Y-DNA frequencies in FTDNA tree

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I don't remember seeing it before, so, for fun, here're frequencies of haplogroups in FTDNA tree (not projects) by flags, which are based on the self-reported MDKA's locations. Although these frequencies are based on about 84,000 samples, they don't necessarily represent modern frequencies in all cases. Perhaps the J1 frequency in Eastern Europe is a nice example, as it's so frequent among Ashkenazi. Many fled to America, where DNA testers seem to concentrate.
Plus, we should expect some biases, especially in the cases there're important regional variations. For example, the R1b % for Italy based on FTDNA tree, lower than expected, may be related to the fact that most of the FTDNA testers with Italian patrilineal ancestry are Italian-Americans, who in turn descend mostly from South Italians, as far as I know.

So, the %s suggested for Europe as a whole, based on male populations in each country, are just references, and they should not be taken literally. The scope is FTDNA tree. It seems an interesting approach anyway, because it doesn't make sense to average %s of countries with very different population sizes.

I've included Turkey out of curiosity, since part of it is located in Europe, but I didn't use it for estimating %s in Europe.

For determining the % of certain macro-haplogroup for certain flag, I simply divided the number of testers who informed this flag and who belong to this haplogroup by the number of testers associated to the same flag in the root haplogroup A-PR2921. The data is from two days ago.
For example, there were 7468 R1b testers under the English flag, and 13768 under the A-PR2921. It'd mean that abt. 54% of the FTDNA testers under the English flag belong to the haplogroup R1b.

I used another FTDNA tool, but the numbers could be checked also here, apparently: https://www.familytreedna.com/public/y-dna-haplotree (see Country Report).
It seems to work well for macro-haplogroups, but the estimations may become more complex when it comes to low level haplogroups.


