Resonance Gear Optimization: Sollant & Transmutation Data

Resonance Gear Optimization: Sollant & Transmutation Data

Table of Contents

• Overview
• Gear Progression Data
• Weapons Data
• Armors & Accessories Data
• Notes on Efficiency
• Fodder Materials
• Methodology
• Conclusion

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Overview

The document presents data-driven insights into gear optimization using Sollant, transmutation rewards, and fragments across three categories: general gear, weapons, and armors & accessories. It emphasizes a higher value when more is better for average points received through transmutation, while considering cost and resource expenditure.

Gear Progression Data

The following table lists tiered data (T1 through T5) for the general gear progression. Values are presented as provided with the original formatting preserved.

Weapons Data

Weapons: T1-T5

Armors & Accessories Data

Armors & Accessories: T1-T5

Notes on Efficiency and Sollant

The notes explain that higher ratios indicate greater efficiency, and they show relative comparisons between Blues, Purples, and Greens across gear slots, including a color-blind friendly note and the concept of full resonance progression across a gear set. Nonstandard characters appear for emphasis in a few lines such as the color codes and special symbols. The text also notes that materials like ore and leather could be added as fodder but their value is low, and this is explicitly mentioned in the original data.

Fodder Materials

You could technically add the materials (ore, leather, etc) you get as fodder too but their value is so low I did not mind

Methodology

• The analysis uses a custom formula: (Points Cost - Avg Points Reward) / Fragments Given, for the general discounting reward approach. - The alternative formula multiplies Item% * Points Given for all possible items, then multiplies by the Chance for Group Reward%.

Conclusion

This dataset provides a baseline for comparing gear progression efficiency via Sollant expenditure, transmutation rewards, and fragment generation. It highlights that higher reward ratios and efficient gearing paths reduce overall grind costs while maximizing total average points gained per cycle.