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Archive for category Statistics

OF COURSE! THE U.S. BEATS SPAIN AND AN OIL COMPANY HELPS ANALYZE PLAYER PERFORMANCE!

Castrol GTX May Not Let Your Engine Break Down, But They Know How to Break Down A Game

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In case you weren’t aware, the ever-prescient governing body of soccer has partnered with Castrol GTX to develop the “definitive system” to rate player performance. Not only does it rate performance, but it rates performance objectively! According to a clarifying explanation on the Fifa.com website, the infinitely complex system “tracks every move on the field and assesses whether it has a positive or negative impact on a team’s ability to score or concede a goal.”

Why even watch games anymore when watching games won’t even tell you which players “truly deserve to grab all the headlines”? If you’re as much of a soccer enthusiast as I am, then you simply need to know which players these are! I mean Fernando Torres, David Villa and Kaka in the top three? Who would have thought? Now I look at them in a newly edifying light. They’re so … technologically advanced.

The secret to the revealing analysis lies in the carefully calibrated zones into which the Castrol Index has divided the field. Passes completed into higher-rated zones are worth more “Castrol points.” The same is true for tackles or interceptions in the most advanced or dangerous zones. In other words, Castrol points are brilliantly simple and complex at the same time, kind of like the internal combustion engine.

Why didn’t I think if the Castrol Index? Probably for the same reason I don’t know how to engineer a high-mileage motor oil with “magnetic properties” and “57% better sludge protection than competitive oil.” I wouldn’t even know how to begin measuring that. Science is amazing.

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Now that such a system exists, I won’t even bother trying to analyze the U.S.-Spain game because I’d probably get it all wrong. Somehow, though, I’ve been lucky enough to get one of the developers of the revolutionary system to be a guest commentator on the semifinal match. So the esteemed Dr. Sludge, who has degrees in both synthetic engineering and soccer statistics, is going to take over from here. You might want to get out your protractors and calculators, though, because Dr. Sludge can get awfully mathematical. Just kidding! Dr. Sludge makes even complex algorithms so easy to digest that he doesn’t even need to explain them because you just know they’re true. Go ahead Dr. Sludge!

Thank you, Thank you. Really, thanks Cyrus for letting me speak with such an adroit and influential soccer audience. Hello Footsmoke.com!

Can I get some epic classical music in the background? Do you have any Brahms? OK. Actually, something a little slower? Heavier? That’s the stuff. Dim the lights. Nice …. Ahem…

“It’s not easy to repel blistering speed. It’s not easy to take on bone-freezing passes. It’s not easy to defy the physical laws of international soccer….

But team U…S…A was not an easy team to develop…

Its synthetic-odometric-enduroefficiency-coverage ensures that it keeps going, even in the 90th minute. Especially in the 90th minute. Because we all know 90th minutes can last lifetimes. And in pressurized conditions like this they can cost games, even lives.

The U.S.’s anti-sludge-combustication-rating ensured that Spain’s pressure couldn’t break its defense down. Stuck together in magnetized-globulated-adhesion (TM), the U.S. defense didn’t crack under even the most extreme Spanish pressure. Its thermo-activated-appendages got between hot Spanish shots and a cracked goalmouth.

Most importantly, the U.S. blocked Spain’s anti-hydro-viscosity-passing-completion-rating from getting too high. And anti-hydro-viscosity-passing-completion-ratings can kill. Obviously.

Also the U.S. had Oguchi Onweyu and Tim Howard.

Thank you.”


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+/- : SLIVERS OF SENSE IN STUPID STATS

Does Tevez Have the Best Plus-Minus in the Game?

Plus-minus differential has long functioned as one of hockey’s central statistics. Over the last two years, the stat has gathered momentum in the NBA to help measure an individual’s contribution to team performance beyond worn numbers like points and rebounds.

In soccer, the statistic is understandably ignored. Too many players working together on the field produce too few goals to statistically isolate one player’s contribution to team success. Except, that is, when you’re looking at Carlos Tevez.

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Without the facts to back it up, I’m willing to bet that Tevez has the best plus-minus differential in the Premiership this season. Of course, playing for United automatically gives any player a good plus-minus, as United have the second best goal-differential in the league. But Tevez’ hand in that number, both as a starter and substitute, cannot be denied. If I had more time and better resources I would prove that, proportionally, he has contributed to it more than anyone.

Against Tottenham on Saturday, Sir Alex Ferguson made one change at halftime, down 2-0 at home. He brought on Tevez for Nani. United then scored five goals in 22 minutes. Although not always present in the highlight-clips of those goals, Tevez’ presence impacted almost all of them. His defensive pressure repeatedly forced Tottenham to turn the ball over. He sparked the counter-attacks that Rooney and Ronaldo finished.

