Armstronglivs wrote:
After one sentence I realised I had no need to read the rest of your comments. You are unable to provide the name of a single distance runner whom you consider has doped without failing a doping test. Dopers - who number in their thousands - are literally invisible to you.
Not reading things is a good explanation for why you are so poorly informed. You made up your mind way back in the 1970s, when you were naive and impressionable, and for 50 years, you have become increasingly prepared to listen to whatever confirms the bias of your friends in high places.
As I said earlier, I cannot draw specific conclusions without specific data.
If I did, I would also call it speculation, and faith based conclusion with scarce evidence.
Somehow you see this as a fault, because I have not adopted your intellectually defective process.
The dopers are there, but the 1 in 3 (or 1 in 7 blood) dopers are camouflaged by the 2 in 3 (or 6 in 7) non-dopers.
If we have aggregated prevalence data, by its nature, we cannot extract names from an anonymized population.
Lacking any showing of a trend correlating performance with doping, I cannot assume the best performances are over-represented with dopers as a function of performance.
I have argued the opposite: although champions dope, it is the more numerous, less performant masses behind them who have more incentive to dope, to achieve some qualifier, or get a contract, or break into the winners circle, or onto the podium, and they have less to lose.
By data, we can include confirmed positives, but also confessions, first-hand witness testimony, evidence collected in detailed investigations, such as receipts, laptop records, lab data, etc.
Are you sure that doping long distance runners number in the thousands, among the all-time fastest performers? "Thousands" in the plural suggests at least 2. I think you tend to throw out whatever numbers suit you, and tend to inflate them without a real understanding.
Here are some of my conclusions (and some speculation for the women) from my performance data stats:
1) Relative to 1990 world best reference (top-5 average) (28 of the last 30 years during the EPO-era):
- 403 men worldwide ran faster than the 1990 world best reference (average top-5), across 6 distance events ranging from 1500m to the marathon, between 1990-2018.
- If we assume 1 in 3 are dopers, that makes 121 men dopers over 28 years
- I did not count the women, but would estimate 200 women running faster than a strong 1500m reference, and weak 5000m, 10000m, and marathon references.
- If we assume half of them are doped, that makes 100 women.
- If we assume 1000s of dopers, than ~220 have run faster than a 1990s world best reference (doped or not doped), and the rest are some 1800 or many more slower performing "no-name" athletes.
2) Athletes appearing in all time performances list (at alltime-athletics website extracted Jan. 2019, dating back to 1960s):
- 1500m: 959 men worldwide (251 East Africans, 95 North Africans, and 613 from the rest of the world)
- 5000m: 1296 men worldwide (579 East Africans, 92 North Africans, and 625 from the rest of the world)
- Marathon: 1124 men worldwide (766 East Africans, 34 North Africans, and 324 from the rest of the world)
So when we look at men's all time best performances, dating back to the 1960s, assuming 1 in 3 dopers, combining all events and de-duplicating athletes, 600 dopers among the all-time best performances is probably a reasonable conservative estimate.
Factoring in women (I did not count these statistics for women) would consider that: for cultural reasons, fewer women ran over this period, and steroids and testosterone and male hormones give women unnatural strength and muscular power for the shorter distance events.
If we assume half for women, similar to my estimate from post-1990), this would make +/- 1000 dopers all time for events from 1500m to the marathon, appearing on all time lists dating back to the 1960s.
You might think a 1 in 3 is not reasonable for pre-WADA performances, especially in the steroid era of the '70s and '80s, but before 1990, the all-time quantity of quality athletes is much lower.
Of course to arrive at "thousands" you can:
- add more events (e.g. 400m and 800m and race-walking),
- lower the threshold of top performances to include many more inferior "no-name" athletes, or
- increase your assumption of distance running doping prevalence