Last week, I caught a foul ball at a Spring Training baseball game.
OK...not on the fly, and not quite off the first bounce. But I grabbed it before it came to a rolling stop.
That still counts, right?
Before the baseball game started, I turned to my kids and told them we were in Foul Ball Territory -- the sections in the stands where batted foul balls were likely to land. And be caught by fans!
How did I know this? Or less arrogantly: What made me believe this?
Because I've watched enough baseball games to know where a high percentage of foul balls land. It's a pattern of batted ball behavior. Garnered from decades of experience from playing, watching, and attending games.
Where we at the epicenter of Foul Ball Territory? I'm not sure. But we could (dis)prove it.
What if we had the data to plot against the stadium seating chart? We could feasibly create a heat-map of where foul balls landed.
Professional sports is filled with data. Here are a few examples, with the last being exactly as I suggest above.
From Exploring Baseball Data with R, plotted batted balls for a particular player:
From Furman University research, data (shown as heat mapping) that supports the shifting of defensive position players for certain batters:
And from Time magazine, discussing an app that helps track and calculate balls batted into the stands, to suggest which sections receive the most foul or home run balls:
As you can see, some data does exist. However, there is almost no incentive for baseball teams to collect data on where foul balls land. Therefore, we are stuck with private apps like that discussed in the cited Time magazine article. Or through personal experience.
Human intuition is the natural, organic, experiential, and subjective portion of mental modeling. It's what humans have been using to make sense of things since the beginning of humanity. (Think of instinct as operating software that comes with the computer; intuition is the software library you download onto it through living.)
Is that why intuition is referred to as "second-nature?"
That's where OODA comes in.
In a nutshell, OODA is visualization for the mental processing cycle:
- Observation - the sensing of information;
- Orientation - the comparison, analysis, & processing of that information;
- Decision - the evaluation of options & simulation or prediction of outcomes;
- Action - the implementation or "doing" of the selected decision.
The Orient phase of OODA is all about the conditioning of the mind. The collection of life's experiences and exposures. The understandings of how the world works. The mental models
. The subconscious preferences & biases. The thinking frameworks you've learned. It's what you bring with you.
Orient is where we make sense of the world around us -- both at the macro level of our individual entire worldviews AND at the micro level the at-the-moment observation in front of our eyes.
But back to the mental models...
They are patterns or shortcuts etched into our minds, through repeated exposure (second-hand) or experience (first-hand). It's why I believed our section of seats at the baseball game was Foul Ball Territory.
But mental models are also created through the scientific method (AKA: experimentation; testing; learning). Or through data work (AKA: intelligence; analysis & synthesis). It's the use of objective information, clues, variables, and evidence to answer a question or hypothesis. It's why I confidently believe Section 110 at Citi Field to be the best place to catch a foul ball. The visualized data in the above infographic shows it to be true! (As long as I trust the sourcing and the methodology! And I have no reason not to...)
Data work allows us to remove pre-conceived conclusions. It's much more objective than experience. It pulls from a larger pool of incidents, situations, and occurrences than any single person can experience.
Data work is what ensures that we can shift, develop, or refine our mental models to be as accurate of representations of reality as possible. And when our orientations match reality, we can exploit those mental models into our favor. We make faster, more accurate decisions. We compress our OODA.
As I walked down the stadium aisle to our seats, I was not thinking of any datasets. I'd only found the above cited articles days later when seeing if such research existed. I was armed only with anecdotal experience. Mental models. My understanding of how a baseball game "works."
Early in the game, I explained to my sons why & how a young minor league catcher misplayed a catch-able foul ball -- with a nasty curved (but predictable!) trajectory caused by the wicked backspin on the ball. It's a lesson not learned through solid data, but through experience and a willingness to learn from feedback. And I wonder what impact that lesson about backspun foul balls might have on my sons when they're in the role of catcher. Did it stick? Who knows...
There was another lesson on trajectory when a foul ball (again, with wicked sideways spin) moved in a predictable, curved, and patterned route. The ball caused many fans to race to where they thought it was going. Which of course is not where it was actually going...
Many fans got out-OODA'd. They were operating with faulty mental models.
Last week, we sat in Foul Ball Territory.
Was it proven through data as the most likely section? No. But no data disproves it either.
Did an imperfect mental model get etched a bit deeper, and more permanantly through the "confirmation bias" of not only getting a foul ball myself, but through what seemed like a constant peppering of foul balls into our section? Quite possibly.
Now if you see Kahneman's System 1 and System 2
in this discussion, you're right! Try figuring out, in the moments after getting that prized ball, which of your kids to hand it to.
If you consider that answer BEFORE you actually get it, you've greased your OODA. And you've exploited a valuable lesson about pre-Orientation!
I wasn't so lucky to have considered beforehand which kid to give that ball to. Luckily, it wasn't the only ball we got that game...
Lou Hayes, Jr. is a detective supervisor in a suburban Chicago police department. He's focused on multi-jurisdictional crime patterns & intelligence, through organic working groups compromised of investigators & analysts from a variety of agencies. With a passion for training, he studies human performance, decision-making, creativity, emotional intelligence, & adaptability. In 2021, he went back to college (remotely!), in hopes to finally finish his undergrad degree from the University of Illinois - Gies College of Business. Follow Lou on LinkedIn, & also the LinkedIn page for The Illinois Model.
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