Basically I filter nothing. If the rating history contains at least 1 game, they go in the 1 game group, if it contains 2 games they go in the 2 games group as well, and so on.
I added the total number of player to the table in the first post.
I won’t do this in the near future.
There are some problems to that:
- To me it looks like the rank settles after at least 10 games, therefor inferring the rating of players who quit early wouldn’t work. (2/3 “quit” after less than 5 games. The rating hasn’t settled at this point)
- I only have ranked games in my sample. If they still are here, but decided to play unranked games until they are better, they appear in my sample as quieted early.
What I have in mind is a breakdown like:
how many players who won their 1st game stayed
how many players who lost their 1st games stayed
lost their 1st and won their 2nd, lost 1st and 2nd, …
I just don’t have the time to do that right now.
Edit: This would probably don’t show anything interesting. If you take a look at the table in the initial post, you can see that while the number of players which have played at least 15 games is a fifth of all players with at least 1 game. The percentage of players weaker than initial rating stays almost the same (≈70% → ≈64%).
If my estimation is correct 19% of the weaker players and 24% of the stronger players stayed for 15 games.
I took a look on how long it takes the average player to finish 15 games if they are new on OGS:
fastest 20% to reach 15 ranked games in 1 day
fastest 50% to reach 15 ranked games in 5 days
fastest 60% to reach 15 ranked games in 9 days
fastest 70% to reach 15 ranked games in 15 days
fastest 80% to reach 15 ranked games in 28 days
fastest 90% to reach 15 ranked games in 66 days
The histogram for September hasn’t settled yet completely.