Baseball has a massive hardware dependency issue, and that hardware is the human body. As anyone who has watched the New York Mets over the last few decades knows, relying on physical, carbon-based lifeforms to execute repetitive ballistic tasks is an incredibly inefficient way to generate enterprise value.
I was discussing this over lattes in Palo Alto last week with some of the smartest people I know, and the consensus was clear: the Mets are fundamentally a data problem masquerading as a sports franchise. The front office is simply too attached to a legacy deployment model—namely, putting nine guys in a field and hoping for a favorable variance.
That is when I pivoted my attention to Out of the Park Baseball (OOTP) on Steam. For the uninitiated, OOTP is not a "video game" like MLB The Show, which relies on deprecated mechanics like hand-eye coordination and rendered 3D graphics. OOTP is a pure, unadulterated database GUI. It is a backend management console for a theoretical baseball universe.
According to my Steam dashboard, I have logged 2,300 hours in this environment. In startup terms, that is roughly three pivot cycles. And what I have discovered, building the Mets from first principles, is that the sport is actually deeply beautiful once you abstract away the sweaty guys in the dugout spitting sunflower seeds onto the floor.
In my simulation, I didn't try to "coach" the team. Coaching is a bloated, unscalable paradigm. Instead, I treated the roster like a cloud computing infrastructure. When a relief pitcher's ERA spiked above a tolerable latency threshold, I didn't give him a pep talk; I terminated his instance and spun up a cheaper, high-velocity arm from the Triple-A server farm in Syracuse.
Take Pete Alonso, for instance. A fan favorite in the real world, sure. But in my OOTP environment, I recognized early on that his power-hitting profile was basically an on-premise server racking up exorbitant maintenance costs. I didn't wait for his contract year to negotiate; I bundled him in a multi-team trade algorithm that returned three mathematically flawless minor leaguers with a combined cost profile of a Zoom Pro subscription. Did the virtual fans riot? The system logged a 14% drop in "fan interest," which I quickly patched by lowering beer prices by 30 cents—a classic user acquisition subsidy.
Contrast this with real-world owner Steve Cohen. He's a brilliant guy, obviously—you don't amass billions in hedge funds without understanding arbitrage—but he's let the meatspace constraints of New York media dictate his product roadmap. He's trying to buy premium, fully realized assets. That's like buying Oracle licenses in 2024. You don't buy the superstar; you build a pipeline of open-source talent that can be ruthlessly iterated upon.
If you look at the Mets' current roadmap, it's completely bottlenecked by an emotional attachment to human beings with connective tissue.
I actually synthesized my 2,300 hours of gameplay data into a 40-slide pitch deck and posted it in a Hacker News thread. The engagement was off the charts. My core thesis was simple: the MLB needs to stop playing the physical games. If both teams simply upload their OOTP scout ratings to a centralized blockchain before the first pitch, we could resolve the entire 162-game season asynchronously in the time it takes my barista to pull an espresso shot.
The physical stadium in Queens could then be repurposed into a high-density co-working space or a massive crypto-mining facility, generating continuous revenue regardless of whether the bullpen blows a save in the 8th inning.
I haven't heard back from the Mets organization yet, which isn't surprising. Incumbents are always the last to realize their core product has been disrupted. Detractors will argue that baseball is a romantic game, a pastime meant to be enjoyed on a sunny afternoon with a hot dog. But as I boot up Steam to simulate my 47th consecutive season of frictionless, mathematically guaranteed dominance, I know I'm already living in the future.