Balancing With Numbers
Flashcards on expected value, cost curves, and quick simulations for tuning game components.
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Questions Covered in This Set
10 cards to master
What is expected value (EV)?
The average result of a random outcome, weighted by probability: EV = Σ (probability × payoff).
Compute the EV of "Roll a d6. On 5–6 deal 6 damage, otherwise deal 1."
(2/6 × 6) + (4/6 × 1) = 2 + 0.667 ≈ 2.67 damage.
Why can a high-variance card be worth slightly less EV than a flat card?
Players pay for excitement and for swing potential when losing; variance has value of its own, so it can be priced in.
Who prefers low variance, the player ahead or behind?
The player who is ahead wants low variance; the player behind wants high variance — so variance is a strategic axis, not just a balance knob.
How do you find the EV of a conditional effect like "If you control a Forest, gain 4 gold"?
Multiply the payoff by the real trigger rate observed in playtests (e.g., 60% × 4 = 2.4 gold).
What common mistake do designers make about condition trigger rates?
Assuming a condition fires ~80% of the time when the true rate is much lower (e.g., 35%), which quietly makes a card dead.
What is a cost curve?
A pricing formula fitted to your own game that converts effects into a reference unit, giving every card a sanity-check price.
What does it mean for a card to be "above curve"?
It gives more value than its cost implies (e.g., cost 4 for 3 VP prices at 6.0) — strictly efficient and likely an auto-include.
Name the two refinements to a cost curve mentioned in the lesson.
Non-linearity (diminishing returns or combo thresholds, e.g., value = n^0.9) and tempo discounting (10–20% less value per turn of delay).
What can a "math skeleton" simulation tell you?
Comparative stats like average turns, min/max, and spread — e.g., 2d6 vs a movement deck both have EV 7 but different spread, which is what players feel as luck.