plusSixOne
@plusSixOneblog
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Data driven Sports analysis. By @jamesday87
Melbourne
Joined April 2016
Full disclosure - I’m a lifelong Hawks fan and lived in Brisbane for 10 years with fond memories of playing footy in Queensland
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Objective ranking of who I would like to see win the #AFL premiership, using a GUT based model Brisbane St Kilda Bulldogs West Coast Power Richmond Collingwood Geelong
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Fellow @FMI_TL ers, please join me in offering huge thanks to FootyMaths for forging on and putting in all those hours despite the especially trying circumstances in this weirdest of years. Not even a global pandemic could stop this competition. Hip hip ...
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I guess you could use the teams existing For and Against to estimate the end of season For/Against and then adjust that to match the Avg Margin from my match predictions? Haven't thought a lot about this yet and how that would work in early season sims
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I'm assuming the solution here is just to produce match predictions that have actual For and Against rather than just Margin but wondering if anyone has addressed this before?
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AFL Wonk Tweeps on @SquiggleAFL (or others!) who only produce estimated Margins, how do you calculate ladder percentage? I just use `average margin` as a kind of surrogate but that falls down towards the end of the season where percentage matters
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Also - for a slightly more more wonky take on which games to watch, give @MatterOfStats simulations posts a read to see his 'match importance' metrics! https://t.co/QsPfxtoDzO
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Obviously not a guarantee but wouldn't call it precarious! Perhaps, as @Jameshi86365839 mentioned, some nervousness in the nineties for long suffering Saints fans
@plusSixOneblog @urniurl @SquiggleAFL Yeah I’m feeling more nervous nineties than confidence. Cheers for the update
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Nice piece although this point on St Kilda is interesting. Quite a bit of noise from Saints fans I know that echo this sentiment! The collective Squiggle models have them as a 94% chance to make the 8, while the market has them at 93% https://t.co/eyr6SfQWnH
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For anyone using #fitzRoy - just be aware that the `get_fixture` code is broken. You can actually use `get_afl_fixture()` which is working, it just will have slightly different team names/structure to the normal `get_fixture`
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OK so I *think* this is working. There are some bugs in `fitzRoy` that I need to fix but think I've got this working and making a bit more sense, although haven't got the brain capacity to fully investigate tonight! https://t.co/MuYgSI7Q4b
Leaving for posterity but thanks to @Jameshi86365839 for pointing out some inconsistencies. I think there is a bug in the final round matches that is messing things up. Will investigate tonight and re-run the sims!
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Leaving for posterity but thanks to @Jameshi86365839 for pointing out some inconsistencies. I think there is a bug in the final round matches that is messing things up. Will investigate tonight and re-run the sims!
Horror week for @melbournefc and their finals chances. @stkildafc and @CollingwoodFC almost locked in, with @GWSGIANTS heavy favorites for the last finals spot https://t.co/MuYgSI7Q4b
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Horror week for @melbournefc and their finals chances. @stkildafc and @CollingwoodFC almost locked in, with @GWSGIANTS heavy favorites for the last finals spot https://t.co/MuYgSI7Q4b
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Have also updated the #AFL mens predictions page showing probabilities of various finishing positions and finals results https://t.co/0ttZUeD4om
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As footy twitter blows up with it's periodic "stats are useless" takes, it's worth noting: Champion Data Player Ratings, like any single number, are an oversimplification of a player's performance.
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#AFL Men's simulations are fresh out of the oven! A note to those interested, these should update every day during a round if you can't wait for the round to finish 🎉 https://t.co/a9iMIV4C7U
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