The basic asymmetry
Most people would rather not lose ten points than gain ten points. More precisely, a loss tends to feel stronger than a gain of the same size. This is loss aversion. Research on the subject has often estimated that losses weigh roughly twice as much as comparable gains, although the exact ratio varies between people, situations and stakes, and shouldn’t be treated as a fixed constant.
The idea comes from prospect theory, developed by Daniel Kahneman and Amos Tversky in the late 1970s as an account of how people actually choose under risk, rather than how a perfectly rational agent would. It has had a large influence on economics and psychology, and it maps neatly onto the choices players face in games.
The main ingredients of prospect theory
Prospect theory describes several features of how people evaluate outcomes.
Reference points. People judge outcomes as gains or losses relative to a starting point, not as final totals. Finishing a game with 100 points feels good if you expected 80 and disappointing if you expected 130. The points are identical, but the reference differs.
Diminishing sensitivity. The difference between 0 and 10 feels larger than the difference between 100 and 110. This applies to both gains and losses.
Loss aversion. The curve is steeper for losses than for gains, so the same size change hurts more than it helps.
Probability weighting. Small probabilities often get overweighted and moderate to large ones underweighted. This is one reason long shots can feel more promising than their odds justify, and near-certainties can feel less secure than they are.
A worked example
Imagine a game offers this choice repeatedly: flip a fair coin, winning 12 points on heads and losing 10 on tails.
The expected value of one flip is 0.5 × 12 − 0.5 × 10 = 6 − 5 = +1 point. On average, you gain a point per flip. Yet many people decline, because the sting of losing 10 outweighs the pleasure of winning 12. If losses feel about twice as heavy, the felt value is roughly 0.5 × 12 − 0.5 × 20 = −4. The bet that is positive on paper feels negative.
That does not mean everyone should always accept such offers. Real stakes, bankrolls and the number of repeats matter, and a single flip can still lose. But the example shows how a feeling can override arithmetic, and why it helps to know which one you are following.
How loss aversion shows up in games
Refusing sensible risks. A player turtles in a strategy game, avoiding any exchange that could lose a unit even when trades favour them on average. Sometimes caution is correct. When it is driven mainly by the dislike of losing something, it can cost more than it saves.
Throwing good effort after bad. Because a realised loss hurts, people avoid realising it. They keep a failing plan going in the hope of getting back to even. This overlaps with sunk cost thinking, but the emotional engine here is the dislike of making the loss final.
Playing to get even. After a loss, the reference point can shift to “where I started the session”. Players then accept risks they would normally refuse in order to erase the deficit. In games with real money this is a recognised hazard, and the guidance on responsible play includes setting limits in advance for exactly that reason.
The endowment effect. Owning an item makes it feel more valuable than the same item would be to a non-owner. In trading games, this can make fair trades seem unfair because you feel you are giving something up.
Framing changes the choice
Prospect theory predicts that the same facts can lead to different choices depending on whether they are described as gains or losses. A 90 percent chance of success and a 10 percent chance of failure describe one situation, but people often respond differently to each wording. Games exploit this with labels such as “lose 10 percent of your stash on failure” versus “keep 90 percent”. Noticing the frame is half the defence. Restate the choice in terms of final outcomes and see whether your answer changes.
Practical steps
- Compare final positions, not changes. Ask where you end up under each option, using the average outcome where it makes sense.
- Pick your reference point deliberately. Your starting stake for the session is arbitrary, and treating it as sacred leads to chasing.
- Check scale. For small stakes, accepting positive-expectation risks is often sensible. For stakes that would genuinely hurt, loss aversion may be protective, which is where ideas of risk management and risk of ruin become relevant.
- Separate caution from fear. If you decline a risk, be able to say why in terms of the odds and your resources, not just “I don’t want to lose”.
- Watch for reversals. Playing more riskily after losses and more cautiously after wins is a common sign that the reference point is steering you.
Loss aversion is not a flaw to be eliminated. It protects against ruin, and the reaction is a normal part of human psychology. It becomes a problem when it quietly overrules a decision that you would endorse on reflection. As ever, outcomes in games with chance stay uncertain, and knowing how losses weigh on you is a way to choose with open eyes.