C-M216E-M96G-M201H-L901I1-M253I2-P215J1-M267J2-M172L-M20N-M231Q-M242R1a-M420R1b-M343T-M184OthersA-PR2921 samples in FTDNA TreeMale population (approx.)
Albania0.00%29.05%0.68%0.00%10.14%9.46%2.70%22.30%0.00%0.00%0.00%6.08%18.24%0.00%1.35%1481,430,000
Austria0.18%10.81%7.75%0.18%9.19%9.01%7.21%9.19%1.08%0.54%0.90%15.32%26.13%1.26%1.26%5554,357,000
Belarus0.00%13.66%6.56%0.00%1.91%6.42%17.08%14.07%0.14%5.74%1.37%21.04%9.56%1.64%0.82%7324,416,000
Belgium0.00%4.47%5.65%0.00%13.41%5.65%1.41%6.35%0.71%0.00%0.47%3.06%55.29%2.12%1.41%4255,645,000
Bosnia&Herz0.00%12.15%1.10%0.00%11.60%38.67%1.66%8.84%0.00%1.10%1.10%20.99%2.76%0.00%0.00%1811,876,000
Bulgaria0.00%18.40%6.78%0.73%5.33%20.82%4.36%14.29%0.24%0.73%1.21%10.90%14.04%1.45%0.73%4133,396,000
Croatia0.00%12.87%2.97%0.50%7.92%35.15%0.99%6.93%0.99%1.49%1.49%17.33%8.91%1.49%0.99%2021,973,000
Czech Rep0.24%8.20%5.51%0.12%6.49%10.65%3.30%5.88%0.24%2.45%0.37%28.03%27.42%0.86%0.24%8175,244,000
Denmark0.00%2.64%2.79%0.15%36.51%8.65%0.15%2.35%0.00%1.17%1.76%8.50%33.14%0.73%1.47%6822,889,000
England0.05%3.45%3.81%0.19%18.11%8.98%0.75%2.79%0.08%0.14%0.71%4.17%54.24%0.52%2.01%13,76826,069,148
Estonia0.00%2.46%0.82%0.00%13.11%2.46%0.82%0.00%0.00%40.98%0.00%24.59%13.93%0.00%0.82%122625,635
Finland0.00%0.59%0.37%0.08%25.37%0.86%0.11%0.24%0.03%60.55%0.13%5.70%5.49%0.11%0.37%3,7362,723,000
France0.09%5.77%6.39%0.09%8.84%6.36%1.50%7.30%0.16%0.13%0.34%2.51%58.45%1.00%1.07%3,19132,390,000
Germany0.13%6.85%7.28%0.02%16.98%8.52%2.87%7.33%0.32%0.37%0.75%9.73%36.27%1.03%1.56%8,57040,970,000
Greece0.42%16.22%11.14%0.00%1.97%11.85%11.28%20.45%3.81%0.28%0.85%5.50%11.85%2.68%1.69%7095,208,000
Hungary0.21%9.16%5.96%0.21%6.92%10.76%9.16%12.67%0.21%1.92%2.45%19.38%18.64%1.28%1.06%9394,676,000
Iceland0.00%0.74%0.00%0.00%31.11%0.74%0.00%0.00%0.74%0.00%7.41%22.96%35.56%0.00%0.74%135182,837
Ireland0.07%1.45%1.22%0.06%6.60%7.65%0.58%1.55%0.05%0.04%0.16%1.92%77.85%0.25%0.57%10,5272,429,000
Italy0.22%12.87%13.93%0.13%3.53%4.91%7.32%20.61%0.83%0.06%0.51%3.31%27.00%3.66%1.09%3,11529,380,000
Latvia0.00%7.81%4.17%0.00%2.08%4.69%11.98%12.50%0.00%21.88%4.69%17.19%10.42%1.04%1.56%192884,909
Lithuania0.12%10.82%6.90%0.00%2.38%2.73%15.93%11.53%0.00%15.70%3.45%17.84%9.39%1.90%1.31%8411,296,000
