What is Loss Aversion?

The concept of loss aversion is quite simple. Imagine this scenario:

A friend offers to flip a coin and give you $100 if it lands on heads. If it lands on tails, you give her $100. Would you take that gamble?

Probably not. Most people wouldn’t.

What if tails still loses you $100 but heads now wins you $150? $200?

Interestingly, most people would still reject those offers even though the expected value (and therefore the probability of making money) is objectively positive. This is because for most of us, the pain of losing is psychologically about twice as powerful as the pleasure of gaining. To put it more simply, humans are driven much more to avoid losses than they are to win.

Let’s get into some fun examples of how this impacts our performance.

Golf

Golf scoring is very simple: the aim of the game is to get your ball in the hole with the fewest shots possible. “Par” is the predetermined number of strokes that a scratch (or 0 handicap) golfer should require to complete a hole, and names are commonly given to scores on holes relative to par. A “par” means scoring even (E). A “birdie” means one shot less than par (-1), and a “bogey” means one shot more than par (+1). Again, the lowest score wins.

Researchers have found that a hugely disproportionate number of putts for par (E) are completed compared with attempts for birdies (-1): during the PGA tour from 2004 – 2009, ~83% of putts for par were successfully completed while just ~28% birdie attempts were sunk.

You might be saying “wait, you didn’t factor in the fact that most birdie attempts were probably from more difficult and farther distances than the par attempts”. And you’d be correct. However, even after averaging-out the distances, golfers still successfully putted 3.7% more shots for par than for birdies.

Why does this happen if a miss in both situations means the same thing (that a player is one shot worse off)? Probably because psychologically, sinking a birdie will always be considered “winning” a point (putting a golfer one-under for that hole) whereas a bogey (+1) will always be seen as “losing” a point (one-over).

Tennis

Another fascinating example of loss aversion occurs in the sport of tennis. For those unfamiliar with tennis service rules, a server has two attempts to get the ball in legally. If the first serve results in a fault, the server may try again. If both tries result in faults, a double fault is called and the opponent automatically wins the point.

Tennis players often (and pretty much without exception, like they all do this), utilize slower second serves to avoid committing double faults. This seems rational at first glance, but results actually indicate that utilizing two fast serves would result in a higher chance of winning the point.

While only ~65% of first serves go in, ~75% of those points go in favor of the server. For second serves (~90% of them go in), the result of the point is around 50/50. This means that the potential win percentage for:

  • a fast first serve and a slow second serve = 64.5% (0.65 * 0.75 + 0.5 * 0.9 * 0.35)
  • two fast serves = 65.8% (0.65 * 0.75 + 0.65 * 0.75 * 0.35)

Loss aversion actually costs players a slight chance of winning their service points!

Poker and Sports Betting

Poker players and sports bettors are not immune either. Every poker tournament has a “bubble”, or the spot just before the prizes come in. For example, the 11th-place finisher in a tournament where the top 10 players win prizes is the bubble. The instinctual loss-averse bubble strategy for many amateur players is to play safely, hold on, avoid risky confrontations, and wait for other players to go bust before they do. As a result, they’re often overly cautious, fold too much, and leave a ton of money on the table. Tournament bubble stages are prime times for savvier players to take advantage and accumulate chips.

Every sports bettor probably understands the importance of money management deep down, but few actually have the discipline to always make responsible decisions with their bankrolls. A common issue involves overreactions to winning streaks. Players often grow overconfident when they go on a hot streak or win several bets in a row and begin to increase their bet sizes because they’re “playing with house money”. The same people may also become timid if their profits dwindle, not being as aggressive as they should be because they don’t want to lose more than they already have.

Loss Aversion Affects Everyone

The impact of loss aversion can also be observed in many other sports and situations, even if it’s not as easily quantifiable. Winning teams often fall into the trap of “playing not to lose”. A soccer team will go up 1-0 early and “park the bus” for the remainder of the game. An NFL team with the lead will start trying to run out the clock instead of passing it through the air as they normally would. A basketball team that jumps out ahead due to their fast-pace scoring in transition will begin slowing it down and playing a halfcourt game.

How many times have you watched a team that has been performing well alter their tactics after they gain a lead during a game, despite their original strategy being the reason they had an advantage to begin with? It’s counterintuitive, yet it happens all the time because we all suffer from loss aversion and make irrational decisions to some degree because of it.

Thus, it’s important to be aware that it exists and understand how it can affect you in different situations so you can begin to take the first steps in becoming a better decision maker.


If you love stuff like this as much as I do and want to read more about loss aversion, check out the 1979 paper Prospect theory: An analysis of decision under risk. In it, psychologists Amos Tversky and Daniel Kahneman detail a behavioral model, called prospect theory, using the principles of loss aversion, to explain how people assess uncertainty.


Jerry

loves sports, games of skill, game theory, psychology, blockchain tech, and many other things.

5 Comments

Zach (@ThatBlakGuy123) · July 1, 2018 at 5:16 PM

Yes I agree. But as a poker player, there’s a big difference in bubbling and returning a Roi of like 90%. Imo stealing at these stages is crucial but only if you are a big stack. Some people underestimate a min cash compared to bubbling and busting out especially in a decent sized tournament where people are only eyeballing the top prizes. I enjoy reading and following barryhorse, keep it up!

    jerry · July 2, 2018 at 11:43 AM

    Hi Zach, thanks for reading!

    Agreed that bubble strategy depends on stack size. My point was just that sometimes players become overly risk-averse, and thus become predictable and unnecessarily put themselves at a disadvantage against savvy players with larger stacks.

Daniel Carlson · July 23, 2018 at 11:53 AM

Totally agree with this article on all points. Specifically, times where I made mistakes in my gambling career. (Upping my bets during a hot streak and then lowering them during a cold streak or playing too tight in order to “mincash”)

Love the content! Keep it up.

    Jerry · July 25, 2018 at 9:07 PM

    Thanks for reading, Daniel!

smartersig · September 2, 2018 at 2:13 PM

This is why I prefer using an automated selection process for horse racing via a Machine Learning model coupled with automated bet placement. If possible I would like to go one step further and literally check things are running OK around Jan 1st and then come back and see how things panned out on December 31st. The problem with this is that the occasional software glitch would go unnoticed even if you did have the discipline to wear the blindfold.

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