How the RIP Score Works

Expected Value—the long-run mean of a probability distribution as defined by OpenStax—was the first thing I calculated because it is the obvious way to measure a pack financially. It was also the first thing that showed me why EV was not going to be enough.

Two sets can land on nearly the same EV and still feel completely different to open. One can spread value across cards you actually hit. Another can hide most of its average in one huge chase.

I would not call those the same opening, so inDex cannot treat them as equivalent.

RIP Score

The current canonical score is Overall RIP V12. It synthesizes three peer pillars without treating their equal visual presentation as equal weighting: Financial RIP V4 asks, “How good are the money outcomes when you open this product?” Chase Accessibility asks, “How reachable are this set's most important collectible values from a pack?” Collector Appeal describes how compelling the collectible roster is and supplies desirable-outcome context. Exact model weights and transform constants are not published.

RIP Score is shown from 0 to 10. A displayed 5.0 is the current Pokémon benchmark. Above 5 means above that benchmark; below 5 means below it. A displayed 9.2 does not mean a 92% chance of profit or 92% value retention.

Rank answers which supported option is best. Score answers how strong the option is relative to the benchmark. A 10.0 is the upper endpoint of the presentation scale, not automatically the current leader; the leader is identified by rank #1.

Financial RIP

Financial RIP reads the simulated pack values and the cost used for the run. It does not consume Collector Appeal or Pokémon popularity.

True Win Frequency

How often modeled value reaches or exceeds pack cost.

Typical Retention

How much of pack cost the median opening retains.

Loss Resilience

How deep and how frequent losing outcomes are.

Strong Upside Quality

The P95 threshold relative to cost defines the current V4 scoring signal. The P95–P99 conditional mean remains descriptive context, not a V4 score input.

Jackpot Upside

The P99 threshold and top 1%, controlled so a giant chase cannot dominate.

Base Economic Efficiency

Average return relative to cost after excluding the top 1%.

The exact weights, anchors, caps, and tuning constants are protected. The dimensions and their behavior are public because a reader should be able to understand what the model rewards and criticize that choice without receiving a cloneable recipe.

Collector Appeal

Collector Appeal V5 uses a contextual Pokémon desirability baseline and a Desirable Outcome Frequency adjustment. Market price, Expected Value, profitability, pack cost, and Financial RIP are not directly added to its score arithmetic. However, same-run card EV contribution provides contextual evidence for which Pokémon meaningfully represent the set’s chase roster. EV establishes relevance; it is not multiplied into Pokémon desirability or treated as a financial score.

Dual-Path Depth remains visible as a diagnostic, but it is not a Collector Appeal V5 score input.

This is narrower than “what people like.” It currently models Pokémon subjects, not trainers, artists, or personal favorites. Missing coverage makes the result unavailable instead of forcing an absent signal to zero.

Chase Accessibility

Raw Accessibility is the underlying modeled collectible-value accessibility measurement. The public Chase Accessibility score is a comparative presentation of that measurement across the eligible set cohort, and the set rank is a separate comparison again. A displayed 6.4 / 10 therefore does not mean a 64% pull probability.

The metric considers modeled pack probabilities and concentrates value significance toward the set's more important collectible values instead of choosing one arbitrary top card. Read the separate Chase Accessibility methodology for its boundaries and diagnostics.

The simulation underneath it

Supported sets run through one million modeled openings using repeated random sampling in the general Monte Carlo tradition described by Metropolis and Ulam. The project-specific pack states, card pools, pull assumptions, and current calculation values produce the distribution that supplies P50, P95, P99, break-even behavior, loss behavior, and the Financial RIP inputs.

A million trials reduce sampling noise. They do not validate the real-world assumptions by themselves. If a pull-rate model is wrong, more trials make the wrong model look steadier. That is why inDex describes these as modeled pull rates, tests the pack-state logic separately, and leaves unsupported sets unranked.

What the score leaves out

Displayed card value is not guaranteed cash in hand. Liquidity, seller fees, taxes, shipping, grading, and regional price differences can all separate modeled value from realized proceeds. Markets and pack costs also move, so each result belongs to a calculation snapshot rather than being a permanent property of the set.

RIP Score is useful for one job: ordering the supported choices in front of you using a consistent opening model. It is not financial advice, a forecast, or a prediction of your next pack.

References

RIP Score and its synthesis of Financial RIP, Chase Accessibility, and Collector Appeal are original inDex methodology. These references support the standard Expected Value, probability-distribution, and Monte Carlo concepts underneath the analysis; they do not externally validate the RIP score or disclose its protected construction.

1. OpenStax. Introductory Statistics 2e. Chapter 4: Key Terms. Supports the Expected Value and probability-distribution definitions used in the opening analysis.
2. Metropolis, N. & Ulam, S. (1949). “The Monte Carlo Method.” Journal of the American Statistical Association, 44(247), 335–341. Supports the general repeated-random-sampling method used to form modeled outcome distributions.