Reoptimisation and the Fear of Overfitting : ChiPS 2016

Richard McElreath, in one of the lectures from his Statistical Rethinking course on YouTube aptly and amusingly notes that (and I'm paraphrasing) models are prone to get excited by exposure to data and one of our jobs as statistical modellers is to ensure that this excitability doesn't lead to problems such as overfitting.

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On the Relative Importance of Offensive and Defensive Ability in VFL/AFL History

In the previous post here I introduced MoSSBODS 2.0, a Team Rating System design to provide separate Offensive and Defensive Ratings for teams in the VFL/AFL. Today I want to explore the relationship between teams' Ratings and their on-field success.

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An Improved VFL/AFL Team Rating System: MoSSBODS 2.0

Earlier this year in this blog, I introduced the MoSSBODS Team Rating System, an ELO-style system that provides separate estimates of each team's offensive and defensive abilities, as well as a combined estimate formed from their sum. That blog post describes the main motivations for a MoSSBODS-like approach, which I'll not repeat here.

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Best and Worst AFL Teams 2005 - 2015: A MoSSBOD Perspective

In the last blog on this part of the site I introduced the MoSSBOD Team Rating System, the defining characteristics of which were that it Rated teams based on Scoring Shot Production and Concession and that it provided both a Defensive and an Offensive Rating for all teams.

Today I want to explore the history of those Ratings across the last decade to see what MoSSBOD has to say about the strongest and weakest Offensive and Defensive teams across that period.

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How Often Does The Best Team Win The Flag?

Finals series are a significant part of Australian sporting life. No professional team sport I know determines its ultimate victor - as does, say the English Premier League - on the basis of a first-past-the-post system. There's no doubt that a series of Finals adds interest, excitement and theatre (and revenue) to a season, but, in the case of VFL/AFL at least, how often does it result in the best team being awarded the Flag?

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A Comparison of SOGR & VSRS Ratings

Earlier posts on the Very Simple Rating System (VSRS) and Set of Games Ratings (SOGR) included a range of attractive graphs depicting team performance within and across seasons.

But, I wondered: how do the two Systems compare in terms of the team ratings they provide and the accuracy with which game outcomes can be modelled using them, and what do any differences suggest about changes in team performance within and across seasons?

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Set of Games Ratings: All Teams' Charts

The Set of Games Ratings post from late December introduced a twist on Tony’s VSRS concept. For any given set of games, the SOGR approach produces a rating for each team indicating its relative scoring ability within those games. Each SOGR model is optimised for the set of games on which it was fitted (in the least squares sense).

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The Dynamics of ChiPS Ratings: 2000 to 2013

Visitors to the MatterOfStats site in 2014 will be reading about ChiPS team Ratings and the new Margin Predictor and Probability Predictor that are based on them, which I introduced in this previous blog. I'll not be abandoning my other team Ratings System, MARS, since its Ratings have proven to be so statistically valuable over the years as inputs to Fund algorithms and various Predictors, but I will be comparing and contrasting the MARS and the ChiPS Ratings at various times during the season.

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Introducing ChiPS

In years past, the MAFL Fund, Tipping and Prediction algorithms have undergone significant revision during the off-season, partly in reaction to their poor performances but partly also because of my fascination - some might call it obsession - with the empirical testing of new-to-me analytic and modelling techniques. Whilst that's been enjoyable for me, I imagine that it's made MAFL frustrating and difficult to follow at times.

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Set of Games Ratings: A Comparison With VSRS

A few weeks back, Tony introduced the Very Simple Rating System (VSRS). It’s an ELO-style rating system applied to the teams in the AFL, designed so that the difference in the ratings between any pair of teams plus some home ground advantage (HGA) can be interpreted as the expected difference in scores for a game involving those two teams played at a neutral venue. Tony's explored a number of variants of the basic VSRS approach across a number of blogs, but I'll be focussing here on the version he created in that first blog.

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Estimating Team-and-Venue Specific Home Ground Advantage Using the VSRS

In the Very Simple Rating System as I've described it so far, a single parameter, HGA, is used to adjust the expected game margin to account for the well-documented advantages of playing at home. We found that, depending on the timeframe we consider and the performance metric that we chose to optimise, the estimated size of this advantage varied generally in the 6 to 8-point range.
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Optimising the Very Simple Rating System (VSRS)

In the previous blog, introducing the VSRS, I provided optimal values for the tuning parameters of that System, optimal in the sense that they minimised either the mean absolute or the mean squared error across the period 1999 to 2013
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A Very Simple Team Ratings System

Just this week, 23 year-old chess phenom Magnus Carlsen wrested the title of World Champion from Vishwathan Anand, in so doing lifting his Rating to a stratospheric 2,870. Chess, like MAFL, uses an an ELO-style Rating System to assess and update the strength of its players.
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MARS Rating Changes and Scoring Percentages: 1897-2013

The idea for this blog sprang from some correspondence with Friend of MAFL, Michael, so let me start by thanking him for being the inspiration. Michael was interested in exploring the relationship between team performances and the resulting change in their MARS Ratings across a season, which I'll explore here by charting, for each team and every season, the for-and-against percentage they achieved in all games including Finals, and the change in their MARS Rating per game during that same season.
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Another View of All-Time AFL Team MARS Ratings Post the 2013 Season

Recently I'd been noticing some traffic to the site from the Big Footy website where the Forum members had been discussing the relative strengths of Bulldogs teams across VFL/AFL history. That, coupled with my continuing desire to become more proficient in the ggplot2 R package of Hadley Wickham, dragged me out of my off-season blog malaise to perform the analyses underpinning this current posting.
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