Rankings Market TCGs Articles

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I built inDex to answer one question: what is actually worth opening? These are the tests, tradeoffs, and weird problems behind the answer.

Research

Research
How Well Does Expected Value Describe a Pokémon Pack Opening?
What 22 million modeled pack outcomes taught us about typical openings, tail concentration, convergence, and the probability of recovering pack cost.
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Methodology

Methodology
How Chase Efficiency Measures the Economics of Chasing a Pokémon Card
How exact card value, modeled pull odds, and verified opening costs combine into one card-level comparison.
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Methodology
How the RIP Score Works
Why Expected Value was not enough, and how inDex compares the full opening experience.
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Methodology
How We Simulated One Million Pokémon Pack Openings
How one modeled pack becomes a distribution of normal outcomes, strong pulls, and jackpots.
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Methodology
How We Validated Our Pokémon Pack Simulation Using Expected Value
The mathematical cross-check that tells me whether the simulator is behaving as intended.
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Methodology
How Financial RIP Measures the Economics of Opening Pokémon Packs
Why wins, normal losses, realistic upside, and jackpots belong in the same financial picture.
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Methodology
How Collector Appeal Measures What Collectors Actually Want
How contextual Pokémon desirability and modeled access combine without turning Collector Appeal into a financial metric.
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Analysis & Guides

Analysis & Guides
Why Expected Value Alone Doesn't Tell You Which Pokémon Set Is Best to Open
Two packs can share the same average while feeling completely different to open.
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Articles | inDex