This is a continued discussion from this thread, where I showed proof of discrepancies on ZwiftPower between cat A on the one hand and cat B-D on the other with regards to race effort. Later on we also found funny things about rider weight.

To sum up the thread, I showed that:

-Cat A winners work harder than the rest of the podium

-Cat B-D winners work less hard than the rest of the podium

-The difference is not random

-The results suggests strong presence of cruising in cat B-D but not in A (where you can’t cruise)

I also showed that:

-Cat C podium winners weigh more than other race participants in races in general

-The difference is not random

The above differences, I argued, are caused by the current W/kg category system that gives advantages to:

a) Sandbaggers (cheaters)

b) Cruisers (cheaters)

c) Relatively heavy riders (not cheaters)

The reasons why the W/kg cat system gives unfair advantages to sandbaggers, cruisers and relatively heavy riders is because of its unique and ill-chosen features compared to category/division systems in basically any other sport, specifically it’s caused by:

i) No category enforcement

ii) Past race Watts determine category rather than past race results

iii) A *performance ceiling* in cat B-D that will lead to DQ *in* a race if reached

I also argued there is a **Light Rider’s Curse**, i.e. that there is a tendency for light riders to sooner get upgraded rather than get anywhere near a podium in cat B-D. You reach the top of your category in terms of W/kg, you still lose, and then you get upgraded to the bottom of the next category.

Why would that be? Let’s theorycraft. It’s because someone doing 300W is going faster on the flat than someone doing 275W.

*“Duuuhh, of course he is! So what?”*

Well, what if it’s a cat C race and the guy doing 300W weighs 94 kg? That’s 3.19 W/kg. And what if the guy doing 275W weighs 77 kg? That’s 3.57 W/kg. See the problem?

The heavy guy wins the race and the light guy isn’t anywhere near a podium but is still a disgusting sandbagger who deserves a DQ. But this never happens in real-world cycling, only in Zwift. And it’s because of the W/kg cat system that no other sport uses.

So *in theory* our cat system gives an unfair advantage to a heavier rider. I also showed with *data* that this is indeed so, looking at averages over a mix of races including not only flat races but also hilly races and even some races with tough climbs.

*“But what if there are alternative explanations? What if the winners are just smarter and race better?”*

So the heavier riders would have extra brain cells that the others don’t? Like… in the love handles?

*“Ok, maybe not exactly smarter in general. But what if the winners simply draft better or were just lucky to be in draft more than the others for whatever reason?”*

It’s a fair question, I think. @Paul_Smith_1948_HERD came with a suggestion:

Maybe a separate dataset for ITTs? That would eliminate the effects of drafting.

So I did a new study. 40 iTT races in cat C taken from yesterday and backwards in time according to ZP. What were the average weights for the podium vs the rest of the field? Was there a difference? And was it statistically significant (i.e. not random)?

**Results for iTT’s in cat C**

Podium avg weight: 83.9 kg

Losers avg weight: 78.1 kg

Difference: 5.8 kg

Statistical significance: p=0.00004 (probability of a random sample/event resulting in such a difference)

Conclusion: The difference is *not* random. In fact, a pharma company doing a study on a new promising medication would do wheelies and bring out the champagne if getting results of this magnitude. So heavier riders do have an advantage in cat C, even in iTT’s where there is no draft.

*“Ok, but maybe this is exclusive to cat C. I don’t care about the fat noobs in cat C anyway. I race in B.”*

So let’s look at cat B too.

**Results for iTT’s in cat B**

Podium avg weight: 77.7 kg

Losers avg weight: 73.0 kg

Difference: 4.7 kg

Statistical significance: p=0.00007

Conclusion: The difference is *not* random. We can see that people weigh less in cat B, just as I predicted in this blog post btw, but there is still a clear advantage for the relatively heavier rider, even without draft.

*“Uh-oh… and you mean the reason for this is that both cat C and cat B have a performance ceiling (3.2 W/kg and 4.0 W/kg) that will weed out lighter riders trying to match the speed of heavier riders?”*

Exactly!

*“A-ha! Gotcha! But cat A doesn’t have a performance ceiling! So if their iTT winners are heavier than the losers too, then your argument implodes!”*

Yes, you’re right. It would. We’d have to come up with some other explanation for the differences. Not that I can think of any. But let’s worry about that later. First let’s look at cat A the same way. If we see the same difference, then I’m in trouble. However, if we *don’t* see the same difference… then the W/kg cat system is in trouble. If I lose, I’ll go jump off a bridge. If the W/kg cat system loses then… it can go jump off a bridge.

**Results for iTT’s in cat A**

Podium avg weight: 68.8 kg

Losers avg weight: 69.9 kg

Difference: -1.1 kg

Statistical significance: p=0.18

Conclusion: There is a small difference, but it’s pointing in the other direction and it is quite possibly just random. We’d get a difference like this almost every 1 in 5 samples from the ZP database. So we conclude that there is *no difference* in weights between podiums and losers in cat A iTT’s. Neither heavier nor lighter riders have an unfair advantage in cat A.

Q.E.D. The Light Rider’s Curse is real. Now where’s that bridge? I’ll take you there.

I have tried. I have really tried. But I can’t think of anything positive to say about the W/kg cat system whatsoever. It just sucks any way you look at it.