Data and Analytics in Soccer, Rise of Deeper Decision Manking

The Rise of Deeper Decision Making, Money and data driving next steps. 

Data and Analytics in Soccer

As the 2022 FIFA World Cup gets underway in Qatar on November 20, some of the most important action will be taking place off the field. Most teams will be furiously crunching data on goalies’ tendencies to try to determine how to win a penalty shoot-out if there’s a draw at the game’s final whistle. But this type of single-instance analysis is only a small part of the revolution taking place in the boardrooms at some of soccer’s biggest clubs. Today, the most important hire is no longer the 30-goal-a-season striker or an imposing brick wall of a defender. Instead, there’s an arms race for the person who identifies that talent.

Barcelona players in a tight huddle as they celebrate a win during the 2012 UEFA Champions League

How the best soccer team in the world lost its luster,  BY SIMON KUPER

Members of the Italian national soccer team celebrate scoring a goal during a qualifying match for the UEFA European Championship.

Successful teams: Superstars need not apply, BY BEN LYTTLETON

Sports Industry Outlook 2022 

The research department at Liverpool FC, the team that won England’s Premier League in 2020, for example, is now led by a Cambridge University–trained polymer physicist. Arsenal FC recently hired a former Facebook software engineer as a data scientist, and current Premier League champion Manchester City hired a leading AI scientist with a PhD in computational astrophysics to their research department. Chelsea FC’s new American owner, Todd Boehly, spent his summer trying and failing to hire a new sporting director with a data background. These are all examples from England, where the sport’s richest clubs are investing to gain an edge—and often recruiting from ahead-of-the-curve clubs with proven track records, like Monaco, in the French League, and the German club RB Leipzig.

Soccer has a rich history of this sort of analysis. Charles Reep, a military accountant, became soccer’s first data analyst in the 1950s, predating personal computers, Billy Beane, and the Moneyball moment in baseball, in 2003. That was followed up, in 2009, by the soccer equivalent, Soccernomics, by Simon Kuper and Stefan Szymanski, and data-driven sports analysis entered a new era. Among Kuper and Szymanski’s findings: goalkeepers are undervalued in the transfer market, and players from Brazil are overvalued.

I cofounded a football consultancy ten years ago with the authors of the book. One of our first clients was the Netherlands national team. We’ve been applying data to soccer for a while—but a lot of it is backward-looking, trying to mine past performance to account for what could happen on the field. We provided the Dutch team with a penalty-kick dossier before the 2010 World Cup final against Spain, in which Professor Ignacio Palacios-Huerta, an expert in game theory, showed penalty trends and patterns of Spain’s kickers. Spain scored four minutes before the end of the game to win, but the Dutch were confident they would have won on penalties.  .... ' 

AI Enhanced Editing of Sports Coverage

Watched some of the recent Wimbledon, and IBM frequently pointed out that Watson was choosing and editing and delivering the film clips based on measures like human applause.   And then writing copy based on some 20 million clips?     Well it didn't impress me, but I have never been responsible for measuring real time editing of many, many sources of tape.   So it seems it may soon become the standard thing.

IBM’s Wimbledon-watching A.I. is poised to revolutionize sports broadcasts  in DigitalTrends.

Among the most lauded essays ever written about the game of tennis is David Foster Wallace’s 2006 article “Roger Federer as Religious Experience.” Originally appearing in the New York Times, the approximately 6,000-word tribute to one of the world’s most supremely talented players reads, as its title makes clear, more like a divine celebration than a piece of sportswriting.

Wallace (and he was certainly not the first writer to do this) gushed about high-level sporting achievements as though they were more than just superb technique; as if they were, somehow, a transcendent portal to godliness. Ordinary mortals like you and I could comprehend what was happening, but only barely. In order to truly appreciate Federer’s athletic feats, we needed a member of the priesthood — a talented youth player like Wallace had been — who could make it intelligible to us.

Why mention Wallace’s almost decade-and-half old essay on a tech site? Because IBM recently unveiled the latest iteration of its impressive A.I. technology — and it’s learned to appreciate tennis on a whole new level. Well, sort of.   .... " 

Sports Decision Making

Have seen lots of examples addressing patterns of athletic data, but not specifically decision making.  Makes this interesting.  Deep learning Techniques and athletic decision making.  Via the CACM.

