What's the Most Important Stat to Convert Skeptics of Analytics?
This is a really good question and one that I find myself thinking about quite a bit as we at StatsBomb start interacting more with media and potentially with football clubs. For the most part, I think the answer depends on the audience.
In the last week, I have seen NPG90 (non-penalty goals per 90) used all over the damned place, including in a Paolo Bandini piece in The Guardian and Gabriel Marcotti either on ESPN or in the Wall Street Journal. This was definitely not happening a year ago. Smart journos know that this type of adjusted rate stat tells you a lot more about “useful” goal scoring than simply looking at who has the most goals in a league, and it’s gaining traction in the mainstream.
The owner of Squawka tweeted a leading goalscorer chart for the Premier League yesterday and a wave of derision followed after it. Not because people don’t like stats, but because it gave the same weight to penalties as to other goals. The world is changing fairly quickly on this at least.
I also like the key pass stat, since it adds a lot more information about which players are dangerous passers that are setting teammates up for shots versus those that are merely involved in the game. However, I think that particular stat is just a touch too abstract for popular acceptance right now. Europeans are barely aware of assists – moving one step beyond that into “passes that create shots” is probably a step too far.
At the team level, I think we’ll see ExpG (Expected Goals) take off like a rocket as teams become more analytically aware. The reason for this is because it creates clear points of actionable data for managers, players, and Directors of Football to talk about. Everyone involved in football knows there is a lot of luck in the game, but having metrics that try to cut through the luck and look at what actually happened in a match is extremely useful.
This is already happening with some teams in hockey. There was a story from Mirtle I read last week about coaches coming to the analysts immediately after the match to check on their PGS (probable goals scored) stats so that they could then have an objective point of reference to talk to the team and media after the game. Everyone involved in football should be evaluating via process more than via outcome, and I think you will see that happen more and more in the medium term.
None of the ExpG models are perfect yet, but they will become more precise in time, and as more data becomes available. In the meantime, what we have now is far better than nothing, or even what the world had access to a year ago.
With regard to conversion of fans, a lot of it comes down to comfort levels with numbers, and some of that involves simply seeing numbers used to compare players and teams on a regular basis. Fantasy football certainly seems to help with this (and I have been told by many FF fanatics that our site is SUPER helpful with picking their teams, despite the fact that none of us play), but so too does seeing useful stats appear regularly on Sky coverage and on BBC. (It helps that some of the same guys helping in the background on those shows are also fans of our site.)
People who do analytics in other sports seem to win the vast majority of their battles, and the media pieces written about basketball and hockey are completely unlike anything you would have seen 10-20 years ago. Football is tiptoeing in this direction, but this is probably the first year that is the case. At some point, literacy with stats will be a requirement for most intelligent sports writing, in America and in Europe as well.
Fast forward a decade from now, and baby steps that we’re taking in football analytics will probably seem perfectly normal stuff to talk about with a broader audience. In the meantime, tell your friends when you see stuff you like, and keep clicking and interacting with the writers that use stats to cheer them on. Almost none of these guys get paid, and they tend to operate on caffeine and kudos alone.