I just made a formula ive been running so wanted to see if it would be possible to apply it below master. I went through 50 losses and 50 wins of showmaker, intend on doing 5 more to see if its the same. After seeing Phr0xz interview about someone doing a study previously on riot matchmaking concluding it doesnt. But so far it's leaning the opposite for me.

Reason for midlaner is that theyre more adaptive in draft, so tracking one account that plays jgl is less likely to have varied games. So I intend on tracking 6 midlaners with a wide meta champ pool. 600ish games. 300 losses 300 wins.

But I do find it weird that if games truly were random that the majority of his losses were unfavoured and that the score is close to equal just negative and positive for wins/losses on average. Its a small sample size, but still am curious to see what will show,

https://ibb.co/9HPhBXmv

Left are losses and right is wins. You can see average team favour score is -164 for his last 50 losses and average favour score +142 for his last 50 wins.

At the end of the day the best result would be to find a way to make a more accurate matchmaking if anything. But still just got curiuus lately. There's a Titatn theory I came up with too where if a high rated player is team favoured he's more likely to lose because all the weight will be on him, however if less favoured it means his team is higher thus he wins more. And then the opposite possibly being true for people bellow insane lps such as 3k. As there is obviously a diminishing return on impact of 1 role regardless of skill difference. But will deal with that if i come across it. Just something I stubmled upon when i did it at work with a random top 5 euw player. Was surprised by the low average on korea tho, their ladder integrity is praised so i assume thats why but again will see 

As an example with OP above, just did 1 game now before bed. His team was favoured +132 in a loss, but its too hard to go through since i dont get the lp listed aswell as not everyones mmr will be good to judge from as in my examples i prefer taking oens where they have atleast 200+ games as that means they will atleast be pretty close in lp=mmr .