Sports Analytics not Always a Slam Dunk

In our Columbia course we have been using sports analytics as a disruptive example of the analytics technology.  Movies like 'Moneyball' imply it is fail safe, but of course it is not.  For my students and further reference to cautions  This piece addresses some of the issues.

Sports Analytics Taxonomy

Gary Cokins writes:

My analytics colleagues,
  
I am writing you to share a recently published article that I co-authored describing a “sports analytics taxonomy”. Everyone loves sports !  ...

The article is a result of a volunteer task force I am on with three others with www.informs.org . As some of you may know INFORMS is a premier professional society with the operations research (OR) community. My 1971 Cornell University degree was in OR.

What led to writing this article was my first meeting with the other task force members. Each has been involved with consulting to professional sports teams and in some cases university athletic departments. I naively presumed that sports analytics is narrowly limited to professional athlete selection or salary negotiations and sports fans interest in “statistics”. I quickly discovered that it covers much broader applications such as stadium management, league scheduling, athlete biology performance, and gambling. I suggested that we first develop a “taxonomy” with tree-branches-leaves to capture the wide breadth of sports analytics, and which can serve as a platform for many applications described in the article (e.g., assessing the maturity of analytical methods to support decisions, indexing articles and academic papers).

The article is on pages 40-43 in the magazine in this link (and if you care to receive its pdf file of its 4 pages, request it from me) :

http://viewer.zmags.com/publication/085442e2#/085442e2/42?platform=hootsuite

You can read about what is occupying my time since I retired from SAS in my website at www.garycokins.com .  .... 

Watson Analytics for Superbowl Front Office Data Analysis

Good, fairly simple example of the automation of analytics.  Here using Watson analytics.  With commonly used exploratory goals.   Explore it for free:

In Business Insider:
" ... In order to help sports fans get started, IBM uploaded a slew of offensive statistics from the 2014 NFL season (provided by SportsData LLC) into its database. For instructions and a demo of what you can do with NFL stats in Watson Analytics, visit the Watson Analytics Storybook.

From there, fans can explore data visualizations of how certain trends played out during the season — like a weekly breakdown of interceptions thrown by the home and visiting teams — and even ask the system predictive questions like, "Which factors lead to rushing touchdowns?" .... " 

Sports Tactics and Conversion Rates

In Conversioner:  Nicely done short piece that brings together a number of data and behavioral process  methods to address selling.    " ... Surprisingly, competitive sports are much like conversion optimization. Whether you’re playing a sport or optimizing a web-site, you want to be the best you can be in order to increase conversion rate. While conversions might be points or goals in sports, they are purchases and downloads in conversion optimization. Here are some insights that we can gain from competitive sports and apply to conversion optimization. ... " 

Big Basketball Data

In Wired:  Excellent non technical look at tracking the complexity of sports.  Have followed this technically for a few years, this is a good non-tech view.  Nice example too of how data can be scrounged from multiple sources ...

" ... tracking 10 players in constant motion isn't trivial. He started scouring fan sites and sports coverage, and eventually he found stats for every shot taken in the NBA. It wasn't much—just who took the shot, from where, and whether it went in. But it was a start.

The data wasn't exactly private, but neither was it public—Goldsberry scraped it from the web. Specifically, he found that ESPN.com published shot charts with the box score of each game. He found the files that powered them and grabbed their information. “They were publishing these data sets but not using them to the potential that I saw in them,” Goldsberry says.

Eventually he pulled together a database with the spatial coordinates for every shot taken from 2006 to 2011—more than 700,000 of them. Then Goldsberry the cartographer teamed up with Goldsberry the hoops junkie. “I wanted to find a way to get this data to sing a new song, to tell us things like where Kobe is good and where Kobe is bad,” he says. And he wanted to do more than just crunch numbers. Goldsberry wanted to show people, “to communicate to players, and fans, and the media.”  ... ' 

For the technically minded here is the paper.

NFL Tackling Big Data

In our recent executive briefing we used the work by the NBA using video imaged game recording for gathering big data to understand the detail of game and player behavior using analytics.  An excellent example.  Colleague Walter Riker points out that the NFL is not far behind.  Here reported on in CNN/Fortune.  With the addition, it seems, of sensor devices to gather data beyond the video recording used by the NBA.   This is becoming common.  Gather all the data,  you will find analytic purposes for it in the future.