Luxembourg0.00%7.84%7.84%0.00%1.96%3.92%1.96%5.88%0.00%0.00%0.00%5.88%62.75%0.00%1.96%51308,720
Macedonia0.00%18.28%5.38%1.08%6.45%21.51%4.30%16.13%0.00%0.00%1.08%13.98%8.60%2.15%1.08%931,040,000
Moldova0.00%9.46%6.76%1.35%2.70%4.05%21.62%18.92%2.70%0.00%2.70%18.92%6.76%2.70%1.35%741,707,000
Montenegro0.00%18.48%4.35%0.00%7.61%22.83%1.09%6.52%1.09%3.26%0.00%7.61%27.17%0.00%0.00%92307,712
Netherlands0.00%4.85%4.94%0.26%21.53%7.91%1.62%5.02%0.00%0.34%1.53%3.15%46.47%1.36%1.02%1,1758,581,000
North. Ireland0.08%1.17%0.78%0.00%10.58%11.36%1.40%1.25%0.00%0.23%0.00%3.04%69.03%0.39%0.70%1,285928,149
Norway0.00%1.07%1.39%0.05%37.33%4.12%0.37%0.91%0.00%2.57%3.75%21.59%25.66%0.27%0.91%1,8672,685,000
Poland0.38%6.76%3.55%0.03%6.32%8.24%8.77%8.77%0.06%3.43%1.70%36.95%13.49%1.01%0.53%3,18018,380,000
Portugal0.00%12.77%7.02%0.23%4.83%5.18%5.41%10.36%0.35%0.23%0.35%1.50%47.30%4.03%0.46%8694,852,000
Romania0.21%12.95%6.79%0.64%5.73%10.19%14.01%18.90%0.21%1.27%2.12%10.83%12.10%2.76%1.27%4719,500,000
Russia2.69%3.56%7.37%0.06%3.81%4.07%11.95%18.03%2.14%13.52%2.44%20.90%6.13%0.85%2.48%5,08751,323,000(Euro)
Scotland0.10%1.54%0.98%0.08%12.21%7.81%0.63%1.90%0.04%0.05%0.16%5.18%68.39%0.16%0.78%7,6682,656,000
Serbia0.00%12.32%1.48%0.49%6.40%26.60%2.46%10.34%0.00%9.36%0.49%16.26%13.30%0.00%0.49%2033,393,000
Slovakia0.49%8.64%5.68%0.25%5.68%14.57%5.93%4.94%0.00%4.69%0.00%33.09%12.59%1.23%2.22%4052,661,000
Slovenia0.00%6.85%5.48%0.00%15.07%19.18%0.00%8.90%1.37%0.00%0.00%26.03%15.07%1.37%0.68%1461,039,000
Spain0.26%11.92%6.35%0.04%4.89%6.05%6.95%10.29%0.30%0.13%0.86%1.59%46.48%2.83%1.07%2,33223,010,000
Sweden0.00%1.38%2.40%0.05%44.67%3.37%0.10%0.91%0.05%7.44%4.13%14.31%20.89%0.05%0.23%3,8305,142,000
Switzerland0.00%7.14%12.05%0.26%11.42%9.18%1.21%6.38%0.89%0.13%0.77%3.25%45.03%0.96%1.34%1,5684,237,000
Turkey0.89%6.57%12.81%0.22%0.67%2.78%15.37%25.17%4.90%1.78%2.23%6.01%13.14%4.90%2.56%8980
Ukraine0.40%12.06%5.74%0.13%2.70%11.54%15.49%13.45%0.26%2.44%2.11%20.57%9.49%1.98%1.65%1,51719,460,000
Wales0.00%3.32%4.49%0.00%12.31%5.30%0.72%1.44%0.00%0.00%0.09%1.17%69.81%0.27%1.08%1,1131,547,000
Europe (based on pop sizes)0.54%7.73%6.59%0.13%9.64%7.89%6.39%10.88%0.64%3.61%1.25%11.92%29.94%1.47%1.39%340,818,110
 
