Robert Younger (@figuringfooty) header
Robert Younger (@figuringfooty) profile picture

Backseat footballer, mathematician and ex-blogger. Performance Data Scientist @melbournefc

Melbourne, Victoria
Joined August 2015
Fair old night!
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New Expected Scores page now available 🟣Explore goalkicking accuracy and shot rating (2021-) 🟣View by player, team or AFL-wide 🟣View player shot charts 🟣Filter shots by season, shot type, distance and corridor/pocket wheeloratings.com/afl_xscore…
New website page is coming along nicely.
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This week we dove relatively deep into centre clearances, how much they are really worth and how teams move the ball away from the middle. To do this of course we focused on West Coast. abc.net.au/news/2024-04-13/u…
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Robert Younger retweeted
Does the outcome of tight matches play mind games on the umps as to which side they should give the votes to? The size of the gap between a 1pt win and a 1pt loss in the below suggests yes, it does. Using the margin is an obvious yet critical factor in predicting Brownlow voting.
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Robert Younger retweeted
Full results are in for 50 expert & media pundit preseason ladder predictions. Summary: Over the long term, Squiggle is going quite a lot better than any of them. I will be reposting this link once per day forever. squiggle.com.au/a-review-of-…
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Robert Younger retweeted
Champion Data's Daniel Hoyne provides some context around HOW Expected Score as a statistic should be used. @SENSportsday | #AFL
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Robert Younger retweeted
Quite simply the most wide-open battle for finals in #AFL history. The computer found over 230,000 possible permutations of the Final 8. Expect 5 teams to finish with 54+ and 8 teams to end up on 44-52 points. 48 won't be enough, unless you have both percentage and luck 1/5
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Robert Younger retweeted
Am really pleased to share this paper as my first piece of authored work. Hopefully it can add to commentary surrounding teams' forward line strategy in the AFL. You can check it out at the link below. #sportsanalytics #sportsdata #sports #analytics #afl
New from @DTS098: Discovery and Characterisation of Forward Line Formations at Centre Bounces in the Australian Football League - mdpi.com/1424-8220/23/10/489… -9721 CBs from 203 matches in 2021 -How do teams position their FWD line players? -What player role combinations are used?
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Robert Younger retweeted
What does the average #AFL player look like? Layering semi-transparent AFL headshots of all 2022 players yields this bloke:
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🚨 Guide to Sports Analytics 📊 New design & we now cover 4! softwares in-depth (R, Python, Tableau, SQL). In total, links to 500+ tutorials, 250+ data sources, 125+ accounts to follow, 50 books, 40 cheatsheets, 40 papers & more. All in ONE place!! ⬇️ docs.google.com/spreadsheets…
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Hard to imagine a worse performance (both onfield and off) than that by the aussies. You can write it off as India being good, but England won’t be pushovers by any means.
So it’s pretty clear now that England are the ones to reap the first mover advantage of analytics in short form cricket. They’re incredibly well drilled, innovate (weakest bowler opening the bowling, fewer yorkers at death etc) and set plans to opposition so well.
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Robert Younger retweeted
2022 is done and dusted! Thought I'd put together a super thread of all the analysis, visualisation and data exploration I got up to this year.
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So it’s pretty clear now that England are the ones to reap the first mover advantage of analytics in short form cricket. They’re incredibly well drilled, innovate (weakest bowler opening the bowling, fewer yorkers at death etc) and set plans to opposition so well.
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Nathan Leamon @Numb3z deserves massive credit for all England’s success. It’s been great to see the influence of quality analysis. Just a shame it was the poms to get there first.
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Robert Younger retweeted
Looking for an experienced analyst to lead data strategy with a sports governing body. Based in Melbourne, Australia. Contact me to discuss. First of a few jobs becoming available in next couple of weeks (both here at VU and external).
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A nice snapshot of the journey in which sports analytics is going on as it matures as an industry.
I hadn't gone into StatsBomb conference intending to write something about it But six analogies, one Warholism, and 2100 words of thoughts later here we are Some thoughts about where 'the edge' of analytics is in Autumn 2022 getgoalsideanalytics.com/c/w…
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We are looking for a new addition to our team as Data Team Lead. If interested, take a look at the link below. linkedin.com/jobs/view/32483…
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Robert Younger retweeted
Twice in the past fortnight Richmond has been involved in matches that have been decided on the final score - and twice it has lost. This year the Tigers are 0-3 in these games: 2: Conceded score to lose 1: Missed score to lose They are ranked last in these games since 2010.
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Expected Scores are back in the news. There's unsurprisingly a lot of misunderstanding, so now may be a good time for a primer. What are they? What can they help us understand about the game? And crucially, what can't they measure?
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Like any stat, Expected Score has it's strengths and weaknesses, and these can be hard for non-statisticians to fully understand. But if used wisely it can add hugely to our understanding of the game, so hopefully it gets through it's teething problems in the media.
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Oh, and the concept for Expected Score has been around in other sports for well over a decade. Nobody in Australia "invented" it.
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