Attempting to tease the luck from the talent in the shot saving percentages seen in the likes of Kevin Hartman, Tony Meola, Joe Cannon and Tim Howard was a lot easier than trying to sensibly argue who England's current stopper should be. So a belated h/t to Big Soccer, where around half a dozen stat enthusiasts hung out in the dim distant past.
A recent tweet from the influential Steve Fenn, a must follow at @SoccerStatHunt, reminded me of the excellent work that is being done by the guys at http://americansocceranalysis.wordpress.com/ notably, Harrison Crow (@Harrison_Crow). They are collecting and also sharing shot data in the current MLS. So a major h/t to them, the first attribute is fairly common, but the second is extremely rare and most welcome!
The availability of data is the major bottleneck is blog based analysis. Methodologies are fairly standard, but weight and credence to any conclusions only comes with increased sample size. It is fairly easy to develop a novel methodology, but the limited data can still make you look dumb.
Back in the day, shot attempts and outcome was the limit of the data, but the the volume of the data, stretching over seasons and, in the case of keepers, their longevity, still made analysis possible, if with a slightly wider error bar attached. Increased shot volume, it was hoped would even out issues of shot and chance quality, that did not exist to such as degree in either the controlled pitcher/batter contest in baseball or the more restricted playing area of hockey.
|I don't have an MLS photo. Instead here's Clint Dempsey celebrating Sounders' Interest (and a Goal against Stoke).|
Applying one of my shooting analysis methods to ASA's improved data was therefore both sensible and a nostalgic treat. Broadly, this method assumes that shot outcome is common to each MLS team and centered around the league average. Any apparent deviation in shot accuracy percentage or conversion (and there is bound to be some) is going to be down to random variation and a talent gap in performing these tasks between sides. Quality of opportunity is hopefully controlled by ASA's use of shooting zones. So if we see a wider range of outcomes in the attempts each side made, compared to a random draw using league averages, we can possibly conclude that random variation isn't the only factor at work in deciding the shooting pecking order.
The sectors used along with the data are all available at ASA's site, so I urge everyone to seek it out there, but for partial clarity the sector descriptions are sector's 1,2,4 and 5 are central to the goal and more distant with increasing number and sector 3 is wide within the area and sector 6 is wide to the flanks.
I have taken shooting data from the site for every game played by every side in 2013 and compared the spread in accuracy (in terms of shots that require a save), conversion rates (goals scored) and the undesirable ability to see shots blocked that was recorded by each side against the type of spread expected from those shot numbers if team talent was universally the same in each sector and variation of outcome was purely luck driven.
Do Sector Outcomes Suggest Factors Other Than Random Variation are at Play in the MLS?
|Sector taken from American Soccer Analysis Site.||Does Accuracy Deviate from Random?||Does Conversion Rate Deviate from Random?||Does Avoiding Blocked Shots Deviate from Random?|
The results are tabulated above. Using shot data from 2013, there does appear to be some evidence that team conversion rates may show a talent differential when strikers are closest to goal. As attempts move further from goal (in the case of zones 4 and 5) and much wider out to the flanks (in case 6), that differential appears to disappear and outcomes become consistent with the average overall conversion rate for the MLS. In short, skill may exist inside the box, but outside you're hoping to get lucky....in the MLS at least.
A talent for greater (or lesser) shooting accuracy as measured by an attempt requiring a save appears to survive to greater distances and angles or it may show a tactical approach whereby a side is required to "make the keeper work" in expectation of a follow up rebound....Or everything may be the result of insufficient detail contained in the current, admirable data.
I know very little about the specifics of the current MLS, other than Dallas produce technical adept players and Seattle has the coolest kit, but others may make sense of Philly being the best opportunity corrected finishers in sector 1( closet to the goal) and Portland the most efficient in sector 2.
Random variation is ever present in the data, but recourse to this concept as a catch all when a side over or under performs against the league norm, may be less (or more) than fair to player and coaches alike, especially in the absence of any evidence that the talent gap at the very top level has disappeared completely.
To reiterate here's the link to American Soccer Analysis.