ban rate = not played
win rate x (1 - ban rate) + theoretical win rate x ban rate = true win rate.
Assuming theoretical win rate = 1 (whoever picks this champ will
tee a win!)
Result:
Leblanc: 0.46 x 0.89 + 0.11 = 51.94%
Malz: 0.525x0.996 + 0.004 ~= 52%
Jayce: 0.47x0.93 + 0.07 = 48.83%
Fault of this approach: Skews data to favor whoever has higher ban rate
Assuming theoretical win rate = 0 (whoever picks this champ will
tee a loss!)
Result:
Leblanc: 0.46x0.89 = 40.94%
Malz: 0.525x0.996 ~= 52%
Jayce: 0.47x0.93 = 41.83%
Fault of this approach: Skews data to punish whoever has higher ban rate
Assuming theoretic win rate = 0.5 (average players will always pick this champ)
Result:
Leblanc: 0.46x0.89 + 0.11x0.5 = 46.44%
Malz: 0.525x0.996 + 0.004x0.5 ~= 52%
Jayce: 0.47x0.93 + 0.07x0.5 = 45.33%
Fault of this approach: Assumes average win rate for that particular champion (does not account for meta, steeple, pro-player streams, etc.)
Overall ban rate doesn't affect the true win rate comparison much... I suggest looking at their play rate! (how often that particular champion is actually played will obviously factor into that champion's strength)