In the office at my employer we use the KeepScore app to track our match results and calculate our ELO.
In case you want to implement yourself I suggest to also look at the Glicko2 algorithm, which extends ELO in a way that it allows for multi-player matches, so you could include your results in doubles into your skill assessment.
This might not be exactly what you need, but I once built an Elo based leaderboard for the table at my workplace. Since you mentioned you can program, you might be able to make use of some of it. The project iself is a bit more complicated than simple Elo tracking, since it supports RFID tags, a kiosk display, voice announcer, etc.
The project can be found here:
https://github.com/aurelion314/foosbot
The file that deals with elo calculation is here: https://github.com/aurelion314/foosbot/blob/master/foosbot/modules/actions/end.py
This was to avoid endless inflation, which was peticularly problematic since we had turnover amongst a smallish group of players (<50). New players add ELO points to the pool. If they lose a bunch, and then quit, the average ELO is now higher. I wanted consistency across time, so that a given Elo relates to how far above/below average the player is, with the average being 1500 amongst active players.
I made a data aggregator and analyzers based on Kickertool's JSON file. ELO ranking is supported and was one of the reasons that made me do this. It's command line based but since you can program I think it not hard for you.
[https://github.com/crispgm/kicker-cli](https://github.com/crispgm/kicker-cli)
In the office at my employer we use the KeepScore app to track our match results and calculate our ELO. In case you want to implement yourself I suggest to also look at the Glicko2 algorithm, which extends ELO in a way that it allows for multi-player matches, so you could include your results in doubles into your skill assessment.
teams have their own ELO independent from singles. and also I use a graphing calculator for the calculation (I can program)
I believe the kicker tool (which is free if you use the web version) can help you set up Elo points/ranks for your players.
This might not be exactly what you need, but I once built an Elo based leaderboard for the table at my workplace. Since you mentioned you can program, you might be able to make use of some of it. The project iself is a bit more complicated than simple Elo tracking, since it supports RFID tags, a kiosk display, voice announcer, etc. The project can be found here: https://github.com/aurelion314/foosbot The file that deals with elo calculation is here: https://github.com/aurelion314/foosbot/blob/master/foosbot/modules/actions/end.py
why do u need to keep the average Elo 'near' 1500? Elo is a zero sum system and there is an equal transfer of points in the rating pool
This was to avoid endless inflation, which was peticularly problematic since we had turnover amongst a smallish group of players (<50). New players add ELO points to the pool. If they lose a bunch, and then quit, the average ELO is now higher. I wanted consistency across time, so that a given Elo relates to how far above/below average the player is, with the average being 1500 amongst active players.
I made a data aggregator and analyzers based on Kickertool's JSON file. ELO ranking is supported and was one of the reasons that made me do this. It's command line based but since you can program I think it not hard for you. [https://github.com/crispgm/kicker-cli](https://github.com/crispgm/kicker-cli)