Atlas Diaries #1 — Did I buy the right cards?
"Would you buy this?"
"Should I sell this now?"
"Is this card actually cheap?"
"Did I buy the right one?"
I have these conversations all the time.
Usually with friends, sometimes with myself.
And before Atlas, the answers were mostly some combination of experience, intuition, market chatter, Discord opinions and the vague feeling that we'd seen something like this before.
Which is why I wanted to test a theory.
Maybe One Piece cards have a rhythm.
Maybe a card comes out, gets hyped, gets flooded with supply, falls, finds a floor, goes quiet, and eventually starts climbing again as supply disappears.
If that rhythm exists, then perhaps the question isn't simply:
"Is this card good?"
Maybe it's:
"Where is this card in its life?"
So I went looking.
And what we found was stranger than the lifecycle I expected.
The first price might not be the price
Let's start with a receipt.
One OP16 card opened around:
฿8,500
Two days later:
฿4,200
A few days after that:
฿3,200
At first glance, that's a 63% collapse.
And if you bought at ฿8,500, that feels pretty bad.
But there is a problem with calling this a 63% loss.
What if ฿8,500 was never really the market price?
That question became impossible to ignore once we looked at how Japanese cards are actually priced immediately after release.
For a fresh Japanese set, there isn't some perfectly efficient global market waiting at the moment the packs open.
There are a handful of early anchors.
YUYU-TEI listings appear almost immediately.
Then, gradually, more marketplaces and more observations arrive.
CardTrader.
Cardmarket.
PriceCharting.
Eventually realized sales.
The market gets more information.
And the number changes.
That distinction matters.
Because ฿8,500 → ฿3,200 doesn't necessarily mean that a card lost 63% of its underlying value.
It can also mean that the market started with an extremely aggressive anchor and spent the following weeks discovering where the card actually belonged.
And Atlas gives us a way to see that discovery happening.
Then we saw it happen again
OP16 gave us the first clue.
Two days after release, YUYU-TEI cut the median price of the chase cards by 47.8%.
That was already pretty remarkable.
Then OP17 came out.
Same market.
Same early Japanese pricing environment.
Three months later.
And again, the opening prices held for roughly two days before being aggressively cut.
This time the median cut was 37.6%, with 88% of the tracked chase cards falling by more than 10%.
That got my attention.
Because one card doing it could be noise.
Two releases doing something remarkably similar starts looking like a pattern.
But it still wasn't the pattern I had expected.
I had imagined a gradual post-release decline.
Instead, the first thing we found was almost a 48-hour reset.
The market didn't slowly walk away from the opening number.
It looked more like it suddenly said:
"No. That's too high."
Then OP16 kept falling
This is where things got uncomfortable.
OP16 gives us something OP17 doesn't have yet:
Time.
A full 100 days.
We took the Japanese OP16 cards with meaningful release prices and removed the cards where the data itself was clearly unstable.
34 cards remained.
At release:
100% of them had their starting price.
100 days later:
34 out of 34 were lower.
The median was down:
65.1%.
Even the top 25% of the cohort were down almost 50%.
And I went looking for the part of the lifecycle I expected to find next.
The floor.
The stale period.
The recovery.
The gradual repricing.
The beginning of scarcity.
I couldn't find it.
Not yet.
The lowest observation for most of these cards was simply the latest observation we had.
Even if you had perfect hindsight and bought each card at its exact lowest observed price, the median return by September 7 was only +2.5%.
There wasn't some obvious goldmine hiding at the bottom.
At least not in the first 100 days.
That was probably the biggest surprise of the entire research.
We went looking for a lifecycle.
OP16 is still falling.
But then we had to ask: how much of that fall was real?
This is where Atlas became particularly interesting.
Because on day one, the problem isn't just that prices are high.
It's that we don't have much evidence yet.
For 97% of the OP16 chase cards, the release-day price was based on exactly one source.
One.
And the median Atlas Estimate at that point was 186% above where those cards would sit 100 days later.
Then the evidence arrived.
More sources appeared.
And the estimate came down.
At day one, the median difference from the eventual level was:
+186%
At day seven:
+112%
At day 30:
+45%
At day 60:
+36%
At day 90:
+3%
That is a very different story from simply saying:
"The cards crashed 65%."
The number was changing because the market was changing.