His productivity is undeniable, and leaves me scrapping for a way to statistically prove it. Working with the most rudimentary stats available on soccernet.com, I came up with this: United is 15-2-2 in the Premiership this season when Tevez plays over 45 minutes (9-3-3 when he doesn’t). If you think such performance doesn’t deviate enough from how United performed without Tevez to mean much, then consider that those two losses both came to Liverpool, games in which Tevez still produced. Tevez scored the lone United goal in September’s 2-1 loss. And he set up United’s opening goal in the recent 4-1 loss (a score line that didn’t reflect the closeness of the match) with an incisive ball to Park Ji Sun that drew a penalty.

Given his goals-per-minute played (my intern is looking into this), and his stunning shot percentage, Tevez appears one of the most efficient players in the game – along with teammate Rooney, Messi, and a few strikers who see far less of the ball. Playing limited minutes, and openly frustrated by it, Tevez has still amassed 14 goals in all competitions this year. He scored these goals on 112 shots. Last season, he started 31 Premiership games and grabbed 14 goals and 7 assists on 92 shots. Compare these numbers to the 318 shots that Ronaldo has needed this year to get 31 goals, or the 324 that Ronaldo took in 2006/07 to bag 26. I’m not saying Tevez has been more productive than Ronaldo, as looking at shots vs. goals gives a limited and misguiding picture of a player’s productivity, but such numbers make you wonder what Tevez could do with more playing time, and more scoring opportunities.

His goals haven’t come in garbage games either. He has played a crucial role in United’s quest for the quintuple (now quadruple) this season. His four goals single-handedly crushed Blackburn in the Carling Cup. He scored two goals en route to a 4-0 win over Fulham in the FA Cup Quarterfinals. Among a few crucial Champions League goals, he scored a decisive goal in the first leg against Porto, immediately after coming off the bench.

Can plus-minus be a telling statistic in soccer? Haven’t people tried this, and where can I find it? Which other players have the best plus-minus scores in the game or on their team? Mascherano? Fabregas? Ferdinand?◊

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SOCCER ANALYTICS: ADDICTIVE AS JUNK AND ABOUT AS USEFUL

Why The Guardian’s New Football Analytics Tool Doesn’t Mean Much, Yet.

Man, technology moves too fast for our own good. I thought we were years away from this, but here it is – real time (almost) analytics of Premiership games. The Guardian Online has unleashed some of the player-tracking technologies of ProZone to the general public so that football junkies can track events like passes, shots, and tackles for every match over the last two and a half seasons. “Interactive Chalkboards,” as they call them, let you compare player or team performances side by side. You can validate your observations, or (theoretically) test new theories.

by Guardian Chalkboards

This is good news for those football addicts always on the lookout for new forms of the drug. But, as I argued in a past post, Fact vs. Faith: Considering the Impact of Statistics on the Beautiful Game, this isn’t revolutionary, yet.

This type of analysis will have a few not-so-new results. First, spazoids will use it to validate observations that are painfully obvious for anyone who watches the game under the microscope with any scrutiny. For example, Morinho2030’s will propose astute observations like this “award-winner” on The Guardian’s website: “Tottenham’s wide players Lennon and Modric take up very different positions on the pitch.” Wow. Can you shed any light on the way Ronaldo plays a different wide role than Park Ji Sun?

Instead of revealing facts about performance, as The Guardian states, stat-based analysis will provide us with another way to evidence our empirical theories about a game. It will temper and bolster observation, not replace it as the most objective way to analyze a game. In other words, the “objective” data that this analysis provides will continue to lead to subjective arguments. You can still interpret the data in different ways.

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But that doesn’t mean this technology is useless. Arguments are great. They’re why sports, especially soccer, were created. They’re what propel the sport forward.

As maybe the most revolutionary affect of Interactive Chalkboards, they allow an instantaneous and informative analysis of a game. You can now digest the flow of a game, or the relative effectiveness of one player, with a few clicks and drags.

One day soon we’ll develop a statistical language that works in concert with a honed version of this analytical data. This is why I’ve locked my intern to Interactive Chalkboard until he creates stats for the following terms: “Attacking Third Productivity Rating,” “Defensive Third Turnover Rate,” “Forward Passing Success Rate,” “Long Ball Success Rate,” “Off-Foot Effectiveness Rating,” “Long Shot Accuracy Rating” and the vaunted “Player Efficiency Rating.”

How long will it take for stats like these to appear along with the analytics that The Guardian provides?

