Thursday, April 10, 2014

The State of Sports Analytics

Well, that does sound presumptuous now doesn’t it?  I mean, who am I to assume to know the current “state” of Sports Analytics?

Quick background – for the last 20 years I’ve been involved in a business discipline known as Enterprise Performance Management (EPM).  I’ve run my own practice in this field for the last 12 years (I tell everyone I made money for other people for the first 8…).  And I have done projects all over the world for a variety of companies across many industries.

Now, with that said, you can Google “Enterprise Performance Management” and you will invariably run across a reasonably authored Wikipedia article on EPM.  There are hundreds (maybe thousands) of books on the subject and if you’re interested I’d be happy to recommend some and also advise you which ones to avoid.

By the way, my particular “flavor” of EPM that I’ve developed over the years and delivered to my customers is a mixture of Balanced Scorecard (Kaplan/Norton), Six Sigma (Motorola) and TQM (General Motors).  I’m also known as a technical specialist in the area of multidimensional databases.  (that’s a fun Google query)

The world of sports analytics is evolving and its evolution is following a very similar pattern as EPM.  Sports Analytics seems to be about 10-12 years behind business analytics (decision support, business intelligence, whatever you want to call it…) but it all began in a very similar fashion – handwritten pencil and paper solutions (a.k.a. “old school”).

In the business world these were ledgers or other record keeping systems that evolved into what we know today as a spreadsheet (still the most widely used EPM tool).  Sports then evolved in to the box score and baseball charting.  I still see people charting baseball games from time to time, but over time the teams themselves moved on mostly to spreadsheets and databases.

Let’s stop here.  Why did we create these things?  It’s simple, we’re trying to represent what happened in the game without actually watching it.  Why?  Maybe someone didn’t have enough time to watch the game.  Maybe they weren’t physically capable or watching the game or they want to analyze what happened in multiple games.  Either way, a sheet or paper (or multiple sheets of paper) were now able to somewhat represent what occurred on the field of play.  The same reason necessitated these breakthroughs in the business world.

Sports then went to the first stage of what we now refer to as “statistics”.  We began to see things like batting averages, on base percentages and eventually we put stats like that “in a blender” and Moneyball was born (Gen 2).  Mr. Beane after all was just taking statistics and blending them together in such a way to value players differently than had been done before.  On the business side, the same thing occurred when companies began analyzing earnings per share or return on invested income or revenue to debt ratios.  Take a collection of data points that you had been “measuring” combine them together and create indexes/ratios that somehow represent the value of something.

A few years ago I did my first work with retailers that were using RFID chips to follow supply chain events, understand inventory and (in some cases) automatically replenish when certain levels were reached.  Cool stuff.  No longer did management need to manually place “orders” and constantly keep inventory, you always knew what was there and could automatically calculate what you needed.  In the same way, we now have sports organizations that are experimenting with RFID chips, GPS locators, even microwave systems that map where bodies, equipment, referees, etc are on the field 100 times a second!  Wow.  Again, cool stuff, but that nagging “So What?” question rears its head… (we’ll save that discussion for another day).

So now the sports world has entered in to what I call the “circles and triangles” phase.  Business went there for a while too (and abandoned it fairly quickly).  You take the enormous amount of data (not information) produced by the above systems and then graphically represent (most often by circles and triangles, hence the name) where everyone is on the field.  You can see speed, acceleration, x/y body position, really neat stuff.  My only question is (not “So What?” I know you guys are tired of that one already) if you’re sitting there for 90 minutes (or whatever) watching circles and triangles, why don’t you just watch the actual game itself!?!?  By watching film you can see where the person was looking, what their body position was, where their hands where, etc, etc, etc  BUT NOOOO…  millions of dollars are being spent right now to simplify that down to circles and triangles…  You can tell how I feel about that.

Now, there are other pieces of information, like telemetry that can be gathered by these system…

Speed of a player?  That’s great.  Anyone who solely bases decisions on speed alone needs to head to Jamaica, there’s a guy down there, last name is “Bolt” I believe that you’ve got to sign right now.  Basing player decisions on how far (distance) a player can run?  There’s some guys from Kenya (Wilson Kipsang for example) that can flat out run forever.  Last I checked he was not under contract by any football (soccer) organization, easy negotiations!  Even mixing some of those data points together still (IMO) doesn’t give you ANY indication of how well someone is playing the game.

Now, I’m not all negative on these types of systems.  I can see their use as far as training is concerned and also in-game analysis of fatigue.  But from a quality of play, I really don’t see much use to these (very expensive) systems.

A piece of advice.  In the business world I’ve always advised my clients to “not buy the demo”.  There’s a lot of flash and some really cool technology out there, but ask yourself what does this do to improve my performance?  Here’s where that “So What?” question comes in handy.  Yeah, the demoes are pretty, but in day-to-day work in my organization is any of this really going to make me better somehow?

Another piece of advice.  Never, ever invest in something unless there is a direct, provable way to exemplify how it is going to improve your organization’s performance.  Now THAT is something that has come to prominence in the business world the last few years, I hope the sports world also realizes this concept soon.

Monday, April 7, 2014

“Old School”

“Only a fool trips over what’s behind them” – Albert Einstein

Blogging is great.  As I sat down to write this with an idea in mind I went through several ways of starting this off.  First of all, I’ll try to make this short.

The above quote is really more about not making the same mistakes twice and not dwelling on the mistakes you have made.  I couldn’t agree more.

On the other hand though, we shouldn’t “throw out the baby with the bath water” (I’m probably dating myself with that reference).

What do I mean by this?

Last week I had the opportunity of sitting in the same room with an “old school” football coach that I greatly admire.  I’ve followed his career since I was a kid really (sorry coach, another age reference).

The only “bad” part of the meeting was that I walked away with the impression that this coach was intimidated to some degree with the technology around the ideas I was presenting.  I tried my darnest to get across to coach that what Real Sports Analytics is all about really is just a natural progression of old school thought.

We believe in film study.  We believe in observable metrics.  We believe in coaches just like him watching film and evaluating how well the game is being played (film don’t lie).  We embrace the concept of the “qualified observer”.  And we most certainly want to tap into the incredible knowledge possessed by some of these “old school” coaches.

The technology enables us to do things with this collected information and present it to coaches, players, administrators in an easy to understand manner.  Yeah, that’s great.  But the old adage of “garbage in, garbage out” applies here as well.  We need to be collecting and analyzing good information to optimize what we deliver with Real Sports Analytics.

If that’s not “old school” I don’t know what is.

My next blog post (already working on) will be focused on the current state of sports analytics and how closely its evolution has mirrored the evolution of business intelligence in the business world.