More interesting references for comparison, from modern Europeans. As always, biases are possible. Unfortunately, it's not possible to know the divisions by country.

They're not references to the number of people that were confirmed for certain haplogroup. They actually show the number of samples that get the ancestor or derived alleles among those who got results for the position.
Numbers from genomAD seem more coherent. In the case of HGDP and 1000 genomes (1KG), the number of samples is too low.
I didn't find a reliable SNP for I2 in NCBI, so I inferred the % in about ~7 (100 - sum of the others).
The %s from genomAD sum up to 94% only, so I just applied a little correction. No big deal.

genomAD in special is a nice tool to play with.

Nr results for SNPAllele CountFrequencyCorrected
E
genomAD v3.1.2M96 (n=)
European (non-Finnish)133846074.54%4.85%
Admixed American356746413.01%
Ashkenazi76518524.18%
Amish21200.00%
NCBI ALFA European2336612485.34%
HGDP European7733.90%
1KG European (source 1)24372.88%
1000 Genomes (source 2)
CEU4900.00%
FIN3800.00%
GBR4600.00%
IBS5423.70%
TSI5347.55%
G
genomAD v3.1.2M201 (n=)
European (non-Finnish)134964553.37%3.61%
Admixed American36242155.93%
Ashkenazi765628.10%
Amish2163114.35%
NCBI ALFA European2979811763.95%
HGDP European7967.59%
1KG European (source 1)24372.88%
1000 Genomes (source 2)
CEU4936.12%
FIN3800.00%
GBR4600.00%
IBS5423.70%
TSI5323.77%
I1
genomAD v3.1.2M253 (n=)
European (non-Finnish)13451154811.51%12.32%
Admixed American3665832.26%
Ashkenazi76120.26%
Amish21273.30%
NCBI ALFA European60756778112.81%
HGDP European7922.53%
1KG European (source 1)2422510.33%
1000 Genomes (source 2)
CEU49816.33%
FIN38923.68%
GBR46613.04%
IBS5400.00%
TSI5323.77%
I2
genomAD v3.1.2P215 (n=)
European (non-Finnish)134349396.99%7.48%
Admixed American35881494.15%
Ashkenazi759233.03%
Amish21410.47%
NCBI ALFA European7.00%
HGDP European801316.25%
1KG European (source 1)23572.98%
1000 Genomes (source 2)
CEU4948.16%
FIN3812.63%
GBR4612.17%
IBS5423.70%
TSI5300.00%
L
genomAD v3.1.2M20 (n=)
European (non-Finnish)13643200.15%0.16%
Admixed American3738240.64%
Ashkenazi77130.39%
Amish21500.00%
NCBI ALFA European599628691.45%
HGDP European8100.00%
1KG European (source 1)24100.00%
1000 Genomes (source 2)
CEU4900.00%
FIN3800.00%
GBR4600.00%
IBS5400.00%
TSI5300.00%
N
genomAD v3.1.2M231 (n=)
European (non-Finnish)134574233.14%3.36%
Admixed American362420.06%
Ashkenazi76210.13%
Amish21100.00%
NCBI ALFA European7342011451.56%
HGDP European7722.60%
1KG European (source 1)244229.02%
1000 Genomes (source 2)
CEU4900.00%
FIN382360.53%
GBR4600.00%
IBS5400.00%
TSI5300.00%
Q
genomAD v3.1.2M242 (n=)
European (non-Finnish)13478500.37%0.40%
Admixed American358441011.44%
Ashkenazi771253.24%
Amish21500.00%
NCBI ALFA European7585220022.64%
HGDP European8111.23%
1KG European (source 1)24000.00%
1000 Genomes (source 2)
CEU4900.00%
FIN3800.00%
GBR4600.00%
IBS5400.00%
TSI5300.00%
R1a
genomAD v3.1.2M513 (n=)
European (non-Finnish)1354712138.95%9.58%
Admixed American3586190.53%
Ashkenazi767597.69%
Amish21641.85%
NCBI ALFA European7184868009.46%
HGDP European78810.26%
1KG European (source 1)243104.12%
1000 Genomes (source 2)M420 (n=)
CEU4924.08%
FIN3837.89%
GBR4648.70%
IBS5411.85%
TSI5323.77%
R1b
genomAD v3.0M343 (n=)
European (non-Finnish)12352663653.72%57.50%
Admixed American3137155449.54%
Ashkenazi7407410.00%
Amish20114270.65%
NCBI ALFA European338341832954.17%
1000 Genomes
CEU493061.22%
FIN3812.63%
GBR463473.91%
IBS543972.22%
TSI532445.28%
T
genomAD v3.1.2M184 (n=)
European (non-Finnish)13476930.69%0.74%
Admixed American3700621.68%
Ashkenazi773354.53%
Amish21400.00%
NCBI ALFA EuropeanCTS482 (n=)
692249891.43%
M184 (n=)
8040826783.33%
HGDP European8200.00%
1KG European (source 1)24131.24%
1000 Genomes (source 2)
CEU4900.00%
FIN3800.00%
GBR4600.00%
IBS5411.85%
TSI5335.66%
 
I don't remember seeing it before, so, for fun, here're frequencies of haplogroups in FTDNA tree (not projects) by flags, which are based on the self-reported MDKA's locations. Although these frequencies are based on about 84,000 samples, they don't necessarily represent modern frequencies in all cases. Perhaps the J1 frequency in Eastern Europe is a nice example, as it's so frequent among Ashkenazi. Many fled to America, where DNA testers seem to concentrate.
Plus, we should expect some biases, especially in the cases there're important regional variations. For example, the R1b % for Italy based on FTDNA tree, lower than expected, may be related to the fact that most of the FTDNA testers with Italian patrilineal ancestry are Italian-Americans, who in turn descend mostly from South Italians, as far as I know.

So, the %s suggested for Europe as a whole, based on male populations in each country, are just references, and they should not be taken literally. The scope is FTDNA tree. It seems an interesting approach anyway, because it doesn't make sense to average %s of countries with very different population sizes.

I've included Turkey out of curiosity, since part of it is located in Europe, but I didn't use it for estimating %s in Europe.

