Reshaping The Game: How Fran Taylor is Using New Tools to Build a Better Team

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Reshaping The Game: How Fran Taylor is Using New Tools to Build a Better Team

Taylor, the 29-year-old Assistant General Manager for the Colorado Rapids, joined the team in January of this year to bolster the data-driven team of Padraig Smith in trying to use numbers to build a better soccer club. While baseball and basketball teams have adopted advanced metrics to try and divulge information that will give their club a competitive edge in their respective sports, soccer is still finding its way in the moneyball era. Newly discovered numbers are illuminating the game, but only in the hands of those who know what to look for.

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Quantifying Successful Possession (xPG)

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Quantifying Successful Possession (xPG)

Some elements of soccer don’t present a clear and direct interaction with the shot, such as the tactical or the formational change. You can use the location of the players to decipher the shape of a team, but how do you measure the efficiency and the individual contribution of each position? To this end, we developed an xG-based score – Expected Possession Goal (xPG) – that is dependent on the location of the ball but not the shots creation.

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Expected Possession Goals: The Value of a Possession and Comparing xPG to Other Metrics

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Expected Possession Goals: The Value of a Possession and Comparing xPG to Other Metrics


It is probably easier to identify good possession by sight rather than a textbook definition: decisive movement and accurate passing lead to good looks, so I’ve been very interested in whether a metric like xG could quantify the value of a possession. If you have not already read it, please begin with Cheuk Hei’s Expected Possession Goals article [hyperlink: Expected Possession Goals (xPG) as a metric to quantify successful possession]. Expected Possession Goals (xPG) attempts to create a more holistic view of a soccer match by focusing on possessions rather than just shots. Possessions occur at about a 10-to-1 ratio to shots, so they can provide 10x the data for analyzing the flow of a game. Take into account just the average number of passes in a possession, and you get around 3x more data.


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Little Things from Week 19: Luis Gil's first touch, Khiry Shelton’s strengths and weaknesses and Laurent Ciman’s fizzing set pieces

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Luis Gil’s first touch and the beauty of the best players

In the later stages of the midweek 2-2 draw between the Houston Dynamo and LAFC, as the Dynamo chased LA’s 2-0 lead, Luis Gil had a play that demonstrated the importance of the first touch, and how difficult it can be for even professional players to combine the mental foresight and technical ability required to make even simple passes.

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Pass Chain Analysis: Should Teams Build From The Back?

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Pass Chain Analysis: Should Teams Build From The Back?

What’s so great about playing out of the back anyway? I have heard coaches give the standard answers, and I get the advantages of the times you do successfully “get out,” but how well does this work in MLS where the current narrative is the attacking is better than the defending? When players several years older than my son can hit a ball 70 yards and change the point of attack in an instant, why would teams make several passes forward, backward, and sideways to cover the same ground? These are philosophical questions that different coaches and their teams answer each game with their choices and execution.

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Lowered Expectations: Week 17

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Lowered Expectations: Week 17

Welcome to Lowered Expectations, week 17 edition! Each week, we go about posting chalkboards and GIFs of the weekend’s best open-play shot attempts which did not quite live up to expectations (and rarely do we update this paragraph). We look at each one and not only evaluate the results, but also the process leading to them.

#5 - Alejandro Silva, Montreal Impact, 62nd minute, 0.414 expected goals
Assisted by: Matteo Mancosu
Passes in sequence: 2

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Little Things from Week 17: The Union Midfield, Gressel's Quiet Contribution, and Jeff Attinella's Decision Making

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Little Things from Week 17: The Union Midfield, Gressel's Quiet Contribution, and Jeff Attinella's Decision Making

Philly’s Midfield

The Philadelphia Union are making a concerted effort to keep the ball this season. They are fifth in MLS in passes per game and have built their attack around getting the ball into the half-spaces and putting the wingers (especially Ilsinho) in positions to run at defenders.

Their 4-0 home win against Vancouver was a manifestation of their newfound approach. They were on the front foot for most of the game against the bunkering Whitecaps, so even with midfield distributor Haris Medunjanin suspended, they demonstrated how good they can be with the ball.

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Tiny Differences: How Changing Small Things Can Have Big Consequences

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Tiny Differences: How Changing Small Things Can Have Big Consequences

Short passes dominate every soccer game. They are the most abundant on-the-ball action. But the variation in short pass accuracy is small; the difference in short pass success rates between the best and the worst team in MLS is 13%. For a typical game with about 400 short passes, the difference represents 52 more successful attempts, or one extra pass every two minutes. How much impact can these extra passes have?

Atlanta United is especially dependent on short passes that lead to shots. What would a few more short passes mean for their offense? Yankee Stadium is a tough place for any visiting team. Critics say that it is too small, and only New York City FC play well there. How exactly do they take advantage of the home turf?

The best way to approach these questions other than watching thousands of clips is to make a model with data and use it to examine or even predict what a team excels or suffers. There isn’t one... yet. Can we make one?

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Pressing, Defensive Lines, and What Defensive Actions Correlate with Goals

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Pressing, Defensive Lines, and What Defensive Actions Correlate with Goals

How do you analytically measure a high defensive line and defensive pressing (see StatsBomb pressing index and Jamon's piece from a couple weeks ago)? Do we have enough data and information to analyze this behavior? If we do, how do these tactics impact the performance of a team?

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