Introducing itscalledsoccer

Introducing itscalledsoccer

By Tyler Richardett and Brian Greenwood

For the latter half of 2021, American Soccer Analysis has been working on an R and Python library to make it easier to programmatically interact with our data. Today, we are happy to announce the release of the library which we've dubbed itscalledsoccer . If you want to get started right away, the library is available for download from CRAN and PyPI, and the source code can be found here.

In this article, we'll talk a bit about how we built the library and walk through a basic example or two.

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Bob Bradley: Possession, Pressing, and Personnel

Bob Bradley: Possession, Pressing, and Personnel

Heading into Toronto on a snowy December day in past years may have had visitors buzzing about the state of BMO Field’s snowy pitch in preparation for an MLS Cup final. For now, there is just roster talk. Roster talk, and manager talk. Enter Bradley. Not the old Bradley we’ve come to know and love, but the even older Bradley who is new to us.

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Priors and Penalties: Finding the best penalty takers with Bayes

Priors and Penalties: Finding the best penalty takers with Bayes

It’s MLS playoff time, and that means the possibility of penalties and shootouts. Rodrigo Schlegel led Orlando to victory after Pedro Gallese was sent off. Zack Steffen earned a move to Manchester City, in large part, due to leading Columbus to two penalty shootout victories. Portland named a bar in Providence Park after the famous double post shot in the marathon 2015 shootout against Sporting KC. Seattle won their first MLS Cup without registering a shot on goal by winning a shootout. Landon Donovan blasted his penalty over the bar to hand RSL the 2009 MLS Cup. Penalties and shootouts are remembered in ways that few other plays are.

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Where Goals Come From: How Do You Train The Killer Pass?

Where Goals Come From: How Do You Train The Killer Pass?

Introduction

In our last article, Jamon introduced the concepts of the “killer final balls” that lead to the best goal conversion rates - those types of key passes that are the most efficient and dangerous. More specifically, the two most “deadly” types of passes in this sub-category are through-balls and cutbacks. As is always the case with this series, our purpose is to create a framework which is actionable and applicable to teams- theory has very little meaning for us.

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How Sophia Smith Turns Good Passes Into Great Ones

How Sophia Smith Turns Good Passes Into Great Ones

Ask any data analyst about the utility of statistics and you’ll get any number of answers, from the ability to measure shot quality to the potential to build all-in-one impact measurements, such as American Soccer Analysis’ goals added, or g+ for short.

However, the most fundamental utility of data is not found in the answers it provides, but in how it empowers us to ask questions.

For example, while pouring through ASA’s numbers on Sophia Smith in anticipation of a piece on her and the Portland Thorns, I noticed something curious. Despite dominating the NWSL in xG, she came off looking far more mediocre in Receiving g+, ranking only 26th among her peers (xG and g+ data accurate as of October 30th).

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Where Goals Come From: Playing the Killer Final Ball

Where Goals Come From: Playing the Killer Final Ball

This is the third article of Season Two and tenth overall article in a series of articles and videos in the Where Goals Come From project from Jamon Moore and Carl Carpenter.

In our last article, we discussed how Expected Goals (xG) helps us evaluate the quality of the shots that a team takes and concedes. That evaluation can happen with individual shots, with a full game, several games (looking at trends), and over the course of a season. As we know from Season One of this series, the type of shot a player gives us a good indication of the typical Goal Conversion Rate (GCR), starting with the very effective shots from Through balls and Cutbacks. We have twelve types of shots in total in our framework, including penalty shots, across five different categories.

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