A League 2 blog with an overwhelmingly pro-Torquay United bias
I often consider clubs’ form when crafting my predictive previews, but frequently fall foul of various stumblings and resurgences as fortunes change and runs are ended. This has caused me to wonder whether certain sides are inherently more prone to going on long unbeaten or winless runs than others, and therefore how useful a team’s form is as an indicator of what they’ll do next.
For example, my beloved Torquay seem to be a team affected by momentum: they began this season by continuing an eventually club record-breaking run of clean sheets, but followed this up with a disappointing winless stretch and are currently enjoying another unbeaten sequence. To try and understand how typical these patches of form are, I employed my clumsy programming skills to crunch all of this season’s League 2 matches so far and calculate the average length of all the runs that each team went on, which I then plotted below:
The length of each bar corresponds to the average length of each club’s runs this season, including both unbeaten and winless sequences. Teams towards the top have, on average, gone on longer runs that those at the bottom, whose form is more volatile. Northampton’s position at the summit (with an average run length of 4 matches) is largely due to the distorting effect of their recent 18-match winless streak, although they’ve enjoyed some more modest sequences too, such as an 8-game unbeaten run in mid-season. Bradford’s lowly placing is due to their results being much less predictable: the longest run they’ve racked up this season is a 6 match winless streak, and only once have they gone more than 2 matches without defeat. As I suspected, Torquay’s tendency to do things in sequences puts them towards the top of the list.
What I conclude from this is that while there are certainly sides in the division who are more likely to put together runs of form than others, you need to be able to read between the lines. Crewe’s low placing is due to them being lethal at home but terrible away, which prevents them from racking up any lengthy sequences of either variety. The lottery of the fixture calendar probably plays a part too, with some teams having clusters of tough and easy games while others have their ‘banana skins’ spread more evenly throughout the season.
One season’s data is almost certainly not statistically significant and there’s probably a much more mathematically credible way of doing this, but I thought I’d share this initial view to see if it resonated with my fellow League 2 fans and whether it was something of interest.