Geography · Economics · Visualization

Data Insight, Reputational Risk, and Bill Belichick: Sports Analytics & Business Analytics, Part II


Can everyone immediately cite your worst professional decision?

If you’re 3-time Super Bowl champion and coaching mastermind Bill Belichick, any moderately savvy NFL fan would blurt out “4th and 2“.


Go for it on 4th-and-2 on your own 29 yard line with 2:08 remaining or punt to the Colts and give Peyton Manning the opportunity to march down the field?  Given the Colts had only one timeout, a first down would almost guarantee victory.

Belichick went for it; they didn’t make it; the Colts march in from the short distance to win the game.

And by most accounts, the odds were in his favor.

Insight Is Not Cost-Free

So if widely respected championship coach can get crucified for playing the percentages in a non-traditional way (during a regular season game in November), why are you surprised when your precious analytic insights that have even a whiff of the counter-intuitive fail to gain traction?

Statistical reasoning is abstract; middle-management reputational risk is very real, very immediate.

We can all applaud the “democratization of data” and tools that empower analysis-for-everyone. But if that means the status quo is at risk, well then, that’s a whole different conversation.  A conversation that’s typically the province of well-dressed, well-paid consultants rather than, say, you the underling who is a bit brighter than the good folks you report to.

Or else it’s the rare don’t-give-a-damn outsider like “The Coach Who Never Punts“.



Probabilistic Thinking In A Binary World

The most entertaining side-show of the 2012 Presidential election was the dust-up between Nate Silver and TV host Joe Scarborough when the latter decried anyone who declared that the race was anything but a 50-50 proposition.  Silver, of course, was drawing massive page views at the New York Times with his daily calculations of election probabilities using a large dose of Bayesian methods.  The revelation was that putatively intelligent people such as Morning Joe much prefer thinking about outcomes in binary/yes-no/Manichean terms rather than as shifting set of probabilities.  Especially when it pertains to a topic in which they are emotionally invested.

So when pitching a middle-manager on workflow improvements that have  an 83% chance of success, you think you’re saying “pretty good odds” when in fact what they are hearing is “it might not work.

*  *  *  *  *  *

Moneyball” has become the fashionable pop culture short-hand for analytics-driven decision making: but recall even Brad Pitt and his good looks encountered institutional resistance.

Without Brad’s good looks and Bill’s Super Bowl rings, what are you to do?

Spend as much time analyzing your organization’s culture as its data.


—Brian Timoney




Why We’re Smarter on Sunday: Sports Analytics & Business Analytics, Part I

We all remember when we first fell in love with tabular data.

For me it was the list of baseball batting averages of every major league player that was published in the Sunday newspaper. Still in church clothes, I’d commandeer the sports section and, donut in hand (the other Sunday indulgence), spend the next twenty-five minutes digesting line-by-line the offensive output of hundreds of players.

In 2014 it’s a bit different: all of this information and much, much more gets updated in near real-time on my phone.

We sports fans live a very strange cognitive double-life: we’re far more analytical about the teams we cheer for on the weekend than the organizations that provide our paychecks during the week.

* * * * * * * *

Information So Important, It Comes Once A Month

Before the first Friday morning of every month, a curious hashtag pops up on Twitter: #NFPguesses. Economists, business journalists, and assorted finance types weigh in with their guesses of the US unemployment rate and jobs added to be reflected by the Non-Farm Payrolls (NFP) report.

This number moves markets and political polls.

And it comes out once a month.

UPS used to have a slogan “moving at the speed of business”. Turns out, even in 2014, a whole lot of business is based on the same old monthly and quarterly reports–just like in 2004, 1994, 1984…

In part III of this series we’ll examine the tempo of data and business models.  Suffice to say when we tell our grandchildren about how we used to gather around Twitter at 8:30AM EST on the first Friday of the month to get the latest unemployment numbers, it’ll sound stranger than the Pony Express anecdotes of yesteryear.

(Well) Beyond the Pie Chart

Not only is the sports world is ahead of most of the work world in the tempo and freshness of its data, but it’s also showing itself more adventurous in the realm of data visualization.

An interesting application of heat mapping seen in the Daily Telegraph and BBC’s Match of the Day are the plots of player movements in the other football (soccer).  Below is a heat map of the wandering lethality of Chelsea’s Eden Hazard against Manchester City–


Worth noting that Match of the Day is broadcast on late Saturday evening in the UK: can we assume a good portion of the viewing audience is less than 100% sober? And yet what they’re being called on to process is more nuanced than whatever xeroxed chart is being passed around at our Monday morning staff meeting.