I’m not saying I want this garbage flashing across television broadcasts. And I’m not saying these stats will solve any arguments about player performance. These terms will probably cause useless mathematical arguments of their own. But they will provide a new dimension to player analysis.

For now, my time is better spent watching games than crunching numbers and dividing fractals of passes on Interactive Chalkboard. It’s a little more meaningful and a lot more fun. Even when we do develop a new statistical language and a more sensitive real-time version of the Interactive Chalkboard, the big question will still remain: will this analysis prove any more reliable than a good set of eyes?

I don’t think so. At least, I hope not. Then I might have to start reading poetry or something instead of watching the sport I love.

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FACT OR FAITH: CONSIDERING THE IMPACT OF STATISTICS ON THE BEAUTIFUL GAME

*Originally published in April, 2008

Soccer has long had less capacity for statistical analysis than any other major sport. This is primarily because of the nature of the game, free-flowing and low scoring and simple to its core. It doesn’t offer the many frames for measurement that so many American sports rely on. Baseball, basketball, and football offer a slew of averages, splits, percentages and ratios that keep Phd-level mathematicians employed.

Soccer’s insulation from data and numbers is part of what has kept it romantic and hard for so many Americans, addicted to statistics-saturated fantasy sports leagues, to stomach. It is truly all about feeling—for players, managers and fans alike. Every sport runs on illogical passions and beer-fueled arguments, but none more than soccer. It is innately subjective. This preserves the ignorance and bias of all who analyze games and players, but it also preserves the game’s lyrical nature, the color and light of perspective and narrative. It protects soccer from the type of statistics-drooling fans that infest baseball—the kind that give you regrettably well-researched evidence of a player’s rating as based on fielding metrics technology even though they don’t know how a shortstop should straddle second base when making a tag out. In soccer, by contrast, maintaining an informed opinion about a game or a player has always required two things: you need to have a deep understanding of the sport, and you need to watch games unfold.

In the last ten years, however, the hot probes of science have been busy giving soccer a lobotomy. Software companies like ProZone, which give computerized video and statistical analysis of games, claim to provide an objective picture of both a player and team’s performance. ProZone, which doesn’t come cheep for the pro and amateur clubs that use it (yearly subscriptions cost around £130,000), can cut through some crucial aspects of soccer’s obscurity. Managers use it as a tool to improve team tactics and player technique. But how deep an impact can these programs have on a game so rooted to subjectivity?

Although they will have a permanent and valuable place in the game, computerized analysis programs will probably never replace the good old empirical one, a keen set of eyes. And although such programs make some aspects of soccer more transparent, they are also adding a new language to the surface of the game that tangles us in new arguments and new questions. They compound the game’s subjective mystique at the same time they erase it.

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Some managers claim that ProZone proves most valuable when evaluating player performance. ProZone’s biggest champion, Arsene Wenger, praises the program’s ability to reveal the quality and speed of a player’s decisions on the ball.

“Technical superiority is measurable,” Wenger stated in a recent and often-quoted interview conducted by Total Youth Football Magazine. “In the past it was just about feelings, opinions. So I thought, ‘that’s not good enough,’ and I wanted to know a little bit more. I am always in the situation where I have to judge people, and the more concrete objective numbers you have the better you can achieve that.”

ProZone, which uses eight cameras to track infinitesimal movements of every player on the pitch, doesn’t only measure completed passes. It can gauge the circumstances of these passes, where they went, and the other options available. So a player can no longer blame a poor performance on his teammates’ lack of movement, or a lack of options, without this excuse getting scrutinized.

Getting such visual and statistical data gives perspective on a player’s performance, but it seems to prove more valuable as a coaching tool than as a way to rate player value. Reviewing a player’s decisions with the ball, seeing where they maintained possession and where they lost it, could help a player make more positive decisions or movements in a game. But breaking a player’s success down to statistics has flaws and gray areas. Unlike baseball, in which numbers reveal truth over time, soccer relies too heavily on intangible and immeasurable elements, like team chemistry and deception and creativity, for statistics to conclusively quantify an individual’s value. For this reason soccer will never see an equivalent to a book like Moneyball, which showed how certain stats (batting average and stolen bases) had long been overvalued at the expense of others (like walks). No matter how much we try to break soccer down, minute frame by minute frame, it can never have the same statistical framework as baseball.

In a 2005 article on ProZone published in The Independent, former Derby County Manager Phil Brown puts it succinctly: “You wouldn’t pick a team on it but it can back up your gut instinct.”

