Geography · Economics · Visualization

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.

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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




MapBrief Geo Predictions for 2014

Soothsaying is so much part of the human condition that, like so many pointless pleasures, ancient scripture took a very dim view of it.

But for us in tech glib optimism is the default setting.  Piggybacking on the predictions of others in the geo industry, I offer the following the prognostications based on little other than personal bias:

1) Geo Will Continue to Grow; GIS Market Share Will Continue To Decline

Geographic data, spatial analysis, and cartography will all enjoy an increase in financial investment and general public awareness in 2014.  But the percentage of this content generated by traditional GIS software will decline.   The spatial-isn’t-special mantra becomes entrenched as interesting geo applications increasingly “happen” elsewhere such as

  • in databases unmediated by geo middleware,
  • custom search applications powered by Solr/ElasticSearch et al
  • statistical analysis packages such a R and the emerging Python ecosystem
  • purely in the browser via Javascript APIs and visualization libraries

Even better from the end-user perspective, instead of the brickwork of cryptic icons that passes for UI in the GIS realm, mobile apps will demand of their users little more than having their phone turned on.

But worry not GIS worker: spatial might no longer be special but projections, datums, and legacy file formats will continue to be very, very special.

2)  Remote Sensing Becomes Something Other Than Background Images

All hail the Geo-Panopticon.

Check out this image of Singapore harbor (2nd image down):  it’s a little bit cool.  But the quicker re-visits promised by newcomers Skybox Imaging and Planet Labs mean new products to tell us just where each of those ships in the harbor has been and help us track where they’re going to. Or at least that’s the hope for an industry that’s still all-too-dependent on government clients.


3)  Postgresql Becomes the Default Choice
2014 is when conventional wisdom catches up to what we PostGIS users have long known:  PostgreSQL is the sh#t.  As platforms such as EC2, OpenShift, and Heroku make it dead easy to spin in it up, we’ll look on with abject pity at the devs making do with MySQL on their $3.99/month commodity shared hosting.

4)  The “Enterprise” Won’t Move As Fast As You Want It To

Sure, they’ll continue to say the right things: “breaking down silos”, “getting smarter with data”, etc., etc.  But you know what’s more powerful than the new possibilities unleashed by technology?

Human inertia.

Or, more specifically, the entrenched interests embedded in a calcified org chart.  Thus the magical thinking of “we’re going to do all these wonderful things with data that will increase profits and efficiency without threatening the status quo.”

Because “disruption”, like “minor” surgery, is best experienced by others.   When you are a middle manager being kept up at night by the ghosts of Future College Tuitions, non-threatening nibble-around-the-edges small improvements expensively offered up by your friendly long-time vendor are preferable to anything that has even a whiff of cutting-edge.

5)  Hadoop Will Become Even More Beloved Among Those Who Don’t Have Big Data Problems

The vast majority of organizations do not have Big Data problems.

They have small and medium data problems.

These everyday small and medium data problems usually aren’t difficult technical problems per se: they’re often solvable with database and ETL tools already on hand, perhaps with a dash of statistical analysis.  But like in #4 above, they face the formidable foe of status-quo processes and the executives that cling to them.  Om Malik has a wonderful post about how everyday customer experiences remain un-informed by the unsexy data that companies have been collecting for years.

All that said, we’ll grant you that ‘Hadoop’ is still a fun word to say.

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On the other hand, the combination of the Apple iWatch and the next iteration of Google Glass could be the game-changers that we’ve all been waiting for.

If so, I’ll gladly issue a breathless retraction of all of the above.


—Brian Timoney

Crystal ball photo courtesy of   spratmackrel’s Flickr stream
Elephant watercolor courtesy of ‘s Flickr stream