Visualising the Championship: the Shot Worm 2014/15

A short post inspired by (stolen from) this chart by David Sumpter. I looked at visualising how teams’ shots for and against changed throughout the season. The result is a connected scatter plot showing teams’ shots for versus shots against. Naturally, the best teams tend to be towards the bottom right and that’s where teams should be aiming to be. Teams above the dotted line are being outshot by their opponents, while teams below the dotted line are taking more shots than their opponents. The shots are grouped into rolling 10 game averages (shots per game).

Rplot49

Points of interest:

  • Brentford’s late streak into elite shot dominance numbers (shown by being far to the right) is driven by their one-off thrashing of Blackpool. They’re a good side, but not quite that good (yet).
  • Charlton spent almost their entire season above the line (compare their worm to Blackpool’s for instance). They have been a pretty dire team by the shots numbers all year and have been kept up by a large number of draws and unsustainable conversion numbers. Leeds are another team in this category.
  • Despite gathering the plaudits early on in the season, Derby’s shots numbers were consistently fairly average and they were probably fortunate to be flying high for so long, driven as they were by unsustainably high conversion rates.
  • Norwich were a truly elite shots team and were probably unlucky to have to go up via the playoffs.
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Visualising the Championship: the Age-Utility matrix

The Age-Utility matrix is (if you’ll excuse the self-important name) something I came up with to show squad balance across different age bands. By plotting the % of maximum minutes played (y axis) vs the age of each player (x axis), we can get an approximate idea of squad balance. For instance, it would be undesirable to be relying lots of older players playing a lot of minutes (especially without younger players ready to come in to replace them), because as they begin to decline as a result of normal ageing, they will need to be replaced. I have also included a marker for players on short term contracts (loans or single year deals) because, if continuity is desirable, then having lots of minutes devoted to players on short term deals is not wanted. Finally, there is also an indicator for an estimate of peak years based on the league average distribution of minutes. This is, of course, an estimate, as the age curve varies depending on myriad factors, such as position, injury history and the like.

Example: AFC Bournemouth

Rplot11

  • We can see the majority of Bournemouth’s minutes are coming from peak age players, with few older players, perhaps a contributing factor to their success this season. Does this age balance allow Bournemouth to play at a higher intensity at times?
  • There are also few loanees, with only Boruc playing a major role.
  • Likewise, there is a clearly demarcated set of core players (top group) and squad options (middle/bottom). It is reasonable to suggest that Bournemouth’s team cohesion has also been a factor in their success so far this season.

Visualising the Championship: Historical context charts

Last week, I wrote a post on Millwall, mentioning that their last 5 games had been historically bad. In fact, at the point of writing, Millwall had recorded the third worst share of Shots on Target over a 5 game stretch since the 2004/05 season. However, is there a way to easily show just how bad a team’s recent form has been compared to past teams’?

Historical context charts

In order to quickly compare teams’ performance to past Championship teams, I have constructed a set of charts looking at the proportion of teams with a superior score (shaded orange), along with where on the bell curve their performance lies (black/orange boundary) for four metrics: Total Shots Ratio, Shots on Target Ratio, Goal Ratio and Points Per Game.

For instance, the graphic for the same Millwall streak as in the post mentioned earlier comes out as this:

histcomp

As we can see, Millwall’s performance in each of these metrics is at the lower extreme. Their performance has been terrible; almost every team in the Championship since it’s rebranding has performed better over 5 games (in all of their 5 game streaks) than Millwall have here, as shown by the almost completely orange histograms.

For comparison, this is what a good team looks like:

histcomp

This shows Bournemouth’s most recent 5 games in their historical context. As we can see, despite their accumulation of points being merely “good”, their domination of Shots, Shots on Target and Goals tallies over recent weeks has been excellent.

Hopefully these are faulty intuitive and a useful tool for putting extreme performances into some sort of context.