But the number was also changing because our view of the market was getting better.
Those two things are happening at the same time.
And with the data we have today, we can't perfectly separate them.
That's important.
I don't want to pretend that every decline is just "price discovery."
Some of it is clearly real repricing.
But the early price of a fresh Japanese card is not the same kind of information as a price that has been tested across several independent markets for months.
A ฿3,300 card with one source behind it is not the same information as a ฿3,300 card with four sources and months of history.
The number is identical.
The confidence behind the number isn't.
So maybe "the crash" is the wrong way to look at it
This changed how I think about new releases.
Imagine you see a chase card on release day at ฿8,200.
Your instinct is to think:
"This card is worth ฿8,200."
But maybe what you should really think is:
"Someone is currently asking ฿8,200."
Those are not the same statement.
Especially when the market is only a few days old.
OP16 gives us a perfect example.
YUYU-TEI could open a card at ฿8,500.
Then cut it to ฿4,200.
Then other marketplaces arrive at completely different levels.
Eventually the market converges somewhere else.
The card didn't necessarily "lose" the difference between those numbers.
Part of that difference may simply have been the distance between an early anchor and a discovered market price.
And that is exactly why I think historical price data becomes so powerful.
A price without context is just a number.
A price with its history becomes a story.
And the story isn't the same for every card
This was another assumption I had to let go of.
There isn't one universal One Piece card lifecycle.
When we classified thousands of cards by their actual price shapes, the largest group — 41.3% — didn't fit a clean pattern at all.
Some rose and held.
Some dipped and recovered.
Some spiked and gave it all back.
Some fell and stabilised.
Some barely moved.
Some never moved.
So I don't think the answer is:
"Every One Piece card goes through these nine phases."
The market is messier than that.
And that's probably a good thing.
Because cards aren't identical assets.
A base SEC is not a championship prize.
A Manga isn't an R alt-art.
A promo with a closed print run isn't the same thing as a card that can keep coming out of booster boxes.
The supply architecture matters.
A lot.
The one split that actually survived
When we separated cards by type, something much more interesting appeared.
Closed-supply categories were generally positive over the common 81-day window:
Promos: +26.3%
Anniversary cards: +18.8%
Championship cards: +15.1%
SP alt-arts: +14.2%
Meanwhile, several booster-product chase categories were flat or negative:
SR: −5.6%
SEC: −10.7%
And the split survived the controls we could apply.
But even here, there is a giant asterisk.
Some of the strongest-performing categories are also thin markets.
And scarcity isn't magic.
One championship promo in our data fell roughly 80%.
So I wouldn't turn this into:
"Buy promos."
That's not what the data says.
What it says is something more interesting:
The supply mechanism behind a card appears to matter more than simply how old the card is.
A card that can continue entering the market through sealed product is fundamentally different from a print whose supply is closed.
That feels much closer to the kind of thing collectors should actually be thinking about.
The hero cards have their own story
There was another pattern inside OP16 that I didn't expect.
The most expensive cards didn't immediately collapse like the chase tier.
At day one, the top 1% of cards represented about 42% of the entire set's value.
By day 100, they represented 62%.
That sounds like the heroes were appreciating.
They weren't.
The middle of the set was simply collapsing faster.
The ฿3,300+ cards were almost flat for the first month while the roughly ฿660–฿3,300 chase tier lost around half its value.
Then the hero tier had its own decline.
By day 100, it was down 68.7%.
So even the "safe" cards weren't necessarily safe.
They just had a different clock.
And I think that is important for collectors.
A card holding its value while everything around it collapses doesn't necessarily mean demand has suddenly become stronger.
Sometimes it simply means the market hasn't finished repricing that card yet.
And then there are the cards that break the story
If this were a neat investment thesis, I could stop here.
I don't want to.
Because the counterexamples are some of the most interesting data we have.
Take OP16 Sakazuki.
While most of the set was getting cut, YUYU-TEI actually raised its sticker:
฿63,600 → ฿106,400
on the second day.
It eventually climbed to around ฿127,700 and held there for roughly twelve weeks before its own decline.
So the two-day cut wasn't universal.
Then there's OP16 Luffy.
Its YUYU-TEI sticker never moved from around ฿8,500.
And yet the card eventually lost around 63%.
Other markets simply came in much lower.
