I’m sure many of you have heard of Moneyball, Michael Lewis’ 2003 best-seller that was recently the basis of a Major Motion Picture. The book details the selection process of professional baseball prospects, and how the traditional methods of scouting have given way to an increasingly mathematical analysis of player performance known in the baseball world as Sabermetrics.
Historically, baseball scouts focused primarily on physical stature to predict future success. Scouts used physical prowess as an indicator of any of “5-tools”: the ability to run, hit (average), hit for power, throw and field. They assumed that if a player looked like a superstar athlete, then, even if he wasn’t, they could eventually mold him into one.
There is clearly logic in their methodology. An athletic body is usually a signal to athletic ability, and athletic ability (speed, power, agility, etc…) factor into the performance of any player in any sport. But one of the fascinating things about the game of baseball, is how consistent execution, not athletisicm, is the primary determinant of success.
The consistent nature of baseball lends itself to the world of statistics. The regular season alone accounts for 162 games, where players get a handful of defensive attempts and at-bats each game. Each at-bat is a microcosm of statistical analysis, where every pitch has different speed and break, each ball struck travels a discrete distance, to a specific location, and with its own unique circumstance (number of runners on base, the time of day, wind, temperature, etc…).
As management in charge of professional baseball teams turned away from traditional scouting and analysts poured over the statistics, they discovered that they could predict with legitimate certainty the outcome of many of the small events that take place in every game. With statistics, they knew not only a player’s batting average, but their batting average against curveballs, thrown by left-handed pitchers, at night, when the temperature is below 60F degrees.
It follows that eventually the General Managers and Scouting departments of Major League Baseball organizations – those tasked with predicting success – migrated their assessment tools from their gut to their computers, notably, statistical software packages.
The fascinating corralary to all of this, is that to make statistically significant judgements on historical data, one must have a large enough pool of data. Statistical assessments based on tens of data points are less accurate than thousands, and thousands of data points are less accurate than millions. This is known in probability theory as the law of large numbers.
Naturally, the longer a player has played, the more accurately we are able to predict success. Many sabermatricians argue that a college baseball player’s chance of success is greater than that of a high-school player. I can’t refute that claim, but I do know that College baseball players have a wealth of statistical data to allow Major League Baseball scouts to better assess their expected performance in the big leagues. So, even if the average College player won’t necessarily perform better in the major leauges, there is less risk in investing in College players because your predictive model of success for College players would be more accurate given more information (less variance, R squared -> 1).
A16Z == B7S
Let’s pretend that analyzing baseball prospects is similar to investors analyzing startups. In this game, VCs are tasked with discovering and assessing entrepreneurs (clearly, VC Partners are the General Managers, and associates are the scouts). If sabermetrics has shifted baseball prospect selection towards experienced, collegiate players, where do technology investors stand on young vs. old founders, and where should they stand?
When it comes to young founders, my immediate assumption is that technology investors are an awful lot like traditional baseball scouts; they’re interested in raw talent. Which is fair, because its tough not to be “raw” when you’re really young. But what are the Tech Investor’s “Five Tools”?
- Programming ability
- Ability to stick with one problem (focus, perseverence)
- Salesmanship ability (writing, communication skills)
- Successful Hacks
I have to admit, I don’t really have an answer. Since Baseball has discrete performance boundaries, it’s easy to compare how hard 2 players throw, and then say which throws harder. With startups, it’s more difficult to relate young founders because the comparative variables aren’t as objective as the performance metrics on the ballfield.
My instinct tells me that investing in young entrepreneurs is extremely risky business. However, I can see a few important attributes common to many young founders:
- Infinite energy & conviction
- Ability to generate unlimited Press Coverage
- Life flexibility (business-first: single, no kids, move easily)
- Unpolluted theory of mind (no previous assumptions, no limits, think big / delusional)
These things are great if you can exploit them and sell out fast. The problems come when building a business. Most successful businesses require longevity, and through this weight of time most founders will eventually succumb to the human condition. Unless they are a ruthless, autistic cyborg, they will likely at some point in time:
- Fall in love
- Have children
- Gain perspective (become less delusional)
Oh boy. I love the energy in young founders. But then I look at this list again. Think back to the first time you fell in love. Not to say that old love is less significant, but, old love tends to have perspective and won’t throw away a business because its girlfriend is moving to Florence to study Art History.
And as the old playground song goes: after love, and maybe marriage, come babies and expensive baby carriages.
My perspective here isn’t completely valid, as I don’t have kids– but if I spend even 1/10th of the time my parents spent raising me, it might have some serious implications on the amount of time I can commit to my business.
Most older entrepreneurs have been in love. They know how to temper their emotion. Maybe they’re divorced, maybe they’ve had 3 kids. Life isn’t full of surprises. Maybe that’s boring, but it’s predictible, and predictability is as core to investing as it is selecting baseball prospects.
Young founders would seem to be a better fit for early stage companies, where their infinite energy and delusional conviction can help shape a company’s culture and push it into a valuable growth phase. Once the company has hit product market fit, it’s suitable to bring on older talent who can optimize the shit out of the company until there’s a suitable exit available.
Then, after an IPO; after scraping any remaining residue of youth and innovation from the whiteboards; after the hackathons are full of only posers and all the real talent has fled to the next revolution; the products stagnate, the culture rots, the bears on wall street rip every remaining piece of flesh from your withering bones, and all that’s left is your huge office campus across town that you’re now forced to sublease to some 19-yr old Harvard prodigy and who’s going to tear down your office wall and put a 10,000 gallon aquarium in your private bathroom.
I just hope you’ve cashed out by then.