In 1 week, what will I conclude to be the number of daily active users the most popular forecasting or prediction markets currently has?
6
Ṁ420Ṁ311resolved Mar 23
42%15%
2500
32%1.0%
350
26%9%
37,000
72%Other
0.6%
1,0000000000
2%
no answer specifying number matches
As part of a bet (https://twitter.com/krishnanrohit/status/1504164219083706371) I proposed, I want to know how many daily active users (DAUs), averaged over the past three months (or smaller number if this is unavailable), the most popular forecasting or prediction markets platform currently has. However, rather than actually research this, I want to experiment with using the market as a way to get the answer.
So, the way this will work is: users can submit free response (numerical) answers and a comment justifying them. Then, on March 23rd around 7:00 PM EST, I will pick the answer I am most convinced by and close the market in favor of that answer.
Separately, to accompany the bet I hope to make, I'm going to have another market that will be predicting whether, 5 years from now, any single prediction market or forecasting platform will have 10X the number of DAUs relative to whatever this market resolves to. This second market will get created upon closure of this market.
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Contra what I said before, I'm now trading on this market but not to win so much as incentivize participation since the current answers lack any explanation. To be perfectly clear, as I discuss below, my answer has clear flaws that anyone could fix with a little effort and beat me in the market. But my hope is that forcing someone to do this improves the quality of the answer.
Enough meta, onto my justification. To get this #, I used similar web to look at monthly traffic #s for Metaculus (https://www.similarweb.com/website/metaculus.com/#overview), Kalshi, Good Judgement Open, Insight Prediction, and Polymarket. Taking the past month's data as my measure for DAUs, I found that Metaculus had the most visits at 1.1M. Then, I just divided this # by 30 to get an estimate.
Note: This is an incredibly flawed way of calculating this. In order to incentivize participation here, I'm going to list out two glaring problems and commit to buying any answer that solves one or more of them:
* I didn't account for most of the visits probably being repeat visits. This means my # may be over-inflated by one or more orders-of-magnitude. Even simple corrections here would presumably improve the estimate.
* I didn't average over the past three months, instead just used the most recent.
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