So you don't even need to see the Japanese anchor fall for the market to reject it.
And then there are the really strange examples.
One OP17 card appeared to go:
฿2,070 → ฿209,200
overnight.
Except it wasn't.
It was a placeholder/mapping issue.
Another whole block of R cards opened at exactly around ฿112, then dispersed as real prices arrived.
Those cards weren't suddenly pumping.
The data was learning.
This is why I increasingly think one of the most important things Atlas can tell you isn't:
"This card is up 40%."
It's:
"How much should I trust this number?"
So... did I buy the right cards?
This is where the answer gets frustrating.
We tested momentum.
Cards that had already risen.
Cards that had already fallen.
Cards that were near their highs.
Cards that were deep below their highs.
None of these gave us a reliable out-of-sample signal.
"Buy the dip" didn't work.
"Buy what's already going up" didn't work.
Being 35% below a previous peak didn't magically make a card a good buy.
And the stale-market theory didn't survive either.
Once we controlled for source coverage and card class, stale cards mostly just did one thing:
They stopped falling.
They didn't reliably start rising.
So if I was hoping Atlas would eventually give me a magic formula for identifying the next winner...
It didn't.
And that's actually what I like about the result.
Because maybe that's not what Atlas should be doing.
Maybe the question is different
Before Atlas, I might have looked at a card at ฿3,300 and asked:
"Is this cheap?"
Now I want to ask:
"Why is it ฿3,300?"
How old is the price?
How many markets are contributing?
Is it a listing?
A buyback?
A realized sale?
Is one shop setting the entire number?
Has Cardmarket caught up?
Has the US market caught up?
Is this card behaving like the rest of its set?
Is it behaving differently?
Has the set already gone through its initial supply wave?
Is the print still open?
And perhaps most importantly:
How much of what I'm seeing is a market moving, and how much is the market discovering itself?
That's a much better question.
We still don't know the ending
And this is where I want to be careful.
We have 100 days of OP16.
We have 16 days of OP17.
That's enough to see the beginning of something.
It isn't enough to tell us what happens in year two.
We don't have the data to say exactly when a set bottoms.
We don't have the data to say every set eventually recovers.
We don't have enough releases to claim that this pattern applies universally.
And we certainly don't have enough evidence to tell anyone:
"Buy this card because the data says it will go up."
What we do have is the beginning of a record.
OP16 has now lived through its first 100 days.
OP17 is currently living through the same early environment.
And future sets will give us something that we didn't have when we started building Atlas:
history.
So, did I buy the right cards?
I don't know.
And maybe that's the point.
I started this research wanting to find a lifecycle.
Instead, I found that the first price can be one of the least reliable prices a card ever has.
I found that two releases showed an eerily similar two-day repricing.
I found that OP16 kept falling long after that initial shock.
I found that some of the apparent "crash" was actually the market becoming better informed.
I found that momentum doesn't seem to tell us much.
I found that scarcity and supply architecture may matter more than simply how old a card is.
And I found that some cards break every neat story you try to tell about them.
So maybe the most useful question isn't:
"Did I buy the right card?"
Maybe it's:
"Did I understand what I was buying?"
Because there's a huge difference between buying a card at ฿3,300...
and buying a card at ฿3,300 when you know that price is based on one source, two days of history, an aggressive Japanese anchor and a market that hasn't finished discovering itself.
Atlas can't tell me where that card will be in a year.
Not yet.
But it can show me what the number is made of.
And for a collector trying to decide whether to buy, hold or sell, that might be the more important thing.
The goal isn't to predict the future perfectly.
It's to make sure we're at least looking at the present clearly.
Disclaimer
OP-Atlas currently tracks more than 11,000 cards across multiple market sources. Market coverage and source availability can change over time.
OP-Atlas is independent and not affiliated with, endorsed by, sponsored by, or associated with Bandai, Shueisha, Toei Animation, or Eiichiro Oda. Market data may contain errors, delays, incorrect mappings, missing data, or other inaccuracies. Atlas Estimate is an analytical estimate, not a guaranteed market price or valuation. Prices can change quickly. This content is provided for informational and entertainment purposes only and is not financial advice.
Content note: AI was used as a tool in the creation of the title artwork and for quality assurance (QA), research and translation support. Final content was reviewed and edited by the OP-Atlas team.