For determining the % of certain macro-haplogroup for certain flag, I simply divided the number of testers who informed this flag and who belong to this haplogroup by the number of testers associated to the same flag in the root haplogroup A-PR2921. The data is from two days ago.
For example, there were 7468 R1b testers under the English flag, and 13768 under the A-PR2921. It'd mean that abt. 54% of the FTDNA testers under the English flag belong to the haplogroup R1b.

I used another FTDNA tool, but the numbers could be checked also here, apparently: https://www.familytreedna.com/public/y-dna-haplotree (see Country Report).
It seems to work well for macro-haplogroups, but the estimations may become more complex when it comes to low level haplogroups.


C-M216E-M96G-M201H-L901I1-M253I2-P215J1-M267J2-M172L-M20N-M231Q-M242R1a-M420R1b-M343T-M184OthersA-PR2921 samples in FTDNA TreeMale population (approx.)
Albania0.00%29.05%0.68%0.00%10.14%9.46%2.70%22.30%0.00%0.00%0.00%6.08%18.24%0.00%1.35%1481,430,000
Austria0.18%10.81%7.75%0.18%9.19%9.01%7.21%9.19%1.08%0.54%0.90%15.32%26.13%1.26%1.26%5554,357,000
Belarus0.00%13.66%6.56%0.00%1.91%6.42%17.08%14.07%0.14%5.74%1.37%21.04%9.56%1.64%0.82%7324,416,000
Belgium0.00%4.47%5.65%0.00%13.41%5.65%1.41%6.35%0.71%0.00%0.47%3.06%55.29%2.12%1.41%4255,645,000
Bosnia&Herz0.00%12.15%1.10%0.00%11.60%38.67%1.66%8.84%0.00%1.10%1.10%20.99%2.76%0.00%0.00%1811,876,000
Bulgaria0.00%18.40%6.78%0.73%5.33%20.82%4.36%14.29%0.24%0.73%1.21%10.90%14.04%1.45%0.73%4133,396,000
Croatia0.00%12.87%2.97%0.50%7.92%35.15%0.99%6.93%0.99%1.49%1.49%17.33%8.91%1.49%0.99%2021,973,000
Czech Rep0.24%8.20%5.51%0.12%6.49%10.65%3.30%5.88%0.24%2.45%0.37%28.03%27.42%0.86%0.24%8175,244,000
Denmark0.00%2.64%2.79%0.15%36.51%8.65%0.15%2.35%0.00%1.17%1.76%8.50%33.14%0.73%1.47%6822,889,000
England0.05%3.45%3.81%0.19%18.11%8.98%0.75%2.79%0.08%0.14%0.71%4.17%54.24%0.52%2.01%13,76826,069,148
Estonia0.00%2.46%0.82%0.00%13.11%2.46%0.82%0.00%0.00%40.98%0.00%24.59%13.93%0.00%0.82%122625,635
Finland0.00%0.59%0.37%0.08%25.37%0.86%0.11%0.24%0.03%60.55%0.13%5.70%5.49%0.11%0.37%3,7362,723,000
France0.09%5.77%6.39%0.09%8.84%6.36%1.50%7.30%0.16%0.13%0.34%2.51%58.45%1.00%1.07%3,19132,390,000
Germany0.13%6.85%7.28%0.02%16.98%8.52%2.87%7.33%0.32%0.37%0.75%9.73%36.27%1.03%1.56%8,57040,970,000
Greece0.42%16.22%11.14%0.00%1.97%11.85%11.28%20.45%3.81%0.28%0.85%5.50%11.85%2.68%1.69%7095,208,000
Hungary0.21%9.16%5.96%0.21%6.92%10.76%9.16%12.67%0.21%1.92%2.45%19.38%18.64%1.28%1.06%9394,676,000
Iceland0.00%0.74%0.00%0.00%31.11%0.74%0.00%0.00%0.74%0.00%7.41%22.96%35.56%0.00%0.74%135182,837
