Zwiftcruiser

I was wreaking havoc on the official Zwift forum recently in the wake of this little study . A question that kept resurfacing in the discussion was whether it is really reasonable to assume that you can detect cheating (cruising) from just looking at a HR distribution chart. Coming from the outside it may indeed seem like a fair question. I would, however, like to argue that it is not, that you are missing the point. The point is that cruising is the HR distribution graph. You can't really detect it any other way, not even in theory. In fact, you can't really define it any other way. I will try to explain. But first one of those mandatory detours that come with this blog. I thought we would start off with discussing dead celebrities. Let's leave the boring Club 27 out of the picture for a change. But do you know who Borg was? No no, not that Borg. I am referring to Gunnar Borg, PhD MD and former Swedish professor in psychology.  I saw him in person a few times while he was

  3R Volcano Climb Race (D) - 29 Aug 2020 I should lay low, waiting for the cat downgrade by next month's end, now that I already have a nice triplet of sub-2.5 races in the ZP race records. But I just couldn't help myself. I had to cheat a little more today and picked this shortish race. It seemed ideal. I chalked it up as honing my cheating skills. The start was hard. A few D's joined up with some C's in a D front group that I decided quickly not to try to go with. I went with the second group instead the initial km's, but we actually caught up with the front group in the underwater tunnel and stuck with them.  I was monitoring my Watts in the Wahoo Fitness app closely of course, and some 12 min into the race the group was still pushing 3.0-3.2 and my average W was by then dangerously high, well above 200W. At 68 kg plus another 7 kg of belly fat, I had only 8 min to get the average down to 185W, my mark to be on the safe side. I dropped and just spun the legs for

Can you hear the rumbling, people? It may have seemed distant before, but it is creeping closer and closer for every day. Bad omens in the sky. Seals being broken one by one.  And on the crumbling tarmac on top of the ZwiftPower bunker an armada of belligerent racers roll in, complaining over massive cheating in Off the MAAP Tour and elsewhere, riders racing fair attacking cheaters in the race chat. Let's face it, the W/kg categories are falling apart. This is not the end of the beginning. This is the beginning of the end. The Apocalypse, Ragnarok, the Untergang. And from the ashes a Phoenix will rise.

Summer vacation drew to a close and now I'm in the city again with days that grow shorter and over 30 min to get to roads even remotely worth riding. And so I'm back in Zwift on weekdays. Time for some cheating! I noticed that my last little screwup in a race was 1 Jul. Well, it wasn't even a race but an official group ride and ZP picked it up. I got caught on the Watopia PD speed camera doing 2.8 W/kg. But I have served my sentence on 1 Oct. Or should have. We'll see, because my current 90 day top 3 average doesn't actually correspond to activities I have participated in. But anyway, I thought I'd prepare for an autumn of intense, relentless cheating. And for that I need a "legitimate" downgrade. Thus I needed two more races staying within cat D limits. Filler race no 1 First was the Namibian Race League of 23 Aug. I had just recovered from an infection with fever the day before. Not covid this time but bad enough to call in sick. Safe to say, I was i

We turn again to our investigations of ZwiftPower race data. In the second of the recent Cruiser Sunday posts I discussed briefly whether the spotted difference between cat A and cat C with regards to relative effort levels among top contenders was statistically significant. Now we will try to analyze race data properly, with a third approach. An explanatory sidetrack We will start with a little loop before we get back on track. Imagine you have kids and that you recently moved to a new area. There are two nearby schools to put your kids in and you have the choice between either and want to choose the one where the students have the highest grades. Is there a difference at all, and if there is, can we somehow determine whether that difference is not just random? Or let's make it really simple. You and a friend throw dice. You roll a die 100 times each. The objective is to score the highest total. If the dice are fair, then there should be no difference between your results, right?

  In the last blog post I tried to show that the majority of races in Zwift and on ZwiftPower seem to be won by riders making a smaller effort than riders coming in behind. As you may have had objections to the methodology, I made new little study which I think you will find more methodologically sound. Method I went through all races in cat C starting from the strike of midnight between the 16th and the 17th of Aug 2020, working myself backwards until I had had a look at 100 eligible races. Again, a lot of races had to be discarded due to low attendance or due to a missing link on ZP to the Zwift rider profile page for the race in question. This time I chose to look at the winner in comparison to the no 4 guy, the guy who didn't quite make it to the podium. Did any of these riders, winners vs 1st losers, on average, seem to make less of an effort than the others? Effort here is defined as a higher workload in terms of HR distribution over the race. A rider who spends more time in

As a follow-up to the last couple of posts about cruising and the weird effort limits the W/kg category system imposes on us, I decided to do a little pseudo-scientific study of the racing in Zwift. Previously I have claimed that the W/kg system favors making less effort than competitors in a race, if the objective is to win. If you haven't read the last couple of posts (you should read all of them), then you might ask yourself, how does that make sense? That couldn't possibly be right, could it? All else equal, sports are won by people making more effort than their competitors, isn't that so? And the awful truth is that, yes, in all sports except Zwift this is indeed so. But Zwift is different, I have claimed, since it has a uniquely weird categorization that imposes an upper limit to your power output in categories B-D - regardless of your perceived effort, I might add. This would then mean, if I am right, that ideally, if you are set on winning races in Zwift, you would

The other day I posted a reply to a thread on the Zwift forum. If you didn't get the point of the previous blog post, the one about Ethics in Zwift, then maybe my reply can serve as a clarification. So I thought I would repost it here. As usual, I don't want to expose names. (Dig yourself if you must.) Names are not interesting, at all. Nothing of the problems with Zwift racing that I write about has anything to do with individual subscribers anyway. Rather, I cover a system that is falling apart because it was flawed to begin with. And it is this system that creates cheating by promoting it. And if this system creates a whole bunch of cheaters, it also creates ten times as many weird and unfair situations in races on a daily basis even though it can't be classified as cheating. Anyway, a guy in cat B despairs after a race and decides to seek advice from the forum. And I would guess this isn't the first time he despairs. Nor the last. It was probably just the average ra