By Eliot McKinley (@etmckinley)

Much has been written and studied about set pieces in soccer. Penalty kicks have been Bayesed multiple times, I’ve analyzed free kicks in MLS and at the World Cup, corner kicks have been rigorously studied. But what about the humble throw-in? Aside from when teams develop a long throw-in program (see Delap, Rory) they are largely ignored or even ridiculed, in the case of Liverpool hiring a throw-in coach (see the first comment here).

Throw-ins are an integral part of every soccer game. In MLS regular season play since 2015 almost 64,000 throw-ins were taken (all data is based on 2015-2018). They occur 44 times a game on average, accounting for almost 5% of all passes. Twice during the 2018 MLS season throw-ins accounted for over 10% of passes in a game. However, a search of MLS’ website brings up only the definition of “Throw-In”, a defunct regular column (with some words about early use of analytics in MLS), and some discussion of long throw-ins as scoring threats. Nobody, at least publicly, seems to be talking about normal run-of-the-mill throw-ins.

I got interested in looking at throw-ins for a couple of reasons. First, while sitting on the outfield berm at First Tennessee Park for a Nashville SC game wrangling my 3-year old son, I noticed that Nashville seemingly kicked the ball out of bounds from the opening kick off. While this is not a common tactic, it is well established. This forced New York Red Bulls II to take a throw deep in their own half that was ultimately won by Nashville. This play ultimately didn’t lead to a shot or a goal, but it piqued my interest. A few weeks later, the Crew suffered an embarrassing loss to Orlando after giving up a penalty in second half stoppage time. Just before the penalty, the Crew’s Hector Jimenez allowed an errant cross to run out of bounds when it appeared to he could have recovered the ball and retained possession (I wrote about this at Massive Report). The Crew ended up losing possession from the ensuing throw-in and Orlando hit to crossbar with a shot a few seconds later. This was the beginning of a flurry of shots from Orlando that could have possibly been prevented had the Crew not allowed the ball to go out of touch. Both of these led me to think about how throw-ins can be utilized to gain an advantage over one’s opponent.

Definitions

Let’s start with some definitions. A successful throw-in is one that “goes to a teammate directly without a touch from an opposition player”. This doesn’t mean that the team retains possession from a throw-in, just that the thrower hit one of his or her teammates with the throw. While a successful throw-in is generally a good thing and occurs 81% of the time, if a throw-in is too hard, to the head, or to a player under pressure it may not be retained by the throwing team. To quantify this, I took the possession definitions Cheuk Hei Ho initially derived for expected possession goals and looked seven seconds after the throw-in was taken to see if there were any possession changes. If the team kept possession for these seven seconds, the throw-in was retained, which occurred for 60% of throw-ins. The choice of seven seconds was somewhat arbitrary, but watching some video leads me to believe that this is in the right ballpark. Thus there are four types of throw-in results:

Successful with possession retained (51% of throw-ins; example video) Unsuccessful with possession retained (9% of throw-ins; example video) Successful with possession lost (30% of throw-ins; example video) Unsuccessful with possession lost (10% of throw-ins; example video)

xThrow and xRetain Models

I created expected throw-in (xThrow) and expected throw-in possession retention (xRetain) models to better understand throw-ins. Both models are almost identical to the expected passing (xPass) model developed by Matthias Kullowatz & Jared Young here at American Soccer Analysis, but with one extra variable, the amount of time since the last action. The time since the last action turned out to be the fourth most influential variable in xThrow (after angle, whether or not it was a long throw, and the x-location) and the third most influential for xRetain (after angle and x-location). Go read Matthias’ article for specifics on how these types of models models work.

Throw-in Angles