Episode 11 House of CardLadder Ft. Chris McGill

Released: July 22, 2025 | Duration: 50:22

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About This Episode

Chris McGill built CardLadder during his final semester of law school, working nights on a data product for a hobby that had no research infrastructure. The soft launch date, June 23, 2020 (6/23 for LeBron James and Michael Jordan), was not an accident. The product grew from a $10 Jordan auction spreadsheet he sold to a few hundred House of Jordans podcast listeners as a proof of concept that collectors would pay for organized data.

This episode covers CardLadder sports card data from the inside: what the research team actually does every night to keep the indexes clean, where the Ladder Score came from and why it largely disappeared from view, how population growth creates a structural headwind for almost every card in almost every index, and a feature called Showcase that most users have never opened.

Chris is a data native who approaches card markets the same way he approached music production, looking for the patterns underneath the surface noise. The conversation is one of the most technically dense in the Slabnomics catalog, and also one of the most useful for anyone who uses CardLadder regularly without fully understanding what they are looking at.

Topics Covered

  • Chris McGill’s background: northern Illinois to Atlanta pursuing music production (2004-2010), back to school for a four-year degree, then law school at UCLA in Westwood, CardLadder started during final semester; never formally practiced law
  • House of Jordans podcast: launched December 2018 with Christina and cousin Brian, recording from a music studio in Westwood, one episode per month at three to four hours per episode with ten-page script outlines; ended June 2020 when CardLadder consumed all available time
  • CardLadder origin: notebooks of Jordan auction data brought to Cardboard Chronicles YouTube (Josh Sherrill); proof of concept as a $10/month Jordan spreadsheet distributed to House of Jordans listeners; Josh Sherrill’s unique skill stack made the product possible; soft launch June 23, 2020
  • Why CardLadder is called CardLadder: Josh named it; the ladder metaphor captures both a ranked database of cards and the idea of a collector laddering up using data as the tool
  • The Ladder Score: Chris’s original all-in-one metric combining price change, transaction volume, velocity, and market cap into a single number analogous to WAR in baseball; still accessible but not widely discussed; collectors preferred raw data over abstracted metrics
  • Research team structure: Chris reviews 30,000-40,000 cards nightly from approximately 10 PM to 2 AM every day including holidays; Christina, Joel, and Kyle (formerly at PSA) handle additional subsets; four people nightly ensuring clean inputs for all indexes
  • Collectors Universe acquisition: announced/finalized November 2021 during the peak of the COVID bull market
  • The 100 million sales database: auction and fixed-price results going back to the early 2000s from approximately a dozen marketplaces; eBay fixed-price results only from 2020-2021 onward
  • Index architecture: category-wide indexes contain thousands of cards; basketball index has 16,500 cards; player and character indexes exist for any player with enough cards; the CL50 as the curated 50-card market snapshot
  • Population growth and the structural price headwind: every new player index tends to start high and trend down as grading activity increases supply; population curves visible in CardLadder; market cap can increase even as per-card prices fall
  • Survivor bias problem in category indexes: unlike stock market indexes where bankrupt companies are removed, cards that go to near zero remain in the database and pull indexes downward; no natural clearing mechanism
  • Showcase feature (underused): collection feature defaults to private; can be made publicly visible; 9,377 Michael Jordan cards visible; no prices allowed but social media links can be enabled; useful for discovery and deal-making
  • Custom indexes: available to users to build privately; not publicly accessible

Full Transcript Summary

How CardLadder Started: A Spreadsheet and a Podcast

Before there was CardLadder, there was a ten-dollar spreadsheet. Chris McGill was in his final semester of law school at UCLA in Westwood, running the House of Jordans podcast out of his music studio, and manually compiling Michael Jordan auction results into a structured data file every month. He offered it to his podcast audience for a small fee. A few hundred people paid.

That was the proof of concept. Collectors would pay for organized, accurate, accessible data. The spreadsheet was primitive. The insight behind it was not.

Josh Sherrill had been watching from the Cardboard Chronicles YouTube channel, where Chris had appeared with notebook pages of Jordan market data. The two had developed a friendship, and the conversation kept returning to the same question: was there a way to make this data product more scalable, more useful, more than a spreadsheet emailed to podcast listeners?

The answer required Josh specifically. Chris is clear that the founding worked because of a talent stack that is genuinely rare: Josh had collector knowledge, software development capability, managerial ability, and the judgment to identify and hire good front-end designers. Without that combination of skills in one person, CardLadder does not exist. The soft launch date of June 23, 2020 (6/23, for LeBron James and Michael Jordan) was not planned. It was the product of pandemic lockdowns, a final semester that converted to pass/fail, accumulated boredom, and the coincidental timing of the sports card bull market beginning to accelerate.

