Playoff Probabilities

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Playoff Probabilities

You may have noticed that yesterday we debuted our playoff probabilities for 2016! It will also show up as an option in the upper right corner until the end of the season.

As in our 2015 iteration, playoff probabilities come from a combination of where teams are now in the tables, what their remaining schedule is, and how good our model thinks they are. The remaining games of the 2016 season were simulated 10,000 times based on win-loss-draw predictions for each game. The probabilities and averages given below are calculated from those simulations. A bit more in-depth explanation follows:

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Tactics, Talent, and Success: Diversity in Scoring and Chance Creation

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Tactics, Talent, and Success: Diversity in Scoring and Chance Creation

I’ve been wondering for some time about soccer teams’ reliance on star power and top statistical producers. Is it really a good strategy? Are teams with one main goal scorer or playmaker easier to “figure out”? When the game is on the line, is a singular threat easier to neutralize than a team with a plethora of attacking options? And would this kind of reliance actually hamper a team’s success across a season?

My skepticism must seem foolish to European executives, given the huge fees Gonzalo Higuain and Paul Pogba went for this summer. But the conventional wisdom is different in the American sports landscape. In our most popular sports, one person simply can’t do it all. Here, Defense Wins Championships. The San Antonio Spurs, the best NBA team of the past two decades, emphasize team play over everything. Peyton Manning was completely underwhelming in both of his Super Bowl wins, needing his incredible teams to carry him to glory. One star pitcher or one star hitter is simply not capable of winning a World Series on their own. The anecdotal evidence even appears in MLS. Chris Wondolowski’s 27 goals in 2012 didn’t get the Earthquakes past the first round of MLS playoffs; neutralize MVP Sebastian Giovinco, and 2015’s Toronto FC didn’t have much else to offer.

More after the jump.

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PScore: Modeling Tactics in MLS by game state - August 2016

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PScore: Modeling Tactics in MLS by game state - August 2016

Friday August was 12th was Elephant Day and it’s seems like as good a time as any to free some elephants from our rooms and get them back into the wild where they belong. What elephants? What rooms, you might ask? Glad you asked. The room we are in right now is one where soccer tactics are turned into numbers. For those new to the Pscore series the idea is to very simply describe soccer tactics with two numbers, one offensive and one defensive. What tactics are quantified? From an offensive point of view we want to know if a team desires possession of the ball or is more direct with their play. From a defensive point of view we want to know how high up the pitch a team pressures their opponent. All styles can be effective but two in particular are generally used in combination. On the proactive side you have your Barcelona’s of the world that look to work possession on offense and counterpress when they lose the ball to get it back quickly. On the reactive side there are examples like Leicester City that will sit their defense deeper and then play directly on the counterattack once in possession. As you’ll quickly see Major League Soccer sports a handful of those type of clubs and a few different styles. If you are curious how these numbers are developed I’ve written about that in detail before and you can read it here.

More after the jump.

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MLS's Original (Dave) Gantars: A Look at MLS Officiating

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Referees in soccer are the most necessary evil in the game, we can all agree on that. Without a referee who would call the fouls? Can you imagine Will Johnson calling his own foul? Neither can I. What about Alvaro Saborio? Hahahaha, everything is a foul to that guy. Robot refs? Not likely for another few decades, but one can hope. No, today we all agree that referees are the worst, absolutely the vilest invention to curse our beautiful game, besides every other method of governing a game that has been attempted.

Now that we've all established how much we hate refs, let’s have a real conversation about officiating in MLS. The professional soccer referees association gave way to PRO in MLS in 2012 with legendary FA/FIFA ref Peter Walton leading the way. In actuality they have likely improved the quality of officiating in MLS. Just tune into their Snapchat channel to see the latest and greatest in training, testing, and qualification that North America has to offer. I won’t extol their virtues long, but realize that they are not just bumbling idiots, laughing their way to the proverbial bank with a wheelbarrow full of our emotional strain in tow.

