
Analysis of AFL
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Analysis of AFL
@anoafl
Analysis of AFL Variance - Semi Explained by @roberto_boberto For AFL data check out use #fitzRoy https://t.co/Km3qIjkR8G







Feelin Fuzzy? @OSPpatrick and I work through identifying players using fuzzy joins to standardize names of sports ball players against that in your database. We use two different techniques, using base #rstats agrep and #tidyverse -esq {fuzzyjoin}! Bit.ly/TidyX_Ep127

Had lots of fun doing this piece on the team behind @aflwfantasy - why they're dedicating hours of volunteer time to grow fan engagement in #AFLW and to improve conditions for #womeninsport more broadly. #aflwfantasy #FantasyFootball abc.net.au/news/2022-09-2… via @ABCaustralia

I guess poor imitation is the sincerest form of flattery.

“Expected scores” is a concept invented by Champion Data, an alternative reality in which there’s a statistical likelihood that a goal, behind or miss will be scored from a particular position. In this parallel universe, Richmond are equal with Geelong. theage.com.au/sport/afl/shou…



