Net Goals Added: Combining Complementary Possession Value Metrics

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Net Goals Added: Combining Complementary Possession Value Metrics

By Mike Imburgio

It’s been about three years since goals added (g+) was first introduced with the aim of measuring how much value a player adds to their team through on-ball actions. Since then, the g+ model has been refined and improved, and lots has been learned.

In fact, the creation of g+ has since spawned two related metrics, g- and g+ boost, which extended the g+ framework to answer questions that g+ itself doesn’t. Because these three metrics were designed to complement each other, bringing them together to form a total player value should provide a holistic system that accounts not just for what a player does on the ball, but what happens after they pass the ball and what happens when their opponent has the ball.

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Thomas Bayes? Meet Djordje Petrovic

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Thomas Bayes? Meet Djordje Petrovic

MLS is no stranger to star goalkeepers turning the fortune of a team, carrying a bedraggled defense to respectability off the virtue of their shot stopping. From Tony Meola and Joe Cannon to Nick Rimando and Stefan Frei, that is MLS heritage. In recent years, the goalkeeping landscape has been dominated by two men in New England, first Matt “xGod” Turner and then a rather large Serbian fellow named Djordje Petrovic. Both shattered the limits of what we thought possible in terms of goalkeeping statistics. 

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The Replication Project: Measuring Shooting Overperformance

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The Replication Project: Measuring Shooting Overperformance

Before Laurie Shaw was working for the esteemed City Football Group, he was gifting us with tidbits of knowledge in blog posts. One such piece of writing was “Exceeding Expected Goals”, a dive into the age-old question of finishing skill in soccer.

While expected goals (xG) tell us about the quality of the shots—accounting for the context of a shot—they’re agnostic to player identity, so we need more info to tease out individual shooting ability. Shaw points out that one way to evaluate finishing “overperformance” is to divide a player’s count of goals (G) by their xG. A ratio of 1 indicates that a player is scoring as many goals as expected; a ratio greater than 1 indicates overperformance; and a ratio less than 1 indicates underperformance.

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What the data says about USWNT's group stage performances

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What the data says about USWNT's group stage performances

The group stage has just finished and the sky is falling for fans of US Soccer. Finishing a measly second in the group, beating only Vietnam, the pundits are overwhelmingly disappointed with the performance of our squad and our coach. However, the celebrations of the team indicate they aren’t as worried. After taking a statistical deep dive, maybe it’s not time to panic just yet.

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The Best NWSL Players Never to Make a Major Tournament Roster, According to g+

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The Best NWSL Players Never to Make a Major Tournament Roster, According to g+

The last three World Cup cycles have been marked by something with which the U.S. Women’s National Team has never previously dealt: a stable and robust professional domestic league. No such league existed from 1991 - 2000, the first wave of top-level international women’s soccer tournaments. The WUSA was in the middle of collapsing as the U.S. hosted the 2003 World Cup, and the program would return to its 1990s structure for the 2004 and 2008 Summer Olympics, along with the 2007 World Cup. The 2011 tournament came in the middle of the chaotic final WPS season. The NWSL finally stuck, and was eventually able to thrive without the direct support of U.S. Soccer. The USWNT now operates like any other international program would: as the supplemental training, developmental, financial, and competitive environment for players relative to their clubs. 

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Beyond xG: Using PFF Shooting Grades to improve goalscoring predictions in MLS

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Expected goals (xG) have become the most widely used metric in football analytics in the last decade. In short, xG models, such as the one developed by American Soccer Analysis, calculate how many goals a team should have scored based on the characteristics of the shots they have taken. Penalties provide the easiest example: roughly 76% of penalties are converted, so each penalty has an xG value of 0.76. Many articles have shown that using expected goals is preferred to actual goals when evaluating performance, because the metric is generally much more stable due to the rare nature of actual goals.

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Does Passing Matter?

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Does Passing Matter?

I really want passing to matter. I watch, on average, 968 passes in a soccer game, and I’d like to think that completing them actually means something more than launching the ball into the first row.

Watching a beautiful through ball unhinge a defense is like watching a sun set on the bay. But that beauty doesn’t mean it matters, at least not to the data. Not if you care about winning.

Let me show you the correlation between a team’s pass completion rate and their expected goal difference over the last three years in Major League Soccer:

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2023 MLS Analytics Survey

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2023 MLS Analytics Survey

Every year, we update the State of MLS Analytics by putting teams into tiers based upon how many analytics staff they have. However, the number of analytics staff members doesn’t necessarily say anything about the quality of work that a club is producing or if analytics is being incorporated into team decision making. And unfortunately, we can never really know what is going on inside a club’s analytics department. This year, though, we decided to do the best we could to get behind the scenes and asked club analytics staff for their input.

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State of MLS Analytics: May 2023

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State of MLS Analytics: May 2023

Over the last few years, analytics in MLS has been turned on its head. Five years ago, if a team had one person “doing analytics,” it was a big deal. Now, questions are asked if a club doesn’t - and it is not uncommon for clubs to have multiple people on staff. The Tiers of MLS Analytics are now based upon the number of full time analytics staff members a club employs.

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