How Pokemon and the Iran War Nerdsniped Me Into Quantifying Strategy
I have been playing the TCG in Pokemon (PTCG) for some time now and found it a pretty refreshing, albeit simpler card game to play because of the tools you have to reduce randomness. Randomness in card games is often surfaced as "bricking your hand", where a bad draw could mean that there is nothing you can do to stop your opponent from building an advantage or just outright winning the game. My curiosity of exploring the "brick-iness" of a deck led me to build a Monte-Carlo simulation of drawing cards until you have reached a "perfect" or "pseudo-perfect" board state.
All was well until a deck I was happy with (less than 20% chance of bricking my hand) lost me 4 straight rounds in a local friendly tournament. I was shocked. My hands "bricked" but not in the sense that I did not draw the cards I needed, but that the opponent always seemed to have the tools to destroy my board state. I tweaked my simulation and tried my hand at online play but the probabilities still were far too removed from what I expected from the simulation.
When the Iran War started, Professor Jiang went trending on X, and his video, "Why Schools Suck" re-introduced game theory to me as more than some abstract mathematical tool. I tried to apply game theory to PTCG, but it does not apply well when you have a multi-turn dynamic game with asymmetric information and near-infinite option space (pokemon decks, especially when played offline due to the availability of cards, have a lot of variety in deck building). This is also where standard game theory (Nash Equilibrium, minimax, etc.) breaks down, because it assumes that players are rational, can enumerate through strategies, and reason over them.
The game also has a time component that evolves turn by turn, whereas game theory traditionally takes a snapshot. So I tried cybernetics instead, treating it as a problem of feedback control. That wasn't quite right either, but it led me to a realization: shorting a stock is the same kind of game. Short too early or show your hand too soon and you prompt a short squeeze that ends with a margin call that kills your fund.
So the real question I was trying to answer is "Will my strategy survive long enough to work?" The answer is not a matter of how risky (which is based on historical data) or how strong (based on perceived advantage) a strategy is, but something deeper: how well the strategy of the deck coupled with the state of the game at each turn. A great deck with a terrible draw is useless but a meme deck that perfectly matches the board state can dominate.
As it turns out, this question is the same question whether you're holding Pokemon cards, stock positions, a startup runway, or a marriage. The math doesn't care about the domain. It cares about the coupling between what you're doing and where you stand, and whether your buffer will last until your strategy pays off.
There's a Chinese word for this: 势 (shì). It's been a core concept in strategy for 2,500 years, Sun Tzu used it, every Chinese strategist since has used it, but nobody had formalized it into math. Existing frameworks either require full information of all available strategies or aren't forward-looking. 势 was always just a feeling, a "vibe".
I've decided to fix that through Strategic Momentum Mechanics (势学) to turn 势 into a computable framework. Interestingly, my wife also pointed out that in Chinese, 势 also has the property of "造势" (to build up momentum) and "借势" (to borrow existing momentum), which fits nicely into explaining the idea, so we wrote a short book around it. It has two parts:
Part One: 势之道 (The Way of Strategic Momentum) builds the theory from first principles, culminating in the three laws of strategic momentum and a danger metric that leads conventional warning signs by three to five periods. All the math is in skippable boxes so you can read the prose and get the intuition without touching an equation.
Part Two: 势之术 (The Art of Strategic Momentum) puts the framework to work across life domains. Career decisions. Economic boom-bust cycles. Marriage as a strategic contract. Teaching your kids. There is even a chapter on distinguishing created momentum from borrowed momentum.
The core insight is deceptively simple: "you can be right on average and dead in practice." Being correct about your strategy doesn't help if your state deteriorates before the strategy pays off.
It's a living manuscript and we're still refining, still extending the framework (there are open questions at the frontier that connect to category theory and complexity science, if that's your thing). Feedback is genuinely welcome.
It's available now on Leanpub: