Is Class More or Less Important In AFL Finals?

You'll hear it said about sport that class emerges when it's needed most. If that applies to football then you'd expect that better teams would be more likely to win games in the Finals than they are games in the regular home-and-away season.
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The Predictability of 2013

Friend of MAFL, Michael, e-mailed me earlier to ask about my claim that 2013 was on track to be the most predictable MAFL season ever, pointing out, quite correctly, that bookmaker favourites have been winning at about the same rate - perhaps even at a slightly higher rate - as they had been at the same time last year.
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Game Statistics and Game Outcomes

My first Matter of Stats blog looked at how game statistics, averaged across an entire season for each team, are predictive of key season outcomes like ladder position, competition points and MARS Ratings. This post summarises similar analyses, but here performed on a per-game basis
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Do Bookies Undervalue Team Performance Metrics?

In 2003 Michael Lewis' Moneyball was published, in which he related the story of Billy Beane, Oakland A's General Manager, and his discovery that the market for baseball players mispriced particular skills. Some skills that could be shown, statistically, as being associated with greater team success weren't recognised as valuable (for example, getting on base, as measured by On-Base Percentage), while other skills were over-valued because of an historical belief that they were related to success (for example, batting in runs, as measured by RBI).
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Which Teams Fare Better as Favourites?

In this blog, the next is a series in which I've been exploring the all-time MARS Ratings I created for every game from the start of 1897 to the end of the 2012 season, I'll be looking at how well each team has performed depending on the relative strength of its opponent, as measured by their MARS Rating. So, for example, we'll consider how well Collingwood tends to do when playing a team it is assessed as being much stronger than, a little stronger than, about as capable as, and so on.
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Does an Extra Day's Rest Matter in the Home and Away Season?

Whenever the draw for a new season is revealed there's much discussion about the teams that face one another only once, about which teams need to travel interstate more than others, and about which teams are asked to play successive games with fewer days rest. There is in the discussion an implicit assumption that more days rest is better than fewer days rest but, to my knowledge, this is never supported by empirical analysis. It is, like much of the discussion about football, considered axiomatic. In this blog we'll assess how reasonable that assumption is.
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Deriving the Relationship Between Quarter-by-Quarter and Game Victory Probabilities

In an earlier blog we estimated empirical relationships between Home Teams' success rate in each Quarter of the game and their Implicit Probability of Victory, as reflected in the TAB Bookmaker's pre-game prices. It turned out that this relationship appeared to be quite similar for all four Quarters, with the possible exception of the 3rd. We also showed that there was a near one-to-one relationship between the Home Team's Implicit Probability and its actual Victory Probability - in other words, that the TAB Bookmaker's forecasts were well-calibrated. Together, these results imply an empirical relationship between the Home Team's likelihood of winning a Quarter and its likelihood of winning an entire Game. In this blog I'm going to draw on a little probability theory to see if I can derive that relationship theoretically, largely from first principles.
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In-Running Models: Confidence Intervals for Probability Estimates

In a previous blog on the in-running models I generated point estimates for the Home team's victory probability at different stages in the game under a variety of different lead scenarios. In this blog I'll review the level of confidence we should have in some of those forecasts. More formally, I'll generate 95% confidence intervals for some of those point forecasts.
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Characterising AFL Seasons

I can think of a number of ways that an AFL season might be characterised but for today's blog I'm going to call on a modelling approach that I used back in 2010, which is based on Brownian motion and which was inspired by a JASA paper from Hal S Stern.
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Does Crowd Size Affect Game Outcomes?

Based on empirical evidence we know that there is a home ground advantage in AFL which, in part, might be attributable to the pro-Home team leanings amongst the majority of the crowd. In this blog I want to explore a slightly different question about the effects of the crowd: specifically, does the size of the crowd matter too?
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1897 to 2011 : Winners v Losers - Leads, Scoring Shots and Conversion

In the previous blog, among other things we analysed which quarter winning teams win. We might also ask about winnng teams, in what proportion of games do they trail at the end of a particular quarter, and how has this proportion tracked over the seasons.
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