Review: Modeling Techniques in Predictive Analytics

Modeling Techniques in Predictive Analytics: Business Problems and Solutions with R  by Thomas W. Miller 

This book does an excellent job of defining prediction, which I have rarely found done well  in a text.  The first chapter: Analytics and Data Science, in a relatively few pages, defines both the value of visualization and the methodology for getting and verifying a prediction.  Nicely and very simply and accessibly described.   The R code for this and every chapter can be found online here.  I have yet to use or test their code, but it seems very well documented.   This book does not teach R. I did not expect it to, ... but anyone who knows coding can follow along after getting an introduction.

Following chapters address specific areas of application:  Advertising and Promotion, Preference and Choice, Market Basket Analysis, Economic Data Analysis, Operations Management, Text Analytcs, Sentiment Analysis, Sports Analytics and Spatial Analysis.  Each of these topics contain a number of foundation problems, and a book of this type cannot cover them all, but the examples used are reasonable starting examples.

I have read the introductions of several of these topics, and the explanations are well done.  Code is printed on pages. and is often long and somewhat hard to read.  I will probably follow it on the online forms.

The text is heavily footnoted.   I like that, but the having the footnotes in the text make it somewhat harder to scan, would have preferred them in the index.

The Appendix contains description of a number of R language packs to support work described in the book.  Using a language like R is all about building on the tested work of others, so this is key. Ongoing work is described, but this will be out of  date quickly.  It may have been useful to have a place for social and formal exchanges and updates.  Think of the book as a nexus for social
interaction.

Overall,  is very well done,  I expect to use several of the examples for applications. I have talked to two other people that have been reading and scanning it, and they also enjoyed its approach.

" ....  Thomas W. Miller, leader of Northwestern University’s pioneering program in predictive analytics, guides you through every step: defining problems, identifying data, crafting and optimizing models, writing effective R code, interpreting results, and more.
 Each chapter focuses on one of today’s most important applications for predictive analytics, giving you the skills and knowledge to put models to work–and gain maximum value from them. ... " 

NumberSense Reviewed

I have been looking for books that explain the difference of what I call analytics, in my long time consulting practice and the newly hyped arena of Big Data.   I am always also on the look out for books that I can use with client groups to explain how analytics is powerful.    The explanation has to be positioned with little or no complex mathematics.  The examples have to be clear, and beg for their simple reapplication to new business domains.

NumberSense includes these characteristics.   Easy to understand, non technical examples.  In the social/marketing/economic/sports domains.  Clear positioning about how the problems should be staged.  Not much about how the problems are technically solved, but that is for the data technologists.  Not a how to book, but sets up the crucial cautions very clearly.

I particularly liked the analysis of Groupon data, which clearly defines where claims and analyses can be wrong in marketing.   A good marketing analysis example.

Fung appreciates the fact that while having more, or 'big' data is useful, but it is more important to get the data and its analysis right, especially as it relates to the decision problem being addressed.  Numbersense is paying attention to the origin and context of the data involved, and knowing enough about how the analysis will be applied to the real problem.  Misinterpretation is the worst mistake you can make.

In the final chapter Fung describes a  day in his life as a data scientist.  This was painfully reminiscent of some of my own enterprise experiences.  Its often more difficult getting the data right than solving the technical problem.

As a decision oriented person you don't need to know the technical methods, any more than you need database expertise to create reports.  This books aims at the business problem and solutions, with a strong numerical focus.  Usually with basic math.   The title of the book NumberSense, is that quality of understanding when an analysis is right or going wrong, and what to do about that.   The data in an analysis does not have to be BIG or even complex, just correctly addressed.   The book and more about it:

NumberSense: How to Use Big Data to Your Advantage    by Kaiser Fung .

See also his Numbers Rule Your World blog site for day to day examples.

Examples covered: 

" ... How does the college ranking system really work?
Can an obesity measure solve America's biggest healthcare crisis?
Should you trust current unemployment data issued by the government?
How do you improve your fantasy sports team?
Should you worry about businesses that track your data?

