Occassional thoughts about orienteering

Saturday, August 09, 2008

Orienteering and loss aversion


Today was the first day of the US O' Champs and I bet that if you stood at the finish line and asked everyone "how was it?" you'd hear:

1. Something like, "I lost 5 minutes, I went to the boulder, but it was the wrong boulder. I relocated and tried to attack the control again but was hesitant and lost some more time."

2. Something like, "The long leg was interesting. I think, I took the best route."

If you counted, you'd probably hear the first sort of comment (disappointment about mistakes) a lot more than the second (satisfaction with something that went well).

A few years ago I did that as an experiment. I asked finishers, "how did it go?" I didn't keep a count, but I remember only one person (of maybe a dozen) didn't emphasize their errors.

Loss aversion is the idea that people tend to feel a loss more strongly than a gain. I think that is what is going on. An orienteer feels upset about losing time, but doesn't value the time that they didn't lose. Of course, it also has something to do with measurement. It is pretty easy to figure out how much time you lost. It is a lot harder to figure out how much time you could have lost but didn't.

I have some more thoughts I ought to write about loss aversion and how orienteers spend so much time and energy analyzing what they did wrong. But, I think I'll go watch a bit of the Olympics on TV instead.

Sprint O' Technique Video

He missed an important tip - always go to the next control.

Back to okansas.blogspot.com.

posted by Michael | 2:16 PM


That is an interesting observation and you may be on to something. One thing that may confound this model, or applying a sort of prospect theory-type of analysis to orienteering, is that the so-called "reference gamble" (used to derive the utility function) is a little different in orienteering (I think) than in the standard sense. What I mean is that there is only so much to gain from assuming risk in orienteering. The distribution of outcomes is pretty skewed, with a long tail on the downside, but which reaches it limit at perfect or trivial navigation.

In the classic sense of evaluating risk aversion, you want to be able to quantity the impact of utility of losses and gains of similiar magnitude. It seems like the model would need to be adapted for orienteering.

Of course, there are probably ready approaches to do this. I hope that some of the economists that stop by here might be able to interject as I have never really studied this stuff.

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