Ireland0.07%1.45%1.22%0.06%6.60%7.65%0.58%1.55%0.05%0.04%0.16%1.92%77.85%0.25%0.57%10,5272,429,000
Italy0.22%12.87%13.93%0.13%3.53%4.91%7.32%20.61%0.83%0.06%0.51%3.31%27.00%3.66%1.09%3,11529,380,000
Latvia0.00%7.81%4.17%0.00%2.08%4.69%11.98%12.50%0.00%21.88%4.69%17.19%10.42%1.04%1.56%192884,909
Lithuania0.12%10.82%6.90%0.00%2.38%2.73%15.93%11.53%0.00%15.70%3.45%17.84%9.39%1.90%1.31%8411,296,000
Luxembourg0.00%7.84%7.84%0.00%1.96%3.92%1.96%5.88%0.00%0.00%0.00%5.88%62.75%0.00%1.96%51308,720
Macedonia0.00%18.28%5.38%1.08%6.45%21.51%4.30%16.13%0.00%0.00%1.08%13.98%8.60%2.15%1.08%931,040,000
Moldova0.00%9.46%6.76%1.35%2.70%4.05%21.62%18.92%2.70%0.00%2.70%18.92%6.76%2.70%1.35%741,707,000
Montenegro0.00%18.48%4.35%0.00%7.61%22.83%1.09%6.52%1.09%3.26%0.00%7.61%27.17%0.00%0.00%92307,712
Netherlands0.00%4.85%4.94%0.26%21.53%7.91%1.62%5.02%0.00%0.34%1.53%3.15%46.47%1.36%1.02%1,1758,581,000
North. Ireland0.08%1.17%0.78%0.00%10.58%11.36%1.40%1.25%0.00%0.23%0.00%3.04%69.03%0.39%0.70%1,285928,149
Norway0.00%1.07%1.39%0.05%37.33%4.12%0.37%0.91%0.00%2.57%3.75%21.59%25.66%0.27%0.91%1,8672,685,000
Poland0.38%6.76%3.55%0.03%6.32%8.24%8.77%8.77%0.06%3.43%1.70%36.95%13.49%1.01%0.53%3,18018,380,000
Portugal0.00%12.77%7.02%0.23%4.83%5.18%5.41%10.36%0.35%0.23%0.35%1.50%47.30%4.03%0.46%8694,852,000
Romania0.21%12.95%6.79%0.64%5.73%10.19%14.01%18.90%0.21%1.27%2.12%10.83%12.10%2.76%1.27%4719,500,000
Russia2.69%3.56%7.37%0.06%3.81%4.07%11.95%18.03%2.14%13.52%2.44%20.90%6.13%0.85%2.48%5,08751,323,000(Euro)
Scotland0.10%1.54%0.98%0.08%12.21%7.81%0.63%1.90%0.04%0.05%0.16%5.18%68.39%0.16%0.78%7,6682,656,000
Serbia0.00%12.32%1.48%0.49%6.40%26.60%2.46%10.34%0.00%9.36%0.49%16.26%13.30%0.00%0.49%2033,393,000
Slovakia0.49%8.64%5.68%0.25%5.68%14.57%5.93%4.94%0.00%4.69%0.00%33.09%12.59%1.23%2.22%4052,661,000
Slovenia0.00%6.85%5.48%0.00%15.07%19.18%0.00%8.90%1.37%0.00%0.00%26.03%15.07%1.37%0.68%1461,039,000
Spain0.26%11.92%6.35%0.04%4.89%6.05%6.95%10.29%0.30%0.13%0.86%1.59%46.48%2.83%1.07%2,33223,010,000
Sweden0.00%1.38%2.40%0.05%44.67%3.37%0.10%0.91%0.05%7.44%4.13%14.31%20.89%0.05%0.23%3,8305,142,000
Switzerland0.00%7.14%12.05%0.26%11.42%9.18%1.21%6.38%0.89%0.13%0.77%3.25%45.03%0.96%1.34%1,5684,237,000
Turkey0.89%6.57%12.81%0.22%0.67%2.78%15.37%25.17%4.90%1.78%2.23%6.01%13.14%4.90%2.56%8980
Ukraine0.40%12.06%5.74%0.13%2.70%11.54%15.49%13.45%0.26%2.44%2.11%20.57%9.49%1.98%1.65%1,51719,460,000
Wales0.00%3.32%4.49%0.00%12.31%5.30%0.72%1.44%0.00%0.00%0.09%1.17%69.81%0.27%1.08%1,1131,547,000
Europe (based on pop sizes)0.54%7.73%6.59%0.13%9.64%7.89%6.39%10.88%0.64%3.61%1.25%11.92%29.94%1.47%1.39%340,818,110
Wow!