Don't take for granted statements made in the media, by our leaders, or even by your best friend. We're on information overload today, and there's a lot of bad information out there.
Numbersense gives you the insight into how Big Data interpretation works--and how it too often doesn't work. You won't come away with the skills of a professional statistician. But you will have a keen understanding of the data traps even the best statisticians can fall into, and you'll trust the mental alarm that goes off in your head when something just doesn't seem to add up.... "

Unilever Spending, Partnerships Up

In AdAge:   This looks to be a considerable development:  " ... Unilever has struck global partnerships with Samsung, Sony's Arcade Creative Group and EA Sports as the packaged-goods giant looks to expand its universe of deals on the heels of a nearly 40% increase in digital spending last year. ... Programs are still in development, but the Samsung partnership will involve advertising and content creation for smart TVs, smart appliances and mobile applications. Initial projects will involve Axe and Hellmann's, said Gail Tifford, Unilever's senior director of media for North America. ... " 

Cleveland Indians Using ThinkVine

I just got a press release from marketing mix optimization and simulation modeling company Thinkvine saying that the Cleveland Indians baseball organization is using their technology for marketing mix type applications.  More here.  We tested and used their methods in the enterprise from their early days.    ... “Sports marketers need a high level of flexibility to adjust their plans during the season based on league standings or other factors that are specific to their business,” said Mark Battaglia, CEO of ThinkVine. “With ThinkVine, it’s now possible for sports marketers to forecast how varying marketing plans, along with variable factors such as team performance, influence targeted sports fans to purchase game tickets. This enables the Cleveland Indians to respond quickly and more accurately to maximize their budgets and keep revenue up.”  ...  

Business Intelligence Symposium

UPDATE:   I have now seen the list pf participants, and this will be an exciting and informative local meeting about the topic.  Meet a number of local practitioners.  Will include a talk by Glenn Wegryn, former head of analytics at P&G.   Also a sports analytics expert who works with the Cleveland Indians. Sign up now at the link below. 

Analytics In Action:  What do Jeopardy, Pampers and Major League Baseball have in Common?

A number of my former colleagues will be presenting.  

October 24, 2012

Full Description and registration.

From the UC Center for Business Analytics.  Headed by Geoff Smith,  P&G Alumnus.

Advancing Google Wallet

Google Wallet now accepts many card options.  We move closer to the electronic wallet.  Near universal capability is key.  " ... The newest version of Google Wallet now sports a feature that makes paying with a cellphone that much more a reality for non-techie users. Google has launched a cloud-based version of Wallet that "supports all credit and debit cards from Visa, MasterCard, American Express, and Discover," according to a post on the Google Commerce blog.... " 

Sports Analytics Blog

Paul Hare's blog:  The Numbers Don't Lie:  Statistical analysis of evidence in the world of sports.  Moneyball and beyond.

Analytics Magazine

The March April Analytics Magazine.  Lots of background and how-to information.    Sports,marketing, public sector, supply chain and more.

Sports Analytics: Beyond Moneyball

Excellent article in Informs' Analytics Magazine.   With links back to some detailed analytical studies in the sports industry.  May of these same thoughts can be applied to outside of sports.


" ... Over the past several years, the sports analytics field has been growing rapidly and has attracted a great deal of interest. Many of the unconventional strategies presented in the book “Moneyball” have become part of the new conventional wisdom, while the film based on the book has grossed over $75 million and been nominated for several Academy Awards. Despite the increase in data and analysis that can potentially inform more management decisions than ever before, too many teams do not engage with the tools and results of sports analytics, even when they are lurking in their own backyard... " 

DemandTec Retail Challenge Scholarship Awards

In an era rewarding mostly sports and celebrity, it is great to see math being noticed.  More. 

P&G Sports a Mobile Game

P&G's Downy plans a mobile scavenger hunt.  An example of brand oriented marketing gamificatition.

" ... Procter & Gamble fabric softener brand Downy will hold a smartphone-based scavenger hunt in Las Vegas next month to introduce a new product to a young, mobile audience. Downy Unstopables is a new line of scent beads that can be added to the wash to make clothes smell nice. On Dec. 3, smartphone owners in Las Vegas will be able to use their mobile devices to play the Downy Unstopables scavenger hunt for a chance to win a prize.    “With this promotion, Downy would like to dramatize the amplified sensorial experience that Unstopables delivers and leverage the city of Las Vegas because it is often seen as ‘the sensorial capital of the world,’” said Sherilena Strub, a spokeswoman at Procter & Gamble, Cincinnati, OH. .... "   Sign up with Downy here.