From observations from longtime members in the old forum, the only thing that makes a bit of difference is drawing a lot of addresses in one sitting. That tends to give more variety than the usual 3-5 common countries. But not necessarily a rare country. I rarely get more than 2-3 addresses at once but the rare times when I get more I get variety (assuming I’m not using “repeated countries”). If I get one address a day I’ll most likely get Germany/USA/Russia.
That’s the only thing I found to make a tiny tiny amount of difference. Time of day doesn’t matter a lot in my opinion.
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That link shows the countries and territories in Postcrossing.
Not the stats that you are all showing.
| Category | Total | Missing Common | Rarest |
|---|---|---|---|
| Sent | 182 | 20 
|
76 
|
| Received | 190 | 16 
|
79 
|
| Joined (MM/YY) | 05/19 |
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Here’s mine.
| Category | Total | Missing Common | Rarest |
|---|---|---|---|
| Sent | 491 | 27 
|
136 
|
| Received | 478 | 39 
|
81 
|
| Joined | 02/07 |
To get the stats, you simply click the ‘Postcards’ column heading under the map, which will organize the countries by number of postcards sent. (You might have to click it twice to get it in descending order.) Then, you just compare your own stats on your profile to that list. For instance, if you’ve sent to Nepal, you’ll see that it’s 105 on the list. That’s the number you would input, if that’s your rarest country. Hope that helps!
@zeihha I see that you’ve actually not sent to other countries more common than New Zealand (Portugal and Thailand, for instance…Portugal is #20).
But side note, I would love to draw a country in the Caribbean! 
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sorry, I misunderstood how to count common missing countries Data is still quite preliminary, but I updated the initial post with the data submitted so far. Strong correlation between how many you’ve sent/received and what your lowest ‘missed common’ card is. Not quite as strong correlation with time, or with what your rarest is.
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| Category | Total | Missing Common | Rarest |
|---|---|---|---|
| Sent | 1073 | 43  : |
168 
|
| Received | 1025 | 33  : |
119 
|
| Joined (MM/YY) | 02/14 |
@TheBeaverFamily Regarding the “When Joined” axis, could you update the unit so it can be easily understandable?
P.S. I only know how to do it in Power BI but not Excel. Sorry 
@iamfromhk I tried to get it to display dates, but no luck. I ended up doing the year as a number x 12 + month. I’ll keep playing as I update the data, but for now, if you’re curious, just divide the approximate number by 12 and you’ll be close.
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| Category | Total | Missing Common | Rarest |
|---|---|---|---|
| Sent | 433 | 33
|
95 
|
| Received | 436 | 41 
|
82 
|
| Joined (MM/YY) | 02/18 |
I hope I have understood adding the data correctly. If not, let me know.
| Category | Total | Missing Common | Rarest |
|---|---|---|---|
| Sent | 72 | 11 
|
51 
|
| Received | 71 | 10 
|
54 
|
| Joined (MM/YY) | 06/16 |
Love this idea. would you mind sharing the collected data?
| Category | Total | Missing Common | Rarest |
|---|---|---|---|
| Sent | 230 | 21 
|
54
|
| Received | 230 | 25 
|
214 
|
| Joined (MM/YY) | 11/17 |
Seems interesting! I think that there’s a huge leap on my rarest sent and received!
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Here is myy data
| Category | Total | Missing Common | Rarest |
|---|---|---|---|
| Sent | 604 | 35 
|
80 
|
| Received | 602 | 47 
|
110 
|
| Joined | Jun 13 |
It would be interesting, if there are any trends resolved.
| Category | Total | Missing Common | Rarest |
|---|---|---|---|
| Sent | 1029 |
43
|
73 
|
| Received | 1029 |
50 
|
76
|
| Joined (MM/YY) | 12/13 | with a few months of inactivity every now and then |
Quite a nice set of stats you’ve got here I think travel mode makes it easier nowadays to receive from an exotic country - but harder now with the pandemic since it cuts off a lot of small islands (not to mention the actual traveling), and/or seriously increases travel times. As others mentioned, increasing postage might change the balance as it becomes seriously restrictive - such is the case for Denmark and some South American countries, from what I’ve heard.
Loving seeing the Guernsey flag there 
. I would class my rare as Jersey (our neighbour, I could almost wave on a good day) they only have 31 members.
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Updated the original graphs with 13 participants. @iamfromhk I made the Joined-By graphs display years now. With the recent update, the Total Sent/Common Countries correlation got stronger. The Total Received/Common Countries got a little weaker, but still shows good correlation. Rarest Sent according to Total Sent shows some very weak correlation, and Rarest Received according to Total Received shows very little correlation.
Joined Date shows very little correlation, and actually the Rarest Received shows an opposite slope. Some of this can be explained by people joining then becoming inactive.
More data = better results. Who else has stats to share? Thanks to those who have shared!
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| Category | Total | Missing Common | Rarest |
|---|---|---|---|
| Sent | 706 | 33
|
68 
|
| Received | 695 | 44 
|
50 
|
| Joined (MM/YY) | 04/07 |
I’m quite sure joined date would show no correlation at all, if you removed the effect of the underlying correlation between joined date and cards sent. Meaning, the only reason an early joined date would have sent to/received from rarer countries, is that this user has sent/received more cards.
One thing I find really interesting is that the correlations with “missing common” are much less noisy than with “rarest”. I feel like it makes perfect sense, but I can’t quite put my finger on why it makes sense in a theoretical framework. anyone?