The ‘Wisdom of the Crowd’ in Sports Betting

Wisdom of the Crowd

If you want to predict the outcome of a challenging problem, is it logical to assume that asking a larger number of people for their opinions or predictions will produce a more accurate collective estimate? The answer is ‘yes’ and the idea is commonly referred to as the Wisdom of the Crowd. It can be a useful tool when dealing with uncertainty, in many environments. from the financial markets, to search and rescue, even sports betting.

However, the accuracy of the Wisdom of the Crowd theory depends on the diversity and independence of the participants. If the group is too homogeneous or influenced by a few strong personalities, then their collective predictions may be less accurate. Also, the crowd can’t be acting as a rowdy mob or a foolish herd.

Wisdom of the Crowd Theory

The Wisdom of the Crowd works by enlisting a diverse and extensive group of individuals to predict the outcome of a given situation. This might be anything from finding a ship lost at sea to guessing the number of sweets in a jar. The theory states that those involved, i.e. the ‘crowd’ , will both overestimate and underestimate the result in roughly equal proportions, resulting in an average prediction that is very accurate. The crowd forecast should be end up very close to the correct result.

How was the Theory Discovered?

The Livestock Fair

In 1906, an anthropologist named Sir Francis Galton observed a competition at a livestock fair, where nearly 800 individuals were tasked with estimating the weight of a slaughtered ox. The group’s median estimate was 1207 Ibs, which was quite close to the actual weight of the ox, measured at 1198 Ibs.

Although no individual guessed the exact weight, Galton discovered that the median of all the submitted estimates was remarkably close to the correct answer, with an error of just 0.8%. This was the first documented instance of what is now referred to as the Wisdom of the Crowd phenomenon.

The USS Scorpion

In James Surowiecki’s book, The Wisdom of Crowds, he tells of the search for the USS Scorpion, a Skipjack class nuclear submarine, which went missing in the North Atlantic Ocean in 1968.

Despite the navy’s search efforts, they were only able to locate the wreck within a ten-mile radius. In a demonstration of ‘collective wisdom’, naval officer Dr John Craven requested input from a diverse group of naval and salvage experts. He utilised their collective knowledge to pinpoint a location or the USS Scorpion. The team’s estimate of the submarine’s position, ended up being a mere 200 metres from the Scorpion’s actual location, ten thousand feet down on the ocean floor.

Although Craven restricted his ‘crowd’ to experts in the field, there was still enough independent thinking within the group to get a result.

Wisdom of the Crowd and Betting

The Wisdom of the Crowd theory can been applied to sports betting as a way of making more informed predictions. By default, people that bet are a large group from diverse backgrounds, with different levels of expertise and knowledge about a particular sport or event.

The theory suggests that the collective wisdom of this large group will produce a more accurate prediction than any individual expert or algorithm. The group’s opinions help to cancel out individual bias and error.

There are several ways in which this theory can be applied to sports betting. Sports odds are set by a mix of different people and groups, such as bettors, analysts and bookmakers. All of them ‘decide’, via bet placement and market movement, what the correct odds should be for a particular event. Once the collective information has flowed into the market, the odds begin to settle and the correct price is usually achieved.

Betting Markets

When a market opens, some of the sharpest punters might take action and place early bets, correcting a price that in their opinion is wrong. This is generally followed by ‘public’ money or the more casual punter, who will, by placing their bets, move the market ‘efficiently’ much closer to where it should be in terms of price.

So, the odds, for example in a football match, by kick off time, will very accurately predict the probability of the outcomes for the teams. This is due to the fact that the ‘crowd’ has been continuously assessing the information as it arrives and betting accordingly right up until the start of the game.

Often the smart bettor or trader will come back into the market at that stage and trade their original position.

Lazy Judgements

There can be times, where bettors get it wrong (particularly in low liquidity markets with a small ‘crowd’) by making lazy or skewed judgements. They might bet on the most ‘familiar’ team or simply bet on the favourite or the one that’s most popular. This push the market away from its ‘efficient’ price.

