There is a very good reason we rely on heuristics – evolution. Our distant ancestors when faced with complex life-threatening problems didn’t have time to weigh up the situation, so developed quick-fire methods. Those that worked were passed down through generations, and we are still relying on them, often when we shouldn’t.

Introducing The Common Heuristics

Anchoring

Anchoring affects people’s ability to estimate the most probable number of items of a particular kind or the most probable value along a sequence.

Example: A group is asked to guess the percentage of African countries in the United Nations. Before answering they witness a random process to produce a number (the anchor), and are asked whether the percentage of African Nations is above or below that anchor. They then make their actual estimate of African countries in the United Nations. The estimates given will track the anchor, even though the participants know it is random.

Without realising it, the individuals are anchoring their estimate to a totally arbitrary point. The reason for this is thought to be because the anchor is taken as a working hypothesis, a starting point from which the individual is reluctant to move too far away from.

This phenomenon is widely exploited in marketing and is very relevant to betting. Bettors should beware anchors in bet wording, and realise how handicaps, and spread values will influence your judgements, without you even realising.

Availability Bias

Availability bias manifests in people’s tendency to attach greater significance to events that leave the strongest impression, or are easier to recall.

Examples of this include the way people over-estimate the risk associated with dramatic and traumatic events such as a terrorist attack or earthquakes. The sale of earthquake insurance goes up immediately after earthquakes though the risk is greatly diminished, while people are prepared to pay a higher premium to insure against death from an act of terrorism than insurance against death of any kind (which would obviously include terrorism).

From a betting perspective be wary of assigning excessive significance to more recent or memorable results. Ask yourself whether you find it easier to recall a 0-0 draw or a high-scoring game.

It’s likely to be the latter, but it doesn’t mean it is more probable. In soccer bettors tend to over-estimate the frequency of events like red-cards and corners, because they are important and easily recalled. This impacts perceived probability and betting behaviour.

It is linked to a common phenomenon of bettors favouring the Over in Totals markets, or buying on a Spread, as availability bias leads them to wrongly conclude the event concerned is more likely than in reality.

Diversification

This heuristic describes how people tend to demonstrate greater diversity when confronted with simultaneous rather than sequential choices.

Example: When asked to choose five chocolates from a selection box, with an equal number of varieties, individuals make more diverse selections than when they make five sequential choices.

With relation to betting, punters tend to invest more when the opportunity appears to be more diversified. A good example would be backing the draw and the away team based on the perception of a more diversified bet, as opposed to simply laying the home team. There isn’t, however a logical reason why you should bet more, unless the Expected Value is greater.

Escalation of Commitment or Sunk Cost

This heuristic describes how people feel compelled to justify a commitment by increasing the cumulative investment despite the potential cost going forward outweighing the potential benefit.

This is commonly described as ‘throwing good money after bad’. An example would be to sit through a film that you are not enjoying just because you have already invested time and money in watching it, and therefore determined to justify that investment.

From a betting perspective this can be seen when punters persist with a bet that has a high probability of incurring a large cost rather than taking a certain immediate, but smaller loss. People in these situations tend to display an irrational determination to justify their original decision, instead of ‘cutting their losses’.

Representativeness, or the Gamblers Fallacy

People tend to believe short sequences of random events are representative of longer ones, ignoring the fact that these events are statistically independent.

Example: The gambler’s fallacy is also known as the Monte Carlo Fallacy because in 1913 Black come up 26 times in a row on a roulette table at the Monte Carlo casino. After the fifteenth Black bettors were piling onto Red, assuming the chances of yet another Black number were becoming astronomical, thereby illustrating an irrational belief that one spin somehow influences the next.

The gambler’s fallacy is closely related to the Hot Hand Fallacy, which is the belief in streaks of good/bad luck. Where someone experience what seems like an atypical sequence of events, they infer some special significance i.e. I am on a hot streak, or my luck is out.

It has come to be known as the Hot Hand Fallacy after a study in the 1980s suggested a basketball player who successfully makes a shot is no more likely to be successful the next time they throw just because of their initial success.

This is particularly relevant in betting for random games of chance such as roulette, lotteries and dice games.

Humans aren’t machines, we try to be rational, but our instincts often get in the way. This can be costly for gamblers, so as much as possible ignore what your gut is saying unless its time for lunch.

If this article has struck a chord with you, then further reading of Daniel Kahneman & (the late) Amos Tversky is highly recommended. The pair are widely credited with ground-breaking work in the field of cognitive biases and Kanheman went on to win the 2002 Nobel Memorial Prize in Economics, despite not being an economist.

His recent best seller “Thinking Fast, Thinking Slow’ summarises much of his work, and will open the eyes of anyone interested in how people deal with making risk based decisions under uncertainty, which is exactly what betting is.

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Source: pinnacle.com