevitably, Anelka went against the data. He shot the ball to Van der Sar’s right, and as the data predicted, Van der Sar dove to his right. Van der Sar stopped the ball, winning the Champions League Final.
This tangible example of game theory shows that the utilization of data can increase the odds of predicting accuracy in the future. First was that it is almost inconceivable to me that Ignacio Palacios-Huerta’s data almost won the Champions League Final by connecting some data points. If Terry wouldn’t have slipped, Chelsea would of most likely been holding up the coveted European Champion Clubs' Cup and the lore would have been credited to the ingenuity of Ignacio Palacio-Huerta. Therefore, Chelsea’s victory would most likely be clouded by the nomenclature of cheaters and unwavering criticism. However, with the loss, the world saw how one of the most powerful sports clubs in the entire world used data to its advantage. The rest of the world had better step up and do the same, or they will quickly get left behind.
Other writings about Ignacio Palacios-Huerta