Goals Added: The Art of the Wheel

Goals Added: The Art of the Wheel

Look at that. Pretty, right? The colors. The font. The icons. The logo. That tiny beeswarm. All work together to make a pretty damn good visualization. But these things just don’t emerge from a computer fully formed, they take a lot of effort and there are a ton of ways that things can go wrong. Inspired by Peter McKeever’s discussion of his beautiful diamond plots, here are the decisions we made and iterations of this viz along the way to what you see above.

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2020 Season Preview: Columbus Crew SC

2020 Season Preview: Columbus Crew SC

Unlike last season where Columbus returned 96% of team minutes played, this offseason has seen more turnover for the Crew than has been seen in years but has also resulted in impressive depth throughout the squad. After a disappointing and injury-filled 2019 season, Caleb Porter will be looking to bring his team to the playoffs for the first time under his watch.

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Offseason Outlook: Columbus Crew

Offseason Outlook: Columbus Crew

The Columbus Crew had a disappointing season in 2019, finishing 3rd to last in the East. Unlike the stability of last season, the roster is showing more turnover than the club has seen in many years. While most positions have starters already in place, the Crew lack depth in most positional groups.

Here’s how the Crew’s roster stands with a projected depth chart in the Crew’s traditional 4-2-3-1 formation…

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The Great Goal Kick Shift

The Great Goal Kick Shift

During the Renaissance era, the English language went through a revolution where vowel pronunciation radically changed. This was known as The Great Vowel Shift, and ultimately led to modern English. Similarly, in the late 2010s, goal kicks were revolutionized in what I am calling The Great Goal Kick Shift. Seemingly a worldwide phenomenon, the location where goal kicks were taken rapidly shifted from their traditional location at the corners of the 6-yard box towards the center of the field.

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Shots in the Dark: how data providers tell us different versions of what happened

Shots in the Dark: how  data providers tell us different versions of what happened

Recently, this tweet created a small firestorm in the soccer analytics community. While it is unclear the source of the error, it was pretty clear that there weren’t 1,300 passes and 50 shots in an English League 2 match. This led to responses from prominent analysts such as StatsBomb’s Ted Knutson (including on his podcast [starts at 10:45]), Opta’s (and ASA alum) Tom Worville and Ryan Bahia, and Chris Anderson, author of The Numbers Game. All of them were saying pretty much the same thing: question the data you are using. If the data you are using to analyze a problem is not valid, then your solutions won’t be either.

So what do we know about the data that is used for soccer analysis? Previous studies have shown that people are pretty good at agreeing about what type of event occured in a soccer game (e.g. shots, tackles). But as far as I can tell, the accuracy and precision of locations  of game events among the various data providers has not been studied. As Joe Mulberry pointed out when looking at the troubling inconsistencies between spatial tracking data and event data, small differences in locations can have big effects on downstream analysis including expected goals (xG) models. In other words, small inconsistencies in how data is tracked can have big consequences for the models built off that data. So what are the differences between how soccer data providers collect and report their data?

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Hanging Chants: Analyzing MLS Goals of the Week Voting

This week, news that is sure to shatter the confidence of MLS fans broke via Andrew Pearson on twitter: there may be massive election fraud happening during the weekly MLS AT&T Goal of the Week polls. Pearson revealed that Atlanta fans are running up record breaking vote totals by possibly untoward means. Furthermore, MLS may have tipped the scales against Seattle’s Cristian Roldan when the 2019 Week 10 award was handed to Ezequiel Barco despite Roldan winning the popular vote by 18 votes*. As fans, we demand answers. Don Garber should appoint Chris Mueller as an independent counsel to get to the bottom of these alarming reports.

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FC Cincinnati 2019 Season Preview

FC Cincinnati 2019 Season Preview

To Minnesota, or to Atlanta, that is now the question for an MLS expansion team. The 2017 MLS expansion teams took divergent paths to roster building. Atlanta supplemented their young expensive South American signings with older proven MLS veterans. Minnesota relied on a corps of players brought up from their NASL squad and a more journeyman group of MLS players, sprinkled with some lower profile international imports and no Designated Players. FC Cincinnati has answered the question with an emphatic “Minnesota.”

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Columbus Crew 2019 Season Preview

Columbus Crew 2019 Season Preview

After probably the toughest season in Crew history, everything’s coming up Massive for the Crew. An absentee, out-of-town investor/operator has been replaced by a committed local group led by the Crew’s long-time team physician Dr. Pete Edwards. A new stadium in the heart of downtown is in the works, Tim Bezbatchenko has returned home to Columbus as President, and Caleb Porter returned to Ohio to win an MLS Cup for Columbus. With the Crew returning 96% of minutes played in 2018, look for an evolution rather than a revolution on the field from Caleb Porter’s men.

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Machine Learning the Crew

Machine Learning the Crew

Machine learning is so hot right now and if Skynet is going to destroy all humans, it should at least know a little bit about Major League Soccer’s Columbus Crew. To wit, I created a machine learning model to classify which position in a Gregg Berhalter 4-2-3-1 formation a player most likely played in during a single game.

I chose the Crew for a couple reasons. First, they are my favorite team. Second, they had consistent coaching for a long period of time with a defined style of play. The latter is very important, as the model has to be trained well in order for the results to make sense. Since the Crew almost always played a 4-2-3-1 that relied on ball possession to disorganize the defense and create goal opportunities (get used to that phrase USMNT fans) it was a perfect test of whether this kind of thing could be done.

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