I had an idea for a data-driven experiment and wanted to ask if anyone here has already tested it — or if someone with a proper setup would be willing to.
The Concept: Using a standard 4-2-3-1 formation (as an example), give 10 players all attribute ratings set to 1, and just 1 player with all attributes set to 20. The idea would be to rotate this "superstar" through each position (GK, DL, DC, DR, DMs, AML, AMR, AMC, ST), keeping all other variables the same — same tactic, same opponent, same match conditions, same instructions, etc.
Run simulations for each variation (ideally 50–100 matches per position to account for RNG) and measure impact on team performance — win %, xG, goals scored/conceded, etc.
If done properly, this could help identify which single position has the most influence on results, and that in turn could help guide smarter transfer policies — e.g. which positions to invest heavily in, or prioritize when building a squad.
If not, would anyone here with a test rig or simulation setup be interested in trying it?
Wouldn't it be tactic dependent though? And you can't just test the positions but each role within it too. Even then you can't really account for how that roles importance changes compared to what other roles are also in play without a really astronomical number of data points.
Hi all,
I had an idea for a data-driven experiment and wanted to ask if anyone here has already tested it — or if someone with a proper setup would be willing to.
The Concept:
Using a standard 4-2-3-1 formation (as an example), give 10 players all attribute ratings set to 1, and just 1 player with all attributes set to 20. The idea would be to rotate this "superstar" through each position (GK, DL, DC, DR, DMs, AML, AMR, AMC, ST), keeping all other variables the same — same tactic, same opponent, same match conditions, same instructions, etc.
Run simulations for each variation (ideally 50–100 matches per position to account for RNG) and measure impact on team performance — win %, xG, goals scored/conceded, etc.
If done properly, this could help identify which single position has the most influence on results, and that in turn could help guide smarter transfer policies — e.g. which positions to invest heavily in, or prioritize when building a squad.
If not, would anyone here with a test rig or simulation setup be interested in trying it?
Wouldn't it be tactic dependent though? And you can't just test the positions but each role within it too. Even then you can't really account for how that roles importance changes compared to what other roles are also in play without a really astronomical number of data points.