Here are the highest and lowest possible positions that each Football League and National League club can occupy after this weekend’s fixtures. If you scroll to the bottom I’ve also added in a link to the Premier League version. For each division I’ve drawn lines under the last play-off spot, mid-table and the last spot above the relegation zone on both “axes”
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Seeing as it ended up being a relatively popular exercise last week, I’ve again calculated the highest and lowest possible positions that each Football League and National League club can occupy after this weekend’s fixtures. If you scroll to the bottom I’ve also added in a link to the Premier League version. For each division I’ve drawn lines under the last play-off spot,
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There have been just enough matches played for the shot numbers to start settling down, so I thought I’d give a first airing of the season to the three scatter graphics I track for each division. These are explained here if you haven’t seen them before. Shot dominance First of all, here is how the number of shots taken by each
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Another new thing from me this weekend. I did some analysis at work recently looking at the possible permutations of results for the European Championship qualifiers (e.g. how many different ways are there of a specific nation qualifying etc) and I wanted to try and apply this to domestic leagues. What I’ve done I’ve written some code that runs through every possible combination
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Following on from my earlier post where I looked at how each of the Football League and National League clubs had fared using expected goals, I wanted to look at how the chances they’d created and allowed compared with the actual goals they’d scored to see which sides have been under and over-achieving. As a reminder, expected goals are calculated by giving each shot a
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I couldn’t resist having an early peek at how the Football League and National League clubs have been doing overall. What I’ve got here are the “shot dominance” graphics – comparing the average number of shots taken and faced by each club – for the season so far. Bear in mind that the strength of each side’s opponents will still have a large
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In case you missed the flurry of posts yesterday, I’ve built a lower league ratings system that includes a calculation of expected goals. If you’re not familiar with these, it basically boils down to giving every shot a value based on how many shots of that type the average team needs to score, rather than treating them all equally. For example if League 2 clubs
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Following on from my earlier post introducing the new “E ratings” I’ve been experimenting with, I thought it would be helpful to illustrate their use by reviewing each division from last season. E ratings are my newest creation, combining the concept of an “expected goals” measure of shot quality with an Elo-style rating system, to track the attacking and defensive performances
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Following a successful trial earlier this season, I’ve produced an animated minute-by-minute league table for the Conference. The way it works is as follows: Each graphic cycles through every club in descending order of their final league position (on an infinite loop with each frame lasting 2 seconds). The line shows what the highlighted club’s league position would have been in an
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This is an update of a previous post for the 2014/15 Conference season, but replacing the graphics with the new versions I’ve developed. While I’m really happy that the scatter graphics I’ve been churning out for the past four years continue to be so well-received, I’ve long wished for them to look a bit prettier. During last season, @bootifulgame and I produced an
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Experimental 3-6-1 
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