Relying purely on data to judge or scout players would skew pictures of player value and potential. For example, I am convinced that Cristiano Ronaldo, arguably the best player in the world, would have been rated as one of the most unproductive and inefficient players in the Premiership had he been gauged on ProZone software back in 2003-04. Maybe someone at Manchester United with access to these archives could prove me wrong, but I believe that only observing a budding Ronaldo in the flesh, bearing witness to his supernatural quickness and touch, could have suggested that he would become such a dynamo. The same can be said about great athletes in other sports. But in other sports statistics are more closely linked with ability.

ProZone’s programs can, however, undoubtedly improve a team’s tactical sense and precision. In a 2005 interview with The Independent, Alan Pardew talked about how ProZone helped him see passing patterns in an opposing team’s offense that his team (then Reading) worked to cut out.

“For scouting the opposition and analyzing your team it gives you a wealth of information you cannot get with the naked eye,” Pardew said. “It is a supplement to your judgment.”

ProZone can make defenses more aware, so that they know where they break down and which spaces they need to better cover. And it can make offenses more aware of how they can link passes and find gaps in an opposing team’s defense.

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Big Sam Allardyce - a big fan of using statistics to gauge player performance

But coaching by placing too much weight on data threatens to make teams one-dimensional. It can force teams into using too many pre-determined movements, stiffening a game that depends on the magic of creativity and improvisation. A few managers, for example, have used statistics to produce brutally predictable styles. As Matt Dickinson points out in a recent article for The Times Online: “You cannot mention [Aidy] Boothroyd and [Sam] Allardyce in the same sentence without someone saying that all statistics produce is robotic football.” Dickinson highlights the importance Allardyce places on getting measurable production out of each position, such as a “quota of crosses” from his outside wingers. And some pub teams play with more fluidity that Boothroyd’s Watford.

Despite the boring nature of these two manager’s styles, however, they have both enjoyed success. And then, as a crushing counterpoint to the assumption that statistics-based coaching produces stiff soccer, there is Wenger’s Arsenal, a team that wins while playing one of the most fluid, incisive, and enthralling passing styles in the game.

Statistical analysis suggests that efficiency can take many forms. If anything, the meaning of the word efficiency has become increasingly blurred in the sport. Does it mean producing a certain amount of crosses? Does it mean linking the most passes in the least amount of time while going forward? Does it mean producing the highest levels of measurable technical superiority on ProZone? Although statistical programs can offer managers some logical conclusions about strategy and player performance, they also breed more questions. Because managers still need to interpret the heaps of data that ProZone gives them—deciphering a radar-like language of arrows, dots, and numbers—many interpretations exist. Different managers will have different opinions about how they can tweak their shape, strategy, and player roles to improve their team. Better information requires more refined and complex strategies, and also vastly different ones.

An overflow of statistics also poses another hang-up for managers. It can cause managers to focus on the minutia of the sport instead of taking a more comprehensive perspective. In striving for certain levels of efficiency, stat-obsessed managers might forget the root purpose of the game: putting the ball in the back of the net. Although we can attribute Arsenal’s drop in the league table to a number of factors, it might suggest that obsessing over efficiency can sacrifice results. Maybe Wenger will have the last laugh when his test-tube babies come of age in the next few years. But this season’s tables might suggest that while Wenger was busy grooming players to rate highly on ProZone, Chelsea and Manchester United followed the tried and true formula of stockpiling proven players that produce goals and win games. Call me crazy, but I think the most “efficient” team is usually the one with the best goal differential at the end of the season.

Maybe in the future, when every club employs PHD-level statisticians and when ProZone-inspired technologies will be available in real time for the masses watching games from home, we will have a more refined statistical language that will come closer to revealing what efficiency truly means. We will throw around stats like “Attacking Third Productivity Rating” or “Forward Passing Success Rate” that could highlight underrated players and show which teams have been more effective advancing the ball. When this occurs I might eat some of my words. But I predict that even using this sort of statistical language will only produce more arguments about player value and playing style. We will more firmly pit statistical fact against observation and gut feeling.

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More "Wenger" than evil?

Maybe scientific managers like Wenger have set the stage for a war of Lost-like proportions within the game. Soccer is the island, a mysterious, untamable, and beautiful beast. Wenger is (maybe a little unfairly) the character Ben, leader of the “Others,” a master of manipulation, bent on scientific methods of deconstruction. His tinkering has bred tensions between future and past, brain and heart, fact and faith, design and free will

These tensions are not new in the sport, or any other sport. But as with Lost, in soccer it has never been more difficult than now to pull these forces apart from each other, to know which one is at work and which one to believe in. To dismiss ProZone and new forms of statistical analysis would be ignorant, but believing in them unconditionally might be more dangerous. Fans that do so will miss the true picture and beauty of the game. And managers that do so won’t survive.

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