If you’re new to collecting, it is important to know a few things.

1. Companies like PSACard.com encapsulate and grade collectibles.

2. These grades typically range from 1 (poor) to 10 (gem mint)

3. A perfect 10, or even a mint 9 is very difficult to achieve. Typically, a collectible needs to appear flawless. If you can find a frayed corner or other imperfection with the naked eye, the chances of a 9 or 10 are pretty much zero.

4. As grade increases, so does the value of the card.

Statement #4 is what we are focusing on with this report. We all know prices increase with grade — but can we quantify by what factor prices increase as a grade increases?
Is it a 10% increase for every point on the scale?
20%?
Less?
Let’s crunch some data and find out.

Let’s start with a desirable card. One at random, but with enough prior sales to really dig into the data.

We started with a 1996 Topps Mickey Mantle card. All of the cards were graded in various ranges from 1 to 9, by PSA. All previous sales transactions were found and imported for the analysis.

1966 Topps Mickey Mantle. Pretty cool card!

We found over 2000 reported transactions of this card, and we plotted each transaction below.
X axis is Date
Y axis is Price
and we grouped them in colors by grade.
So, step 1:

Each graded card is represented by a color. As you can see.
The Mint 9’s are pink and represent the top section. We can clearly see, grade MASSIVELY affects price.

Let’s dig a little more and find out HOW MUCH grade effects price.
Let’s do a simple linear regression, controlling for year:

Pay attention to the areas highlighted in blue above. As we can see, grade held constant, the price has been increasing by about $70 per year (which is a little over 10% per year). A 10% return on your investment over the years is pretty solid!
We see that, holding year constant, price increases with respect to grade by about $427 per a one point increase in grade! Given the average price of this 1966 Topps Mickey Mantle card in our dataset is $647.32, we absolutely must control for grade if we perform any sort of larger analysis for this type of data.

So how could we generalize this? Can we get to the point where we can say that price increase by X% given a 1 point increase in grade? Is the change linear or proportional? Let’s find out!

(in the next article) 😀

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