It’s still early days in the EFL season but I wanted to take a quick look at which attacking players were showing the most promise. Using the same expected goals data that powers my timelines and scatter graphics, I ranked every player in descending order of the quality of goalscoring chances they’d been on the end of. I then filtered
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As usually happens in the early part of the season, I got impatient while waiting for a meaningful amount of match data to build up and blasted out some very early scatter graphics showing how the EFL clubs’ expected goals tallies were looking so far: It's way too early to draw conclusions, but curiosity got the better of me so
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With the new season imminent I just wanted to provide a quick update on what I’ve got planned for the blog and where things are at the moment. A slow start… The blog’s output will unfortunately be a bit patchy for the first few weeks of the new season. I’ve had a few exciting new work projects land over the
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I’ve been looking at squad churn – how much each club’s squad changes between seasons – for a fair few years now but I’ve never been all that happy with how the graphics turned out (apart from that one year I got Bootifulgame involved: http://matchstory.co.uk/portfolio/player-churn-the-championship/). Therefore I thought it was worth having another stab at it and managed to come
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While there’s no football to cover, I’ve been gradually chipping away at my “to do” list. Most of this is tidying up and improving code, but there are also a lot of questions I’ve been asked and hadn’t gotten around to answering. When I produced a recent mid-season batch of my attack breakdown graphics I was asked whether I could create
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I did some analysis at work lately that turned out to be way more popular than I was expecting: this graphic for bwin looking at which outfield players have spent the most time on the bench in Europe’s big five leagues this season. It ended up on quite a few newspaper sites and apparently the James Tarkowski stat – the fact
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I spotted a PA interview with David Moyes yesterday in which he sounded surprisingly – and uncharacteristically – upbeat: David Moyes: "We still think we have got a good chance (of survival) #SAFC https://t.co/eQi0EbOYcU — PA Dugout (@PAdugout) April 25, 2017 This doesn’t chime with how my model sees things. It’s pretty much given up on both Sunderland and Middlesbrough,
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There’s a lot of interest in the League 2 play-off race (and the League 1 relegation battle, but that’s a bit morbid), so I thought I’d road-test another graphic from the “half-finished” folder on my laptop. What these do is to split out the weekly model simulations I run to show the spread of predicted finishing positions and points totals
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I saw plenty being made of Sunderland’s current barren run after their 3-0 defeat to Manchester United earlier today and realised that I had half-built a way of working out how long each club’s longest goalscoring drought is from the last time something like this happened. I was able to polish it off pretty quickly and run it for all four
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With Rotherham’s relegation confirmed this weekend and the season fast running out of matches, I thought it was worth dusting off another post from last year which looked at what was still mathematically possible (no matter how unlikely) in each division. This is a rare situation when the limited data available at National League level isn’t a hindrance to me including
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Experimental 3-6-1 
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