- Our idea of the future is based on the past
- How many piano tuners are there in Chicago?
- Superforecasters & the Good Judgement Project
- 10 Commandments of good prediction
The anticipation surrounding the Mayweather vs. McGregor match is unparalleled due to its unique nature, sparking widespread discussion and conjecture. This scenario creates a conundrum for those attempting to forecast the result, as traditional predictive methods rely heavily on historical precedents to gauge future outcomes. In such cases, bettors can benefit from a methodology devised by a Nobel Laureate in physics.
How to make predictions?
Predictions is inherently a data-driven science. Possessing a wealth of historical data enhances the likelihood of devising a predictive model that accurately foresees future scenarios.
Innovation in prediction occurs when new variables influencing an event are identified within a dataset, enabling the refinement of forecasts beyond current theories. This is evident in domains like meteorology and outright bets on the Premier League.
Absent historical data, qualitative analysis becomes essential, involving structured speculation about future events. While seemingly rudimentary, the application of scientific principles, such as the Fermi method, elevates this approach.
Enrico Fermi, a pioneering physicist and Nobel Prize recipient, is celebrated for his seminal contributions to nuclear physics and for developing a practical technique for making swift estimations on seemingly incalculable problems due to limited data.
The absence of data necessitates a qualitative analytical approach, where logical arguments predict potential outcomes. This approach, although appearing simplistic, gains credibility through the Fermi method. Fermi challenged his pupils with thought-provoking questions to illustrate this technique:
How many piano tuners are there in Chicago?
Approaching this question encourages the formulation of a logical argument based on estimations and sub-questions, leading to an educated guess without immediate access to search engines.
If you asked yourself the following sub-questions (or followed a similar logic but with slightly different questions) you would arrive at a good idea of the answer.
How many pianos are there in Chicago?
How often is a piano tuned each year?
How long does it take to tune a piano?
How many hours a year does the average piano tuner work?
Using your guesses for the first three questions you can calculate how many piano-tuning work hours there might be in Chicago annually and divide it by the number of hours a tuner might work in a year to arrive at a reasonable guess of how many pianos that would support. Of course to inform questions one, two and three you have to break them down into further sub-questions.
So for question one you would need to guess Chicago’s population using any knowledge of other US cities’ populations. You might guess somewhere between 2-2.5 million (it is actually listed as 2.7 million in 2016).
You then need to work out what percentage of people own a piano, which by rule of thumb could be one for every 100 (around 25,000 if you use the upper guess for population). Then throw in a value for bars, clubs, schools etc. so you might double the penetration to say two in every 100 or 50,000.
Questions two and three are simple intuition, unless of course you have domain knowledge. A piano is tuned around once a year and takes roughly two hours. Question four could be based on your own experience or an average full-time job working five days a week with standard holidays.
So if you guess that there are 50,000 pianos needing tuning once a year, taking two hours each to tune, that represents 100,000 tuning hours. Divide that by the 1,600 hours worked on average per year by a tuner and you would arrive at 62.5 piano tuners in Chicago.
There is no definitive answer, though analysis of yellow pages (courtesy of Daniel Levitin) came up with 83, including duplicates, so if you got somewhere between 55 and 70 you are doing well.
Don’t stress too much about the accuracy of the answer as much as the approach you took. This kind of a mindset is conducive to accurate forecasting in the absence of data - similar to Mayweather vs. McGregor betting. If you didn’t quite understand how to approach this question, read the rest of the article then try again with another abstract question.
The piano tuner question has been used by Google, for example, as an interview question - helping to establish reasoning skill - along with similar questions like ‘How much does the Empire State Building weigh?’
Bookmakers aren’t in the business of making predictions; they simply offer a measurement of how likely something is to happen, represented in the form of odds. In that respect, we are on safer ground with established sports that follow a fixed set of rules and have good solid and accessible historical data.
Superforecasters - The Good Judgement Project
The art of prediction, as elaborated in "Super-Forecasting: The Art & Science of Prediction" by Philip Tetlock and Dan Gardner, gains depth through the lens of the Good Judgement Project (GJP). This initiative explores the evolution of predictive science, offering invaluable insights.
For over four years, Tetlock rallied around “20,000 intellectually curious individuals” to partake in the GJP, aiming to project the outcomes of various global predicaments. This endeavor was part of a broader mission led by IARPA (Intelligence Advanced Research Projects Activity), a segment of the US intelligence community, focusing on refining forecast accuracy regarding pivotal political and economic incidents affecting national security.
IARPA organized a forecasting contest that grouped five teams, including the GJP, spearheaded by top-notch researchers in the field. Throughout five years, nearly 500 queries were posed, demanding daily responses from the participants.
The precision of these forecasts was gauged using Brier Scores, a metric that calculates the discrepancy between the forecast certainty and the actual result. Introducing a confidence measure for each forecast encourages a balanced approach to confidence, distinguishing the adept predictors effectively.
