2018/19 season stats (1 Viewer)

From here Ben Mayhew’s excellent Blog https://experimental361.com/2019/05/05/scatter-graphics-league-1-2018-19/

Shot dominance

First of all, here is how the number of shots taken by each club compares with those they face in return. The average number of shots taken per match is on the horizontal and the average number faced is on the vertical, so bottom right (take plenty, allow few in return) is good while top left (take few, allow plenty) is bad. The stripes are like contours: the greener the stripe, the better the performance (and vice versa for red).



Attacking effectiveness

Now let’s look at attacking alone. The horizontal axis stays the same as in the graphic above, but now the vertical shows the average number of shots needed to score each league goal. Therefore bottom right is good (taking lots of shots and needing fewer efforts to convert) and top left is bad:



Defensive effectiveness

Next let’s look at the defensive situation – basically take the above chart and replace the word “taken” for “faced” on both axes. Now top left is good – facing fewer shots and able to soak up more per goal conceded – and bottom right is bad:



Expected goals

Finally here’s an attempt at correcting the first graphic for the quality of chances created and allowed, using the same “expected goals” values that power my shot timelines (explained here). The reason for doing this is that the results tend to correlate more strongly with performance than when we treat all shots equally:



Kind of sums up our season really. Better than most teams but just not quite good enough for promotion.


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Season Now-There are two lines:

The blue line shows the rolling average of a club’s goal difference over the last 10 league games;
The red line shows the rolling average of their expected goal difference, based on the quality of chances they’ve created and faced.
Comparing these two allows us to see not only how a club’s performances have changed over time, but also whether there were any differences between the balance of chances created (a useful measure of underlying performance) and goals scored.

These are shaded as follows:

Blue shaded areas are where goal difference is higher than chances created, suggesting an overachievement;
Red shaded areas show the reverse, where the balance of chances was healthier than the actual goal difference, signalling underachievement.
Over the long term we’d expect the two lines to converge unless there’s a significant difference in a club’s attacking or defensive skill compared to the average for the division. We can’t tell from the data alone whether skill or luck is the cause, but the longer a difference persists the more I’d suspect the former.



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