From the science of sport:
At some point, the off-score gets so high, it is strongly indicative of doping (the 1 in 100, 1 in 1000 thing). For example, Shobhukova had an off-score of 153 (yikes). The off-score can also be so low that it suggests doping, and these “cut-offs†or limits are known.
Radcliffe’s values (115, 110 & 109) lie either just below (2) or just above (1) the off-score upper limit WHEN TAKING ALTITUDE INTO ACCOUNT.
That is, there is a different ‘cut-off’ to deal with altitude cases, because altitude is known to affect the blood. So a normal cut-off of 103 is increased to accommodate this recognized possibility/explanation.
Anyway, the point is that Radcliffe is NOT a Shobhukova type example, though her numbers are still high.
Where it gets tricky, however, is that off-score values are ONLY PART of the picture, which is why releasing 3 off-scores is not conclusive of anything, even if they are close to those cut-off limits.
That’s because the whole premise of the passport is to measure CHANGE over time, and so a value can be “normal†and thus not flagged by itself, but when that value is looked at relative to others, it may be marked anyway.
Because of this, a ‘spot’ off-score of 100 might be more suspicious than a value of 110, if the preceding values were 70 vs 105, respectively. The biological passport software does have an adaptive component that works out a sequence score, but we’re dealing here with “spot†off-scores.
Perhaps even more importantly, it helps to know how that off-score is generated – you can produce the same off-score with different combinations of Hb & Ret% (which would, in theory, allow you to mask doping by manipulating half the equation to hide the other half), so really, isolated off-scores tell you nothing other than you’re not dealing with Shobukhova-level doping here!
In fact, off-score alone is like power output in cycling. At some point, it’s so high it screams DOPER. But when lower, it doesn’t prove non-doper, and you instead need to appreciate the nuance. So only releasing part of the data seems to be to actually obscure that, which is ironic because it makes this issue so much MORE DIFFICULT to understand (which was Radcliffe’s justification for keeping it out of the public eye in the first place).
All the facts – easy! Half the facts – impossible!
What would help to test each of Radcliffe’s explanations (altitude, illness, hydration) is the specific values (Hb & Ret%), not just an off-score, and to do so over a longer period.
Each of her explanations is a hypothesis (“Dehydration after running in the heat has increased my Hb concentration and triggered a high off scoreâ€, for instance. Or “A period of altitude training has elevated my Hb and suppressed Ret production to produce a high Off-scoreâ€).
These “hypotheses†are entirely testable, and if they pass the test, believable, and on top of it all, she’d be playing open cards, which is worth a great deal in the climate of mistrust.
I still feel that her explanations are POSSIBLE, and complete data would make them PLAUSIBLE, and that equals trust. But the half-truths & opaqueness make it less plausible, at least to me (opinion). It’s the ACTION, not necessarily the data, that speaks loudest.