Family Tree DNA just released nice Y tools, which can be found here: https://discover.familytreedna.com/

The kind of statistics I calculated above may now be checked in one of the tools.
R1b-M343: https://discover.familytreedna.com/y-dna/R-M343/frequency
R1a-M420: https://discover.familytreedna.com/y-dna/R-M420/frequency
J2-M172: https://discover.familytreedna.com/y-dna/J-M172/frequency
J1-M267: https://discover.familytreedna.com/y-dna/J-M267/frequency
E-M96: https://discover.familytreedna.com/y-dna/E-M96/frequency
I1-M253: https://discover.familytreedna.com/y-dna/I-M253/frequency
I2-P215: https://discover.familytreedna.com/y-dna/I-P215/frequency
G-M201: https://discover.familytreedna.com/y-dna/G-M201/frequency
N-M231: https://discover.familytreedna.com/y-dna/N-M231/frequency
T-M184: https://discover.familytreedna.com/y-dna/T-M184/frequency
Q-M242: https://discover.familytreedna.com/y-dna/Q-M242/frequency
L-M20: https://discover.familytreedna.com/y-dna/L-M20/frequency
H-L901: https://discover.familytreedna.com/y-dna/H-L901/frequency
etc.

As expected, it works well for macro-haplogroups, but not so greatly for low level haplogroups, because there are many men just superficially tested in the database.

Another nice tool, and perhaps the most awaited, is the Age Estimate, built with the participation of I. McDonald.
Here's R-L2's, for example:

https://discover.familytreedna.com/y-dna/R-L2/scientific
 
Wow!
Family Tree DNA just released nice Y tools, which can be found here: https://discover.familytreedna.com/
The kind of statistics I calculated above may now be checked in one of the tools.
R1b-M343: https://discover.familytreedna.com/y-dna/R-M343/frequency
R1a-M420: https://discover.familytreedna.com/y-dna/R-M420/frequency
J2-M172: https://discover.familytreedna.com/y-dna/J-M172/frequency
J1-M267: https://discover.familytreedna.com/y-dna/J-M267/frequency
E-M96: https://discover.familytreedna.com/y-dna/E-M96/frequency
I1-M253: https://discover.familytreedna.com/y-dna/I-M253/frequency
I2-P215: https://discover.familytreedna.com/y-dna/I-P215/frequency
G-M201: https://discover.familytreedna.com/y-dna/G-M201/frequency
N-M231: https://discover.familytreedna.com/y-dna/N-M231/frequency
T-M184: https://discover.familytreedna.com/y-dna/T-M184/frequency
Q-M242: https://discover.familytreedna.com/y-dna/Q-M242/frequency
L-M20: https://discover.familytreedna.com/y-dna/L-M20/frequency
H-L901: https://discover.familytreedna.com/y-dna/H-L901/frequency
etc.
As expected, it works well for macro-haplogroups, but not so greatly for low level haplogroups, because there are many men just superficially tested in the database.
Another nice tool, and perhaps the most awaited, is the Age Estimate, built with the participation of I. McDonald.
Here's R-L2's, for example:

https://discover.familytreedna.com/y-dna/R-L2/scientific
pity it is not a straight count
frequency is erred due to pop numbers , which differ too much

as example ...............Portugal and Italy both have 4% of T ...............pop numbers clearly indicate that Italy has a majority ............an example why frequency is so so
 

The FTDNA’s block tree with my final branch was updated

oXNXzVb.png

ColK5r9.png
 

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