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Why Andre Blake and David Bingham Shouldn't Win Goalkeeper of the Year

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The MLS All-Stars fell 2-1 to Arsenal in the most recent all-star game, with Philadelphia’s Andre Blake and San Jose’s David Bingham splitting time in net. On paper, the two selections make sense. Blake started for Jamaica in the Gold Cup this summer and Bingham was in the running for being the third stringer for the US. But as we've passed the halfway point of the season, the next time a goalkeeper will be selected to represent MLS is with the annual Goalkeeper of the Year Award. The two have a myriad of saves, but are they really deserving of MLS’s most and only prestigious goalkeeping award? More after the jump.

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Visualizing Expected Goals, Actual Goals, and Player Salary

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If you have not heard of Expected Goals (xG) then please have a read of these posts before continuing. 

11tegen11 has written about expected goals (xG) and concluded that it predicts future performance better than other metrics such as Points Per Game (PPG), Goal Ratio, Shots Ratio & Shots on Target Ratio.

Using the interactive visualization, you can see how your favorite players performed each season and how much they earned per season. As you will notice, a number of players "over-perform" and others "under-perform" their xG every season. We could classify them as being "lucky" or "unlucky". Dan Altman in this video explains why this may or may not be the case.

See the interactive graphic after the jump.

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Who is the best passer in MLS? Debuting an Expected Pass Completion Model

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Javier Morales of Real Salt Lake had completed 82.3% of his passes before last weekend. Chad Marshall completed 84.4% of his passes for the Seattle Sounders. Gyasi Zardes has a 66.1% pass completion percentage. Is any of this good? Which player is a better passer? Fans are smart enough to know they can’t compare those numbers directly because Morales and Zardes play attacking roles and Marshall is a defender and will face pressure less often. 

Looking at pass completion percentages without context is a fool's errand. To address this issue I built a model that predicts the likelihood that a given pass will be completed. The effect is that the difficulty of the pass - including position on the field, part of body used, whether it was backwards, etc – can be factored into this expectation. With this model we can observe whether or not a player passes more or less effectively than an average passer, adjusting for the difficulty of the pass.

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ASA First Touch: Colorado's waste of resources

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Finally, the Secretary of Defense is home. Though the game ended in the dreaded 0-0 tie, Tim Howard’s debut with the Rapids was surely the biggest storyline of the week. When his signing was originally announced, there was no doubt he would take over immediately as the starter, but it did create a tremor of controversy.  Are the Rapids really best served by changing their goalkeeper after letting in the fewest goals of any team after 16 games?

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Goodbye expected goals, hello expected points!

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An expected goals model frames quite well what everyone knows to be true: that not all goals are created equal. Goals are created from tap-ins and bicycle kicks and all the shots in between, and expected goals allow analysts and fans to quantify the likelihood a shot will go in the net, and therefore the value of a shot. The next logical step in the discussion of goals is to analyze their value. Goals aren't created equal but neither are goals equal. The goal that makes a two goal lead a three goal league does not nearly have the value as that stoppage time goal that captures all three points.

To measure the value of a goal I looked at game states in MLS from 2011 to 2015 and built a series of functions that estimate the expected points for home and away teams given the score of the game and the minute being played. Each of the functions fit tightly with the actual data and had an R squared greater than 85%. The expected points functions look like this for games with a difference of two or less goals.

Pretty graphs after the jump

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ASA First Touch: Second Edition

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This is ASA’s attempt at an ensemble wrap of various things pertaining to US Soccer things over the last week. This is not intended to be a deep retrospective or an overtly granular analytical take. These are quick and hard takes by our first rate crew.

USMNT KNUCKLE SANDWICH

By Jared Young (@jaredeyoung)

The USMNT did not have their best week as they failed to score against both Argentina and Colombia finishing fourth in the Copa America Centenario. The most interesting statistic this week came in the form of an undefined number as the U.S. had a finishing rate against Argentina of 0/0, or something that can’t be expressed numerically. It’s tough to score when you don’t shoot. 

Whenever you finish fourth in a major tournament but don’t score in the final matches you will divide your contingent. Twitter might not be an accurate representation of the USMNT fanbase but it at least offers some data to consider. Many on twitter have been calling for Jurgen Klinsmann’s head despite the overall success of the team in the tournament. But just how divided are fans?

More apologies for JK after the jump.

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