Introduction to Common Battle Formulas and Testing Approaches in Game Development
This article introduces typical subtraction, multiplication, and division damage formulas, explains their design principles, demonstrates practical examples from games such as Arknights and Dota 2, and outlines testing methods, effective metrics, and additional concepts like stacking, round‑table theory, and second‑roll analysis for balanced combat systems.
The article provides a concise overview of frequently used battle formulas and testing strategies, aiming to help readers grasp the underlying design ideas and apply them in their own work.
Subtraction Formula : Damage = Attack - Defense . It is simple, low‑cost to understand, and suitable for games where precise attribute tuning is required, such as Arknights, Fire Emblem, or Hearthstone.
Multiplication Formula : Damage = Attack * (1 - DamageReduction) . This adds a damage‑reduction factor and can be extended with additional parameters for more complex calculations.
Division Formula : Damage = Attack / (Attack + Defense) . It emphasizes the importance of the attack attribute and typically avoids zero‑damage outcomes.
The article then discusses the characteristics of each formula type, noting that subtraction formulas have low comprehension cost but demand strict value placement, while multiplication/division formulas allow finer balance adjustments at the expense of higher complexity.
Practical examples are given: for Arknights, the damage of the character "能天使" is calculated step‑by‑step using the subtraction formula, showing how buffs and talent bonuses affect final damage; for Dota 2, armor‑based damage reduction is examined with both old and new formulas, illustrating how changes impact survivability curves.
Beyond formulas, the article introduces testing concepts such as effective round ( EROUND = EHP / EDPS ), effective HP, and effective DPS, providing derivations for HP, DEF, and CRD attributes and showing how to evaluate their contribution to combat performance.
Additional topics include stacking methods (linear vs. non‑linear), the "round‑table" theory for probability allocation, and the "second‑roll" theory that separates primary outcomes (miss, block, etc.) from secondary outcomes (critical hit, direct hit).
The piece concludes with a summary of key takeaways: understand design intent, align testing with game mechanics, monitor attribute growth and value, use visualizations, and continuously playtest to ensure balanced combat.
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