I. Introduction
The “Card Ladder Value” looks to produce an estimated value on every card in our database
using player indexes and comparing the last sold value to the movement of that player’s index.
The confidence decreases the older the last sold date becomes.
Collectors often think about the value of a given card as it relates to the other grades of that same
card. When a BGS 9.5 of a card sells then collectors typically do math in their heads on the value
of their PSA 10 as a multiple. It’s a natural thought process to attempt to describe the value of a
card. We have seen examples where the lower grade of a card is estimated higher than the higher
grade because of the confidence of the “Card Ladder Value” given the old sale dates.
Card Ladder would like to introduce a new value using this thought process for collectors called
“Grade Ratio Value”. This will not replace the “Card Ladder Value” but will add another data
point for consideration and often helps supplement when the confidence is low due to the last
sold date being far in the past.
II. Methodology
(A) Eligibility
Card Ladder would like to introduce a new value using this thought process for collectors called
“Grade Ratio Value”. This will not replace the “Card Ladder Value” but will add another data
point for consideration and often helps supplement when the confidence is low due to the last
sold date being far in the past.
(B) Comparison Grades
In order to calculate the value we must first look to different grades of the same card as tracked
by the Card Ladder vetted database. Once we determine that a card has not sold in more than a
year, next we look to other grades of that card. In order to find the ratio between the two grades
two things must occur for us to calculate an accurate value.
First, the comparison graded card must have sold within the last 6 months. We need confidence
that there is a recent vetted sale in order to determine the value of our card today.
Second, the comparison graded card must have a sale in the past that occurred within 6 months
of a sale of our card for which we seek the value. Here’s an example of the data we look to find
for eligibility with the PSA 10 being the card we hope to determine the “Grade Ratio Value”. The
current date in this example is May, 2022.
PSA 10 Copy of Card:
BGS 9.5 Copy of Card:
In this example above we can see that in the past the PSA 10 sold for 2x the BGS 9.5 and the
BGS 9.5 has a sale in the last 6 months and the PSA 10 hasn't sold in more than a year.. This
example will allow us to provide a “Grade Value Ratio”
(C) Calculation
- Example: Using our figures above the Sold Price of the PSA 10 card divided by the sold
price of the BGS 9.5 card gives us a ratio of 2.0. This ratio is then multiplied by the last
sold price of the BGS 9.5 of $2000 giving us a “Grade Ratio Value” of $4000.
III. Selection of Comparison Grade
(A) Multiple Comparison Grades
Using this methodology we will have situations where we have different ratios across multiple
grades. For the example above there might also be an eligible comparison to the BGS 9 copy.
(B) Solution: Select the Highest Grade
For this situation we simply select the highest grade of all eligible grade comparison cards. The
reason we did this was because the higher grades have less volatility over time and generally are
more liquid cards. Once you get down to 7’s and lower they start to blend together and skew the
ratios. The PSA 10 to BGS 9.5 ratio has a more consistent long term comparison that is
predictable, for example.
IV. Final Thoughts
This methodology offers an analytical lens through which to describe the value of a card that
hasn’t sold recently where we have recent comps of other grades of the same card. It also brings
our team comfort knowing this method is used by collectors regularly. “Grade Ratio Value” brings them automation and mathematics to aid them. The ways in which it is limited are worth
noting.
The ratio of one grade to another changes over time and is never 100% consistent. Anecdotally
we have noticed the ratio of higher grades to lower increases as the overall market increases.
This can skew the final calculation when using the ratio from an older date.
Second, the ratios won’t be perfect because of several variables being introduced to the two cards
selling. The cards can sell within 6 months of each other to be eligible and it’s possible the
market for that card changes during the 6 month window and the comparison grade sells. Also,
it’s possible the two cards were sold on different platforms which can affect the value of one to
the other.
In short, any pricing model – even one that is based purely on “comps” – should be conceived of
as a theoretical tool for performing analysis, rather than a definitive determination of value.