In the 2011 study, the authors used two measures:
M1, minimal estimates without any assumptions on the doping method
M2, estimates obtained assuming doping with rEPO microdoses
Only M1 was called minimal. Both measures produced 12% for male samples. (Maybe 15%-16% if we consider endurance males only.)
And yet, M2 was sometimes lower, and sometimes higher than the "minimal estimate" M1. Strange...
In any case, you are still not recognizing the elephant in the room:
Contrary to the Tuebingen study, the authors of the IAAF study thought the prevalence would be even lower for athletes: "Nonrandom sampling among athletes makes the prevalence in populations of samples higher than the prevalence in populations of individuals."
Well yes, fine, but I was not comparing the minimal estimate from the samples to the minimal estimate for the athletes, but to the real doping prevalence. As pointed out before, the real prevalence is a lot higher because all the dopers not pushing their Hb beyond the threshold remain unflagged here.
Referring to the example in the introduction to use same real numbers:
"If a blood sample is collected from 200 of these athletes, between 1 and 9 of them (4 on average) should present a value higher than 164 g/L. If 30 of these athletes presented a value higher than 164 g/L, then between 21 (11%) and 29 (15%) presented a value that was too high."
So anyone doping from 150 to 160 g/L (to use their units) would not count as a doper here. Anyone not tested while going from 150 to 170 g/L (e.g., because of poor OOC testing in Kenya at the time, or because of a quiet doorbell) would not count here either.
And exactly that is the main problem of the ABP (aside from the demonstrated corruption), as demonstrated in the Ashenden Eur J Appl Physiol 2011 paper, where the athletes doped - unflagged - from an average of 155 to 164 g/L.
If "Ashenden told us that athletes played a cat-and-mouse game with blood values. This means that the low values post-2007 likely do not reflect true blood doping prevalence." is correct, then it is also correct that we cannot determine the true prevalence of either cycling, or running, post-2007 (or for any year for that matter), unless we know to which extent the various athletes from the different sports played cat and mouse.
Finally. We only know that the real numbers are significantly higher.
Oh, and running was also worse than cycling in 2001 and 2002 (about 18 to 12%), before the cat-and-mouse games began.
Btw, Kiprop and Jeptoo got away with their blood manipulations for quite a while before slipping up. So did Poistogova etc. That happened also to Ullrich and Landis, and Armstrong actually, so there is a comparable amount of sophistication from that point of view.