Where presumably everyone is 100% sober.

A Geographer Dominating Sports Micro-Geographies

Here in the States, some of the most innovative sports visualization is being done by Geographer Kirk Goldsberry.  (Like a legit Geographer–PhD and everything).  And we’re not talking a few color plates accompanying a paper in the Annals of the AAG–his stuff appears on ESPN’s web platform.

Which would make him the most read academic Geographer working today.


What’s worth pondering about Goldsberry’s work is how he communicates dense, multi-variate data to a very large general audience and draws out the most salient information, even it takes hand-drawn circles.  One of the bigger sins of visualization is, in the name of displaying all of the data, not directing the viewer to the most interesting/important information.

And not providing a meaningful point baseline of comparison.

What I like about the chart below is that the variation in LeBron’s shooting percentages in different areas of the court is a little bit interesting.  But it’s the diverging color-ramp of “efficiency” that lets us assess his relative strengths compared to other players in the league.  Those dark blues and dark reds are the real story of the visualization.



No Cheering in the Office

What’s been fascinating about the rise of sports analytics is that the momentum has been largely created outside the leagues themselves.  Take the emotional over-investment of a large portion of the public and amp it up with gambling, fantasy leagues, and multiple 24-hour sports tv and radio networks: the hunger for information is immense.  Despite the data deluge, resistance among traditionalists has been very real over the last 20 years.  In part II of this series will take a look at the battle happening both in your workplace and the stadium: the struggle between Analytical Insight and Reputational Risk.


—Brian Timoney

Calendar photo courtesy of   Joe Lanman ‘s Flickr stream




In Praise of the Static Map

You need to make a map.

And you want to use the web.


If you’re a geospatial professional it’s likely you misapprehend the task in 3 crucial ways:

  • You will  underestimate the time it will take to create an interactive map using one of the usual Javascript mapping APIs.
  • You will overestimate the amount of time your audience will spend using your map.
  • You will overestimate you audience’s enthusiasm for “interacting” with your map.

If time is money, then my money-making advice to you is…embrace the Static Map.


The Browser is Your IDE

If the phrase “Integrated Development Environment” doesn’t ring any bells, then Static Maps are a great place to start web mapping.  Most of the well known services have Static Map APIs–Google Maps, Mapquest, Bing, Mapbox, et al–that are driven completely by URL strings entered into your browser.  You simply specify parameters for height, width, zoom level, coordinates of your point/poly/line overlay, color, etc. , etc.

So, for instance, let’s draw a polygon around Walter White’s house in Albuquerque, New Mexico.


This is created simply using these URL parameters–

&key=<your key here>

Fairly straightforward, no?  And since fundamentally what you’re doing is string manipulation, the door is open for you to become the danger by making URLs in bulk using some Excel CONCATENATE fu.

You are the Web Mapper Who Knocks.

Saving Time Means Getting Real

Many of my client needs include maps that the intended audience will spend about 8 seconds looking at.  Sorry, but 8 seconds of viewing time means it’s not worth my time to cook up pretty D3 or fancy interactive controls.

Besides, they don’t know what those controls mean.  Or how they work on their phone.

So here’s a swatch of oil well drilling activity in North Dakota:  note that the (Mapquest) static map API automatically de-clutters the points for me.  In real life this means I run dozens of these maps every night and I don’t have to qa/qc them.  More rem sleep is a win for everyone.

82.3% of Interactive Maps Are Used To Make Screen Captures*

(*invented statistic)

Another unpleasant truth that web mapmakers dare not admit to themselves is that a depressingly large percentage of people use web maps to manually create screen captures to insert into a PDF or PowerPoint.

So let’s do them a solid and save them from MS Paint by giving them the static maps they really want.

If we have some basic coding chops we can make pretty PDFs (who doesn’t love a PDF?).

But with a little scripting elbow-grease we can also go to 11 by embedding maps inside Excel spreadsheets:


In this use case, the attribute data is as important as the geography–by simply scrolling down in Excel they can absorb and mentally filter on multiple variables all while sipping contentedly on their morning coffee.

When I suggested on Twitter that embedding static maps inside Excel workbooks represented cutting-edge Geo Business Intelligence, I received this glowing reply:


Hands-Free Time-Series Cartography

Because hating animated GIFs is hating life itself.

(Mean center of US population 1790-2020)



—Brian Timoney


Marc Pfister created a Google Maps Static API playground to help you get started.


Twisted watch photo courtesy of   Metrix X ‘s Flickr stream