What the Research Team Does Every Night

Most CardLadder users open the app, check their indexes, run a price search, and leave. What they do not see is what made those numbers trustworthy.

Chris reviews incoming sales for approximately 30,000 to 40,000 cards every night, starting around 10 PM central and running until roughly 2 AM. Every day, no holidays. The purpose is quality control: ensuring that the sales feeding the indexes are legitimate, accurately categorized, and representative of actual market activity rather than outlier transactions, shill bids, or listing errors.

He is not alone. Christina has her own subset of cards she reviews nightly. Joel and Kyle, who came over from PSA following the Collectors Universe acquisition in late 2021, handle TCG primarily with sports crossover. Four people, every night, holding back what Chris describes as the flood of bad data that would corrupt everything downstream if left unchecked.

The consequence of this work is that the 100 million-plus sales in the CardLadder database going back to the early 2000s are not a raw dump from eBay. They are a curated dataset, vetted by people who know what normal looks like and can identify what does not belong. That distinction is not trivial. Garbage in, garbage out is the most important rule in any data product, and it is expensive to prevent.

The Ladder Score: The Metric Nobody Uses

When Chris originally conceived of CardLadder, the organizing principle was not a price history page. It was something he called the Ladder Score.

The idea was an all-in-one metric analogous to WAR in baseball or QBR in football: a single number that combined price change in both absolute and percentage terms, transaction volume, transaction velocity, and market cap into a unified signal. A card with a high Ladder Score was outperforming. A card with a declining score was softening.

The problem was that collectors did not want abstraction. They wanted data. When someone sat down to research a card, they wanted to see what it sold for last week, not a composite number derived from several variables they could not independently inspect. The market feedback steered CardLadder decisively toward raw data, price history, population tracking, and clean indexes rather than synthetic metrics.

The Ladder Score still exists in the product. It is not prominent. Chris is candid that it was his idea, it was a genuine attempt to create something useful, and the market mostly passed on it. The lesson: the thing that sparks a product is rarely the thing the product ultimately becomes.

Population Growth and the Structural Price Headwind

This is the most important framework in the entire conversation for anyone thinking seriously about card investing.

When a new player enters the market, their PSA 10s are scarce. Population of ten, then fifty, then a hundred. Early buyers pay high prices for low supply. The player is good, the narrative is building, and the market is willing to pay.

Then the population reaches five hundred. Then two thousand. Then twenty-five thousand for Wemby’s base Prizm, less than two years after the card came out. Each increase in population creates downward pressure on price because supply and demand are not complicated. The price has to clear a larger number of cards against whatever buyer demand exists.

This dynamic is visible in CardLadder’s population curve feature, which shows how a given card’s graded population has grown over time and can be mapped against price changes. What looks like a declining player narrative is often just a declining scarcity premium being corrected by grading activity.

The nuance is market cap. A card that was worth $500 at a population of ten is a $5,000 total market. A card worth $50 at a population of two thousand is a $100,000 total market. Price per card goes down. Total market size goes up. Both things can be true simultaneously.

The category-wide indexes carry this structural problem at scale. The basketball index has 16,500 cards. Unlike a stock index, where a company that goes to zero is removed from the index, a card that goes to nearly zero remains in the database. Cards that peaked at a few dollars and are now worth a cent are still counted, still pulling the category index downward. There is no survivor bias filter. The long-run trajectory of most category indexes, absent a bull market, is structural decline driven by population growth and the attrition of cards that never found durable demand.

The Showcase Feature Nobody Talks About

CardLadder’s collection feature defaults to private. Most users treat it that way forever.

There is a setting that makes a collection, or parts of it, publicly visible in the Showcase section of the site. Several hundred thousand cards from user collections are currently visible in Showcase. Searching Michael Jordan returns over 9,000 results. There are no prices, no marketplace functionality, and no obligation to sell anything. It is purely a visibility and discovery layer.

Chris uses it regularly. He has made deals from cards he discovered in other users’ public collections. He has had collectors reach out about cards they found in his Showcase and opened negotiations that would not have happened otherwise. He also uses it as a low-friction way to share his collection without the commitment of an Instagram post, which he treats as a more deliberate, captioned event.

The feature does not get discussed in the hobby. Most users do not know it exists. For collectors trying to find specific cards that rarely surface publicly, or trying to make their own collection discoverable to potential trade partners, it is one of the more practically useful tools in the CardLadder product.

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