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Pythago NRL

Rugby league Elo models, player ratings and statistics

Category: Primers

Primer – Introducing Pythago World Rankings

While the recent RLWC was on, I couldn’t help but notice that the RLIF had Scotland pegged as the world’s fourth best team. Scotland hadn’t won a game since 2014 and even that was against Ireland. Since then, they’d lost to Australia, England, Ireland, Wales and France. I also got frustrated because a fifteen second… Read More Primer – Introducing Pythago World Rankings

January 16, 2018March 5, 2018 pythagonrl

Primer – How does the Collated Ladder work?

The Collated Ladder takes in two inputs: The projected number of wins for each club from the Stocky The projected number of wins for each club from Pythagorean expectations Put simply, the Collated Ladder is an average of these two numbers, with a 2:1 weighting towards the output of the Stocky, rounded to the nearest… Read More Primer – How does the Collated Ladder work?

April 19, 2017January 14, 2018 pythagonrl

Primer – How does the Stocky work?

The Stocky, which is short for stochastic simulation, is a Monte Carlo simulation of the season using Elo modelling to work out what the outcome of that season might be. The basic premise of a Monte Carlo simulation is that if you have a few pieces of the puzzle, an idea of how they relate… Read More Primer – How does the Stocky work?

April 12, 2017January 14, 2018 pythagonrl

Primer – What variables do the Elo models use?

In my previous primer on Elo ratings, I talked about different ways of calculating Elo ratings with a view of measuring form and/or class. This primer will look in a bit more depth at how I arrived at the specific numbers for the variables. The main variables in an Elo model are: Starting ratings (discrete… Read More Primer – What variables do the Elo models use?

April 5, 2017January 14, 2018 pythagonrl

Primer – How do Elo models work?

Short answer: with a lot of time spent in Excel and Google Sheets. Long answer: It depends on what you want to do. I introduced the Elo rating system in a previous primer. Now it’s time to put it to work. I think most sport’s fans would agree with the following definitions of form and class… Read More Primer – How do Elo models work?

March 30, 2017January 14, 2018 pythagonrl

Primer – What is a Pythagorean expectation?

Pythagorean expectation is the idea that you can calculate a team’s winning percentage based solely on its for and against. It originated with baseball nerds but, according to its Wikipedia article, has been adapted for other sports. It is also where the name of this site came from. Pythago is basically what Pythagoras would have been if… Read More Primer – What is a Pythagorean expectation?

March 30, 2017January 3, 2018 pythagonrl

Primer – What are Elo ratings?

Elo ratings originated in chess as a way to rate different players. A player starts with a rating of 1500 by convention and then the rating goes up or down depending on whether the players wins or loses. The player’s rating will change proportionally to the rating of their opponent: if the player beats a very… Read More Primer – What are Elo ratings?

March 30, 2017January 14, 2018 pythagonrl

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