Hi all. It came to our attention over Friday beers yesterday that players in crappy teams still seemed to be polling quite well. When we investigated this we noticed a bug in the code which was stuffing up the score differences. Essentially, if Essendon had beaten Carlton by 100, the score difference column was +100 for all players in the game, and not -100 for Carlton Players. We fixed this and re-ran the model and for some players it has made a significant difference. For the big three, not so much, but several players in the top 25 have shifted significantly. Apologies for not picking up on this earlier – the last model wasn’t “wrong”, as the score difference variable did nothing, it just wasn’t as good as it should have been. We think this one looks better, and hopefully people hadn’t made any bets on Patrick Cripps and/or Dayne Beams as they probably look shaky now.

The above graph is players who predicted average votes shifted by 3 or more. Red numbers are the earlier version of the model, and blue is the new one. As you can see the hardest hits were players from the bottom of the ladder. Seb Ross has made a mockery of our earlier blog post and is now predicted to get an average of 19 votes. Bryce Gibbs seems too low, but we will investigate that. All in all, its a significant change, so have a good look!

The new pdf is available here: FatStats AutoZerrett 2017 Predictions V1.4

If this is your first time, the original 2017 predictions post is here and last years more thorough description of the process is here.

Please let us know if you spot any more bugs, its more than likely they exist.