https://astralcodexten.substack.com/p/play-money-and-reputation-systems?utm_source=url

For now, US-based prediction markets can’t use real money without clearing near-impossible regulatory hurdles. So smaller and more innovative projects will have to stick with some kind of play money or reputation-based system.

I used to be really skeptical here, but Metaculus and Manifold have softened my stance. So let’s look closer at how and whether these kinds of systems work.

Any play money or reputation system has to confront two big design decisions:

1. Should you reward absolute accuracy, relative accuracy, or some combination of both?

2. Should your scoring be zero-sum, positive-sum, or negative sum?

Relative Vs. Absolute Accuracy

As far as I know, nobody suggests rewarding only absolute accuracy; the debate is between relative accuracy vs. some combination of both. Why? If you rewarded only absolute accuracy, it would be trivially easy to make money predicting 99.999% on “will the sun rise tomorrow” style questions.