NEED IT IN EXCEL (READ ALL DETAILS AND THEN BID PLEASE)
Budget: $30 – $250 USD
I’m looking for someone that can build a spreadsheet that calculates both RPI and ELO ratings to rank sports teams. I can a separate excel sheet that calculates RPI and a google sheet that calculates ELO but it’s a lot of time entering the scores into both sheets.
https://docs.google.com/spreadsheets/d/1bRBZKDjtjN5NpyOFmo-BQrYgJ_CXRiG8sHXyKX9jPh4/edit?usp=sharing
my goal is to be able to have an accurate team strength index for team that never play each other but my have similar opponents
so currently I am having to enter the game scores into both sheets separately, I would like to only have to enter each game score one time and have a calculation that includes both the RPI and ELO rating into one number.
I use this spreadsheet to calculate the ELO it has proven to be very accurate, but I do not know how the math is calculated behind the formulas
Elo’s central assumption was that the chess performance of a player player in each game is a random variable, and that it follow a normally distributed bell-shaped curve over time. Thus, while a player might perform significantly better or worse from one game to the next, the mean value of their performances (a reflection of their true skill) would remain the same. The assumption here is that this mean value of the performances for any given player only changes slowly over time. The difference in the ratings between two players serves as a predictor of the outcome of a match. If players A and B have ratings Rᴬ and Rᴮ, then the expected scores are given by: The formulae for calculating expected scores given Elo ratings If two players have equal ratings (Rᴬ = Rᴮ), then the expected scores of A and B evaluate to 1/2 each. That makes sense — if both players are equally good, then both are expected to score an equal number of wins. Sometimes when a player’s actual tournament scores differs from their expected scores, the scores need to be adjusted upwards or downwards. Elo’s original suggestion, which is still widely used, was a simple linear adjustment proportional to the amount by which a player over-performed or under-performed. The maximum possible adjustment per game, called the K-factor, was set at K = 16 for masters and K = 32 for weaker players. If Player A was expected to score Eᴬ points but actually scored Sᴬ points, the player’s rating is updated using the formula: Formula for updating a player’s ELO rating Let’s consider an example: Anand has a rating of 2600 Boris has a rating of 2300 Their expected scores are therefore: Anand: 1/1+10^(2300–2600)/400 = 0.849 Boris: 1/1+10^(2600–2300)/400 = 0.151 If the organizers determined that K =16 and Anand wins, then the new ratings would be: Anand = 2600 + 16 (1 – 0.849) = 2602 Boris = 2300 + 16 (0 – 0.151) = 2298 If the organizers determined that K =16 and Boris wins, then the new ratings would be: Anand = 2600 + 16 (0 – 0.849) = 2586 Boris = 2300 + 16 (1 – 0.151) = 2314
https://docs.google.com/spreadsheets/d/1VSmglYXT8Rl27ORacShNgDMLUTgByTwKVMKy-Wg3EWQ/edit?usp=sharing
https://docs.google.com/spreadsheets/d/1bRBZKDjtjN5NpyOFmo-BQrYgJ_CXRiG8sHXyKX9jPh4/edit?usp=sharing
my goal is to be able to have an accurate team strength index for team that never play each other but my have similar opponents
so currently I am having to enter the game scores into both sheets separately, I would like to only have to enter each game score one time and have a calculation that includes both the RPI and ELO rating into one number.
I use this spreadsheet to calculate the ELO it has proven to be very accurate, but I do not know how the math is calculated behind the formulas
Elo’s central assumption was that the chess performance of a player player in each game is a random variable, and that it follow a normally distributed bell-shaped curve over time. Thus, while a player might perform significantly better or worse from one game to the next, the mean value of their performances (a reflection of their true skill) would remain the same. The assumption here is that this mean value of the performances for any given player only changes slowly over time. The difference in the ratings between two players serves as a predictor of the outcome of a match. If players A and B have ratings Rᴬ and Rᴮ, then the expected scores are given by: The formulae for calculating expected scores given Elo ratings If two players have equal ratings (Rᴬ = Rᴮ), then the expected scores of A and B evaluate to 1/2 each. That makes sense — if both players are equally good, then both are expected to score an equal number of wins. Sometimes when a player’s actual tournament scores differs from their expected scores, the scores need to be adjusted upwards or downwards. Elo’s original suggestion, which is still widely used, was a simple linear adjustment proportional to the amount by which a player over-performed or under-performed. The maximum possible adjustment per game, called the K-factor, was set at K = 16 for masters and K = 32 for weaker players. If Player A was expected to score Eᴬ points but actually scored Sᴬ points, the player’s rating is updated using the formula: Formula for updating a player’s ELO rating Let’s consider an example: Anand has a rating of 2600 Boris has a rating of 2300 Their expected scores are therefore: Anand: 1/1+10^(2300–2600)/400 = 0.849 Boris: 1/1+10^(2600–2300)/400 = 0.151 If the organizers determined that K =16 and Anand wins, then the new ratings would be: Anand = 2600 + 16 (1 – 0.849) = 2602 Boris = 2300 + 16 (0 – 0.151) = 2298 If the organizers determined that K =16 and Boris wins, then the new ratings would be: Anand = 2600 + 16 (0 – 0.849) = 2586 Boris = 2300 + 16 (1 – 0.151) = 2314
https://docs.google.com/spreadsheets/d/1VSmglYXT8Rl27ORacShNgDMLUTgByTwKVMKy-Wg3EWQ/edit?usp=sharing