The parallels between analytics in football and where analytics in Baseball was years

Miller
Photo Courtesy of David Rogers

ago are uncanny. Like stats in football now, analytics in baseball was once considered the domain of nerds. It now has widespread acceptance with both media and teams alike. Michael Caley, who could be compared to a baseball analytics’s Bill James, is a well-respected writer in football stats, known especially for his work with expected goals, but in March he made the parallels between baseball and football stats closer when he applied the idea of an age curve to the “Big 4” football leagues in Europe. A term any listener of “Effectively Wild” (If you made Moussa Dembele run backwards when he played, how many goals would he score?!) would recognize, Caley took the total minutes played in each position by each age and divided that by the total minutes played to see what ages played the most in the big leagues. He found that the “peak years” for players in those leagues were 25-28, though that changed a bit by position. If you haven’t read the article by Michael on ESPN, go here now. It is a great example of seemingly simple analysis that can give huge insights to clubs. I’ll wait while you read.

Back? Cool. One of things that struck me after reading this was its application to Scotland. I believed there was probably a similar trend in the SPFL. However, when the Caley’s article was first published, Kenny Miller had not yet been signed to an extension for next year by Rangers. Miller was Rangers leading scorer and the Glasgow club would likely not be in 3rd place, despite Miller turning 37 this season. Clearly Miller was a huge part of Rangers season but was well outside those peak years. I also thought of my article on Don Cowie leading Hearts in Expected Assists and being among the xA leaders in the league despite being 33 years old this season. Steven McLean scored again against Celtic Saturday and is on pace for another 10 goal season in the league at the age of 34. Of course, there is the fantastic season young Moussa Dembele and Patrick Roberts has had with Celtic, despite being younger than those typical peak years. With players the age Miller, Cowie, Dembele and Roberts in mind, I looked to calculate the same percentage of minutes played by age for the SPFL.

Forward Minutes.jpg

The largest percentage of minutes played by forwards are by 25 years old (17.6%) in the SPFL, similar to what Caley found for the Big 4. However, the next largest percentage of minutes are played by 23 year olds (8.81%) and 29 year olds (11.48%). These ages are playing a much higher percentage of minutes in the SPFL than they are in the biggest leagues in Europe. 22 year olds (7.48%) also play a higher percentage of minutes in the SPFL than anyone aged 23-28 (besides 25 year olds) and play much more than they do in the big leagues of Europe. And of course we see Kenny Miller’s contribution at the end of the graph as a 37 year old.

Midfielder Minutes

We see a very similar story when we look at midfielders. There is a high percentage of 24-28 year olds playing in the SPFL, as there is in big European leagues. However, the largest percentage of minutes in the SPFL played by midfielders are played by 22 year olds (11.71%). 20 year old midfielders are getting plenty of playing time as well (6.54%), but the thing that sticks out to me here is the minutes 30+ year old midfielders are getting. Midfielders at least 30 years old are getting nearly 18% of all the midfield minutes in the SPFL this year, a very sizable chunk.

Clearly, both youngsters looking to make a name for themselves and older players who may not get a chance anymore in a bigger league can find playing time in the SPFL. But what type of contribution are these players outside the typical “peak years” bring to the league?

Shots xG Age

Not only do both younger and older players than the typical peak ages get to play in the SPFL, they do well. Ages 20 to 24 average a higher expected goals per 90 minutes in the SPFL than ages 25 through 29, as well as averaging similar numbers of shots per 90 as those ages. We also see various 30+ year olds averaging very respectable shot and xG per 90 numbers that are higher than we see in the biggest leagues.

xA Age

If we look at expected assist numbers for midfielders, the highest average xA per 90 by age is for 27 year olds. However, that is due to Scott Sinclair, who deservedly won the player of the year award last week. Besides Sinclair, we see high xA numbers for ages 29-33, which were the ages Michael Caley found xA start to drop for the bigger leagues. On the other end of the graph, we again see players younger than the 25-29 year old peak being contributors to their club with good xA numbers.

Brendan Rodgers arrival at Celtic has seen them able to attract players to the club they

Cowie
Photo Courtesy of SNS

would not have been able to sign the past few years. However, the rest of the SPFL is likely unable to bring in this caliber of player. Yet, those other SPFL clubs can look at data like this and know that they will be able to get more out of a younger player who hasn’t hit his peak or an older player past his traditional peak than a club in a bigger league might get out of him. With this knowledge Scottish clubs can look for younger players who will improve with the minutes an SPFL club can give them and then sell them on for a profit or an older player who they sign for a bargain price and still make a meaningful contribution on the field. While finding players at their peak is a key in England, Spain and Germany, you can exploit an inefficiency in Scotland by avoiding those peak aged players. With data and scouting, your club can find the next Don Cowie or even perhaps the next Moussa Dembele.

This article was written with the aid of StrataData, which is property of Stratagem Technologies. StrataData powers the StrataBet Sports Trading Platform, in addition to StrataBet Premium Recommendations.

One thought on “Bringing the Age Curve to the SPFL

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