Information Cascades

Information cascades are not that surprising a phenomenon. They often create a ‘feedback loop’, where decisions continue to be made based on the original information responsible for driving down the price in the first place. A non-betting example, might be a ‘run on a bank‘ where investors and account holders are swept away by the ‘cascade’, regardless of the accuracy of the information.

Germany’s World Cup Exit

In the 2018 World Cup, many people put their money on Germany, and the betting exchanges and bookmakers had them as favourites. Germany were defending champions, they were second in the World Rankings and had a reputation for going deep into big tournaments. They were also widely tipped up in the press.

On closer analysis, however, the Germans had not been in great form. They had only won one of their previous six games, a 2-1 victory over Saudi Arabia. Germany’s group was not straightforward either, comprising of South Korea, Mexico and Sweden. Key players who’d contributed to their 2014 World Cup title, like Schweinsteiger, Klose and Lahm, were not in the 2018 squad, so it was much less experienced.

Add to that the fact that only twice had a country retained the World Cup, Italy in the 1930’s and Brazil in the early sixties (so not even in the modern era) there were reasons to argue that Germany would find it a tough ask to win in 2018.

In the end, Germany crashed out in the group stages.

Next England Manager

Another example came back in 2012. Betting markets like the Next Manager market, are often subjected to information cascades. When Fabio Capello resigned, punters began to bet large amounts of money on Harry Redknapp being the next England manager.

The market was based on solid arguments that favoured Redknapp, but also the eagerness of the public to trust the stories of pundits and the media. In the end it was Roy Hodgson who got the job.

Trusting The Wisdom of the Crowd

In the financial markets, there is often hype surrounding some stocks, shares, or other financial instruments. Investors charge to get on board in a ‘frenzy’ that much of the time does not follow cold logic. A share price might be artificially increased or reduced by ‘over hype’ or ‘negative comment’. Under these circumstances, the relevant market moves in an unnatural direction.

This can happen in the betting markets too and, in this age of digital information, social media and communication applications, the reliability and sources of such information should be questioned more rigorously before putting trust in the ‘crowd’.

However, as alluded to before, if the market is highly liquid, the more accurate the price will be. This is partly the reason that value odds are more easily found early on, in less developed markets, or in niche markets where ‘knowledge’ and liquidity is less.

Wisdom of the Crowd Experiment

In 2014 Pinnacle Sportsbook / Bookmaker decided to put the Wisdom of the Crowd theory to the test. They set it up by presenting their customers with a large number of ‘chocolate balls’ and asking them to correctly guess the total.

To help make it more interesting, Pinnacle published the daily average of guesses sent in. Participants were therefore forced to decide between first mover ‘advantage’ but with minimal information, or waiting to guess later on but knowing and being able to use as a guide, the guesses of other customers.

The daily average of the guesses submitted was published each day.

Date	Mean Guess
21/03/2014	0
22/03/2014	752
23/03/2014	667
24/03/2014	635
25/03/2014	629
26/03/2014	614
27/03/2014	634
28/03/2014	663
29/03/2014	658
30/03/2014	654
31/03/2014	649
01/04/2014	645

They received a total of 608 entries. The range of guesses varied from 10 to 7436. One customer guessed correctly at 636.

From the table you can see that the first day’s average guess was 752, about 15.5% higher than the true number. Yet, by the third day, average guess was within just 1% of the actual number, and from that point on never moved beyond 11% of the total.

Late in the competition, Pinnacle received a jump in new entrants. This had the effect of moving the average further away from 636. In a day, however, it was back to within 11% of the correct number.

Interestingly, only just over 25% of entrants managed to keep their guesses within the range of the daily average.

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If want more information on ‘Crowd Wisdom’, then check out this video:

Conclusion

By utilising the collective knowledge and insights of diverse groups of people, it is possible to make better decisions and solve complex problems that may be difficult to solve by relying solely on individual expertise. The crowd, however, needs to be of a diverse nature and high number with no unnatural partiality or biases within the group.