Chess ELO Calculations

Author

Mubin Ejaz

Approach:

I will start from where I left off in the project. I have two columns which have Prerating and average for every player. Although my final table and dataframe skipped the column that has which player they played with, I still kept a data frame CombinedData that have the round information.

I will use that infomation, so the formula of ELO calculation is (Chessigma.com)

R_A –> player A’s current rating
R_B–> Player B’s current rating
E_A –>Player A’s expected score (a value between 0 and 1, where 1 means a certain win, 0.5 means an even match, and 0 means a certain loss

I’ll mutate and have a new column that’ll have E_A and another column for R`_A (new ratings, formula is given in bold next)

It seems like the assignment wants us to get to the point to find the new rating for every user by

R`_A = R_A + K(S_A+ E_A)

Usually people us K (K factor) to be 32 as default. the higher the K value, the faster the rating change. You chose higher K value for new player.

You can add options to executable code like this