2026 Topps Chrome UFC

Main table columns

Listed price

The dollar price on the Throne break CSV for that named fighter spot — exactly what the breaker is charging before fees or discounts.

Fair proxy

A peer split of the named-spot dollar pool: we sum every named fighter price from the same sheet, then allocate that total in proportion to each fighter's checklist strength score.

fair_proxy = (sum of named spot prices) × (this spot's strength) ÷ (sum of every named spot's strength)

Think of it as "if strength were the only allocator, this spot would deserve this share of the named pool." It is not a secondary-market comp.

Proxy gap

Compares the fair proxy to the listed price. Shown as a percent after rounding in export.

proxy_gap = (fair_proxy − listed_price) ÷ listed_price

Positive proxy gap means the proxy sits above the listed price — the model estimates more modeled exposure per dollar than the average split implies. Negative proxy gap means the spot appears pricey against the model. Value bands (Strong, Fair, Pricey) are driven from these proxy gap thresholds.

Auto index

Expected dual-case autograph mass for this fighter after checklist odds work: reciprocal subset weights, dual-subject splits, and published dual-case auto seat counts. Higher means more modeled share of autograph programs across both cases together. It is a relative index, not a calibrated pull probability (parallel serial odds are still coarse).

Signal

In the table this column is the price-trend residual. We fit a simple line across all named spots: checklist strength vs listed price. Each fighter's residual is how far above or below that line they land.

signal = actual_strength_score − strength_predicted_from_price_trend

Higher means "more checklist juice than fighters who usually cost about this much." The default sort (Model signal) uses this so expensive favorites do not drown out structural bargains.

Band

Quick bucket from proxy gap alone (for example Strong when proxy gap ≥ about +45%, Fair near +15%, Pricey past about −40%). Use it as a traffic light, then read price, proxy, and driver.

Driver

Short explanation of what moved the score — autograph share vs insert footprint vs tier vs price gap — generated from thresholds on auto index, insert index, and tier.

Sort menu (same screen)

Proxy gap

Sorts by proxy gap percent (fair proxy vs listed).

Strength per dollar

Checklist strength score divided by listed price — value spots with big modeled footprints float up.

Overall strength

Raw checklist composite (risk_mass_score in the analyzer) before the price-trend residual.

Lowest price

Sheet price ascending.

Auto index

Sort purely by modeled autograph mass.

Tier & archetype

Tier (A / B / C) reflects champion / hype assumptions maintained in the workbook — not a live odds feed. Archetype labels (Champion hit profile, Insert volume, etc.) come from rule bands on tier, price, auto index, and insert depth.

2026 Topps Chrome UFC

Detail panel (selected spot)

Fair proxy / Proxy gap

Same calculations as the table columns, repeated for the fighter you clicked.

Strength per $

Overall checklist strength divided by listed price.

Insert index

Expected dual-case insert-row mass — the insert analogue of auto index using published insert seat totals and program weights.

2026 Topps Chrome UFC

Letter pools sidebar

Random-letter and multi-fighter pool spots use a blend score so one mega fighter cannot hide a thin pool.

Listed pool price

Breaker price for that pool line from the sheet.

Signal (pool)

Combines the best fighter in the pool with average depth:

pool_signal = max(fighter_scores) + 0.35 × average(fighter_scores)

Only fighters that matched the checklist contribute to max/avg; see matched counts below each row in the UI.

Signal per $

pool_signal ÷ pool_price — bang-for-buck on the blended score.

2026 Topps Chrome UFC

Human review queue

Fighters flagged because the model sees enough checklist footprint to deserve a human pass on tier or intel, even when automation kept a conservative default. The score shown is sheet-only checklist strength before hype overlays.

Value bands — UFC

Bands come from value signal (fair proxy / listed price). Four canonical bands describe where a spot sits relative to the model's fair proxy estimate.

• Strong — value signal ≥ 1.2. Fair proxy well above listed price. Worth deeper review.
• Fair — value signal 0.8–1.2. Price and fair proxy roughly agree.
• Pricey — value signal > 0 but < 0.8. Listed price above fair proxy; appears pricey.
• Review — no value signal or insufficient model coverage. Needs manual review.

2026 Bowman Baseball beta

Bowman team table

Bowman ranks teams per selected retail/format using parsed checklist sections and official Topps pack odds — still no break PYT prices until you upload them.

Format score

For each team we count checklist rows in weighted sections (base, paper/chrome prospects, autograph programs, etc.). Each section score is multiplied by a format factor derived from published odds for that format (hobby, jumbo, breaker delight, mega, value). Higher means more modeled participation in programs this format actually delivers.

Base score

Same section counts with full static weights — exposure before suppressing programs that are absent or extremely rare in the selected format.

Format index

This team's format score divided by the top format score among all teams for that format. 1.00 means league-leading modeled exposure before prices.

Uploaded PYT price / Value index

After you load a two-column CSV (team,price), we attach prices where names match.

value_index = format_score ÷ uploaded_spot_price

Bands like "Highest exposure" vs "Needs price" flip to price-aware modes once numbers load.

Prospect / Rookie / Retail autos

Counts of autograph checklist lines attributed to that team in the probe parser — not hit probabilities.

Bowman sort options

Value index

Requires uploaded prices; ranks exposure per dollar paid.

Format score / Format index / Base exposure

Raw modeled footprint variants without needing PYT.

Chrome prospect autos / Retail autos

Sort by parsed auto-program counts.

Value bands — Bowman

Before prices upload, bands are based on how close each team's format score is to the leader in that format (ratio cutoffs). After prices upload, bands incorporate value index thresholds instead.