Do Not Use Memory When Predicting Sport Outcomes, Study Reports
When it comes to almost any sports, there are always people betting the outcomes. Although some bets might be friendly and low-risk, other bets can involve quite a lot of money. According to a new research study, people who like to gamble on sport games might be able to use a new technique that can help them predict outcomes more efficiently than before. Researchers from the University College London (UCL) and the University of Montreal reported that based from their results, people should not use their previous knowledge and memory when predicting the outcome of a game.
The researchers explained that when people make decisions, they are often influenced by their memories of previous situations and events. These memories can mislead the individual in making a current decision because their memories tend to make them biased in the situation. The research team, headed by Dr. Bradley Love from the UCL Department of Cognition, Perception and Brain Sciences, compared the accuracy of people's predictions in sport games when they relied on their memory to people who made predictions based on idealized scenarios compiled by a statistical analysis.
"Providing people with idealized situations, as opposed to actual outcomes, 'cleans' their memory and provides a stock of good quality evidence for the brain to use," Love explained.
The research team recruited two groups of participants. The first group of participants was given correct information about the outcomes of several baseball games, whereas the other group was given idealistic outcomes of baseball games based on the match ups of the players and previous statistical data. The participants were all given a list of team rankings based on wins. The ranking was altered so that the second group received an ideal list of rankings, which meant that the best team with the best players and record always won. The participants were then asked to predict the winner in a match up between two major league teams.
"Unlike machine systems, people's decisions are messy because they rely on whatever memories are retrieved by chance. One consequence is that people perform better when the training is idealized - a useful fiction that fits are cognitive limitations," Love stated.
Love and his colleagues found that the people who were trained under the idealized group were better able to predict outcomes of games, similarly to what a computer would calculate. Based from these findings, the researchers believe that people with a "clean" slate can predict outcomes better because they would not be biased toward any particular team. The people with idealized training would focus on the numbers and make the best prediction based on statistics and not emotions.
Although this study is still very new, it suggests that people could be trained to make more computerized predictions when they ignore their previous knowledge on the current situation.
The study was published in the journal, Proceedings of the National Academy of Sciences.