Columbus Crew

Columbus Crew 2019 Season Preview by Eliot McKinley

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 An absentee, out-of-town investor/operator has been replaced by a committed local group led by the Crew’s long-time team physician Dr.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 by Eliot McKinley

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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You Down with t-SNE? by ASA Staff

We all know that some teams play a certain style, Red Bulls play with high pressure and direct attacks, Vancouver crosses the ball, Columbus possesses the ball from the back. Although we know these things intuitively, we can use analytical methods to group teams as well. Doing so seems unnecessary when we have all these descriptors like press-resistance, overload, trequartista-shadow striker hybrid, gegenthrowins, mobile regista, releasing, Colorado Countercounter gambits...etc (we actually don’t know what some of these terms mean and may have made some up, but the real ones are popular so just google them yourself). Those terms are nice, but no qualitative descriptor can tell us how the styles of New York City and Columbus differ from each other. We need to measure, compare, and model two teams’ playing styles and efficiencies. If we are able to do these things we may be in a position to answer what style really is.

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Postseason Preview: Columbus Crew SC by Eliot McKinley

We saved the Crew! In a way I don’t even care about the playoffs, we saved the Crew! For the last year, the team and the fanbase have been in an existential fight to save the Crew from being ripped ripped from Columbus and moved to Austin. This fact hung over everything in the Columbus Crew universe. No matter how hard I tried to just sit back and enjoy a game, there was always a thought in the back of my mind that this may be the last time the Crew plays [insert team here], or this may be the last Pipa chip I get to see. But you know what? We saved the Crew! It took thousands of man-hours from countless volunteers working together to do it, but we saved the Crew!

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Expected Possession Goals GameFlow: Taking a Ride Into the Danger Zone by Jamon Moore

A few weeks ago, we introduced Expected Possession Goals (xPG) GameFlow, a visualization of the momentum of a soccer match from kickoff to final whistle of each game. xPG GameFlow uses the accumulation of Chance xPG to measure the strength of an opportunity for a team to get a shot. The higher the Chance xPG differential between the teams, the longer the bar for that minute for the team with the higher amount. Quite often goals are scored when the momentum bars on the xPG GameFlow chart are at their longest.

Many people have asked us, “what is the difference between xPG and xG?” or “how does xPG translate to xG or to goals?” To aid xPG GameFlow in answering questions such as “which team had the better chances?” and “when should a team have scored?”, we introduced a couple improvements after the first week of tweeting MLS game charts on @GameFlowxPG. I wanted to provide more context for these improvements and dive deeper into them.

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The Tactical Proactivity of each MLS Team by Jared Young

The MLS playoff drama is peaking with all but a half dozen teams dreaming of postseason glory. All the teams have played their tactical cards by now and the chess matches from here on out should be very entertaining. It’s therefore high time to look at a model whose goal is to examine the very chess moves that teams are making and look for insights. The Proactivity Score (Pscore), an attempt to numerically represent a teams basic tactical approach, has been updated through August 27th and there are some interesting new trends. Here’s a chart of where teams stand:

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The Next Level of xG: Expected Possession Goals by ASA Staff

Using xPG variants to assess risk-and-reward of the game

We introduced Expected Possession Goals (xPG) in two recent articles. xPG groups and rates the outcome of a possession and began from an idea that every action in the possession connects to create a shot. Here, we’re introducing new xPG variants, extensions to the original xPG definition to assess the risks and rewards inherent in a soccer possession.

xPG rates a group of uninterrupted events - or when an interruption lasts fewer than two seconds - based on where the ball travels. It assumes the purpose of the possession is to move the ball within shooting distance.

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Where the Ball Was Won: Using Passing Data as an Indicator of Defensive Pressure Points by Jamon Moore

I’m a die-hard San Jose Earthquakes fan. Please don’t leave yet. In case you aren’t paying attention to MLS much this year, the Quakes have been…underperforming, even by their less-than-lofty standards. I was preparing data for an article about the Quakes troubles with defending the opposition Zone 14 (or are you #TeamZone5?) discussing why they have given up a league-high 6 goals there so far this season, when – you may be aware – Matt Doyle (@MattDoyle76) and Bobby Warshaw (@bwarshaw14) publicly blasted the Quakes for the very same issue back on May 27.

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Expected Narratives: Seeing Reds by Ian L.

xN is our weekly look at what you can expect to read, write, and discuss about Major League Soccer this week. We take a look at each prospective narrative and rate it based on its strength and whether or not it has any actual merit.

Last week, I asserted that if Toronto failed to secure three points this week that the talk of the league would be whether or not last year’s all conquering heroes would even manage to make the playoffs this season. Unsurprisingly, they failed to acquire those three points, surprisingly nobody is really talking about it all that much. Well, since I’m CNO (Chief Narrative Officer) of this league now (self appointed, the term is lifelong meaning it remains until such a time as I die or get bored. Smart money on the latter.), I’m going to go ahead and make it a narrative because a) it’s important and b) I can’t really think of another thing to write about this week. I mean I guess we could cover VAR again, but NAH.

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Little Things from Week 11 by Harrison Hamm

Welcome to Little Things, a weekly look at some of the nuances that occur in MLS games. Technical and tactical aspects will be looked at to better evaluate players and teams on a larger scale, and of course statistics will be put to use.

Here’s our inaugural analysis, including an example of how not to press by Minnesota United, an interesting set piece fad, and an impressive build-up by Orlando City:

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