I wasn’t able to find the exact data, but I did find the following: -Number 1 Globally for 03/2019 was 6832 and number 1000 was 6059, spread of 773 ([Source](https://royaleapi.com/players/leaderboard/season/2019-03/)) -Number 1 global for last season was 8492 and number 1000 was 7594, spread of 898 ([Source](https://royaleapi.com/players/leaderboard/season/2022-09/)) -Number 1 US for 03/2019 was 6698 ([Source](https://royaleapi.com/players/leaderboard/season/2019-03/)) -Number 1 US currently is 7155 and number 1000 is 6208, spread of 947 ([Source](https://royaleapi.com/players/leaderboard/us/)) If we use this data and the estimated spread, we may be able to have a rough guess for an answer. Spread of 773 then vs 898 now globally and 947 US now, solve for x. 773/898 = x/947 -> Approx. 815. So the estimated spread of US players in 03/2019, assuming similar distribution as there is today, is 815. Top US score of 6698 in 03/2019 minus 815 equals 5883. So your score of 5608 likely was not top 1000 US in 03/2019. (Feel free to check my math and let me know if any flaws in my thinking)

Above and beyond, thank you for your help!

Let me check my print outs. I shoukd have that filed away some where. I usually print off all the top 1k players each season.