By : Christopher Ingraham
Jan. 6, 2020 at 5:00 a.m. PST
“Trust your gut.” It’s something we’ve all heard (and probably even expressed at one time or another), an exhortation to not overthink decisions in realms as diverse as business, sports, dating and politics.
But is it actually good advice?
In a new paper published in the Journal of Behavioral and Experimental Economics, a trio of British economists applied some brainpower to the question of gut feelings and found that people who second-guess themselves make considerably worse decisions than those who stick with instinct. The researchers focused on prediction accuracy in sports betting but said their findings would apply in any realm where people have to make educated guesses about the future.
The economists gathered data on 150 users of a popular sports betting and prediction website. This was a representative sample of a subset of bettors vying to predict outcomes for all 380 soccer matches in the English Premiere League during the 2017-2018 season.
The final data set consisted of 57,000 individual predictions, each consisting of a user’s best guess of the final score of a given match. Users were called on to predict scores and could revise their forecasts up to the minute the match started.
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Revisions were infrequent: Only 6 percent changed their predictions, with the typical user revising 15 out of 380, and most of those occurred within minutes of the initial forecast. The authors speculate that in such cases, users typed in a prediction and looked up some relevant information on the match before quickly changing their mind. But there also were a number of instances involving large segments of time — days, even weeks — between prediction and revision; such bettors waited nearly two days, on average, to switch gears.
The researchers specifically wanted to know whether the revisions were more accurate than the originals.
In theory, there are a lot of reasons to believe this might be the case. A person would presumably revise a prediction after obtaining new information, such as an analyst’s match forecast or a team roster change.
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In practice, however, the opposite was true: Revised forecasts accurately predicted the final match score 7.7 percent of the time. But the unaltered forecasts were correct 9.3 percent of the time. In other words, revised forecasts were about 17 percent less accurate than those that had never changed. “Game players would have been better off sticking with their first judgments rather than ever revising,” the authors write.
So where did the second-guessers go wrong? For starters, the researchers controlled for match-to-match and player-to-player variation — it isn’t likely the case, in other words, that matches receiving more revisions were more difficult to predict, or that bad guessers were more likely to revise their forecasts.
The researchers found that revisions were more likely to go awry when forecasters dialed up the scores — by going, say, from predicting a 2-1 final score to 3-2. Indeed, across the data set, the bettors systematically underestimated the likelihood of a 0-0 draw: an outcome anticipated 1.5 percent of the time that actually occurs in 8.4 percent of matches.
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That suggests a general forecaster bias toward scoring as opposed to nonscoring — or, more broadly, toward things happening rather than not. Few people, after all, watch a soccer match and hope that nobody scores.
One final, tantalizing piece of evidence: Forecasts revised after a longer period of time were considerably less accurate than those changed within a few minutes. This suggests that overthinking it, or “over analysis” in economics parlance, was a key driver of the revised forecasts’ relative inaccuracy.
In the end, the authors write, their findings “could have relevance to other contexts where judgmental forecasting explicitly takes place and which have real economic importance, such as in company management and planning, financial markets and macroeconomic policy.”
For those of us not in the prediction business, the findings can be boiled down to a simple message: Trust your gut.
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Got a knotty nonprofit strategic problem to solve? I just wanted to pass the word that the Harvard Business School Ass’n of Oregon is taking applications for its Community Partners program.
Through this program, HBSAO partners with local nonprofit organizations to help them solve a wide variety of managerial, competitive, and analytical challenges. They assemble teams of volunteer consultants, from Harvard and other top business schools, to tackle questions such as:
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D-Prize funds new entrepreneurs who increase access to proven poverty interventions.
The world has already invented ways to end poverty, yet the best interventions are not being distributed at mass-scale. Can you design a business or NGO that solves one of the Distribution Challenges below? If selected you will be awarded up to $20,000 to launch a pilot in any region where extreme poverty exists.
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If you’re interested in the Global Competition, visit www.d-prize.org for challenges, deadlines, and all the information you need to apply.
The University of Oregon’s Division of Global Engagement is excited to announce the 2019 application cycle for the UO-Global PDX collaboration grant. This collaboration grant offers one of two possible avenues for UO faculty to collaborate with a Global PDX Organization. One option will serve as seed funding for a UO faculty member who seeks to develop a collaborative research project with a Global PDX member organization. The second option will fund a curricular integration project that incorporates the work of a Global PDX member organization into an ongoing or experimental UO course
The deadline for applications is June 15, 2019. All other details about the collaboration grant, including award amounts, application procedures, and selection criteria, may be found at: https://gsi.uoregon.edu/GlobalPDX
Please direct all questions and concerns to Grace Honeywell, Innovative Programs Coordinator for UO’s Division of Global Engagement.