I have been playing about with different ways of presenting team level Championship stats in recent weeks, and settled on the following approach (for now anyway); the Fancy Stat League Table.
These tables show the rank of a team for particular metrics – the higher the rank (or taller the bar), the better a team has performed in that metric compared to their rivals. An important limitation of these tables is that they provide no scale to the stats presented; Brighton sit one place above Middlesborough in terms of points per game, but by how much? The tables don’t tell you that.
So, why this approach?
Well, I think (hope) they are easy on the eye. The majority understand a league table and, personally, I find that the quicker I can understand a graphic, the better the graphic.
I did mess about with graphics displaying the raw numbers but unless you know the typical range of the metrics presented, this approach probably wouldn’t mean too much. Feel free to recommend alternative approaches, I’m all ears.
Anyway, here’s how all teams have performed so far, presented in the context of this weekend’s fixtures, but first a few words on each metric.
Points/game – this replicates actual league position
Points v Expected – this provides a view of performance in terms of bookies’ expectation, and provides an indication of over/under performance
Actual goals – for, against, and rate (for/total goals) – goal rate correlates very well to league position at the end of a season
Expected goals – as for actual goals but this provides some context in terms of the quality of chances taken and conceded. This is based on the excellent Ben Mayhew’s model which you can read more about on his blog – go check it out, there’s loads of great analysis across England’s professional game.
Finally Shots, total and on target – again these correlate well to final positioning however treat with caution, score effects, particularly at close game states (where a team is leading or trailing by 1 goal), and strength of schedule can skew these figures.
I’m looking forward to see how teams perform over the season and observe any regression. I hope also, at some point, to introduce form tables.
Final note, and a generalisation which may be worth exploring further; tables which are left hand heavy (points and goals) may suggest a level of over-performance, right hand heavy (expected goals and shots) might identify teams that deserve a break.