Unlike traditional bookmaking, which doesn't entail making predictions but rather setting odds that reflect an event's likelihood, 7x7Bets stands on more familiar ground with conventional sports, thanks to the abundance of historical data and established rules.
To attract new clients and retain current ones, 7x7Bets expands its horizons beyond traditional sports, venturing into emerging or less conventional sports where historical records are scant, such as eSports, specials, and elections.
The rarity and varying conditions of elections render historical data almost obsolete. Poll reliability issues and the complexities of news dependency often thwart accurate political betting.
The Maiden Conundrum
Maiden horse races present another instance where predicting outcomes is notably challenging, serving as an informative case despite 7x7Bets not offering horse racing bets.
Maiden races for two-year-olds, featuring horses with no previous wins, lack substantial form data. The brief nature of these races leaves minimal room for error, complicating predictions for horses making their debut on the track.
How do you predict the talent of a horse that has never run, in a race where success (from the trainer/owner perspective) may be measured in terms of simply giving their runner a positive experience of racing?
You ask a set of deductive questions that follow the Piano Tuner Problem.
How good is the horse’s breeding? How successful is the breeder?
What about the trainer? Their record with first-time out winners, and over the same course distance?
What about the jockey’s record in Maidens?
These deductive questioning method helps in estimating a horse's odds of success, ideally synthesizing these factors into an overall rating and utilizing Brier Scores for a precise confidence evaluation against market odds.
Thus, these seemingly unsolvable challenges offer unique opportunities for gamblers, as bookmakers, equipped with only their expertise and a Fermi-like strategy, navigate these uncertainties without reliance on mathematical models.
The 10 commandments for good prediction
The challenges that the GJP faced are no different to those faced by bettors and bookmakers when they move away from traditional sports markets into the realms of exotic bets which brings us back to Mayweather vs. McGregor. We have a reasonable idea about handicapping Boxing and MMA, but a boxer vs. a mixed martial artist essentially opens up a Fermi type problem (bettors can try and solve using the live odds and odds movement chart below).
The good news here is, based on the findings of the GJP, there are some very practical things that were experimentally proven to raise the base level of predictions of these amateur forecasters.
Tetlock has actually distilled 10 commandments of good prediction based on the experience of the GJP. More detail can be found at www.goodjudgementproject.com - better still read the book - but here they are (adapted in short-form) and applied to betting and where applicable, the Mayweather vs. McGregor question.
Using randomized trials Tetlock established that those reading a guidebook containing these tenets increased their Brier Score by 10%. That could be enough to move you into long-term profitability as a bettor.
Focus on problems where your hard work is more likely to pay off, ignoring both the obvious and the intractable. There is little chance of you discovering something about the Premier League that isn’t already accounted for by the market. Find a realistic level - a Goldilocks Zone - where it is realistic to assume value can be found with reasonable time and effort.
Break big chunky problems into a series of smaller ones. For example ‘Who will win between Mayweather and McGregor?’ Might it become “What boxing form does McGregor have?” “What are their respective motivations?” “What style does McGregor fight, and what is Mayweather’s success-rate against that style?” and so on. Assign values and a degree of confidence to your answers.
Balance inside and outside views. In respect of Mayweather-McGregor that requires you to step outside of a boxing or MMA only assessment. McGregor has a huge following within the MMA community, who are no doubt backing him in large numbers, but is their inside view valuable here? Equally, how much do boxing purists know about MMA? Trying balancing both views.
Balance over/under compensation for new information. This basically encourages a Bayesian approach of incorporating new evidence, but equally cautions against over-reacting to new information, as much as sticking to your guns. This relies on experience and weighing the value of the source of information. A huge amount will be said online about this fight, so spend time figuring the best sources of information.
Challenge your prejudices. If you know your boxing and can’t see past a Mayweather win, challenge yourself to think of any scenarios in which he might lose, and vice-versa.
Translate hunches into degrees of probability. An experienced forecaster will have a wider language than ‘Mayweather is a certainty’ or ‘McGregor has no chance.’ Their approach will reflect a more nuanced assessment measured in probability, not rhetoric.
Learn to balance over/under confidence. This means striking a balance between procrastination to the point of inaction - and missing an opportunity, going all-in without making a measured assessment.
Analyze both failures and successes with the same rigour. What is worse than being wrong, is not taking ownership for where the mistake was. Equally, you can make the right decisions and still get the wrong result and vice versa.
Bring out the best in others and let others bring out the best in you. This relates to the Team nature of the GJP, so will only be relevant if you are working as part of a syndicate or perhaps if you are very active on Social Media and willing to share your work and accept/give constructive criticism.
Improvement only comes from putting your good intentions into practice. It is fine to see betting as recreation, just don’t expect to win in the long run. If you aren’t happy with that prognosis accept that you will have to commit time and effort to betting in a systematic and structured way.
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