Ride faster, not harder

Have you ever Googled “How to ride my bike faster”? If you have, this one’s for you. If you were to raise your FTP by 10 Watts it might take you between 8 and 12 weeks depending on your level of experience and the quality of your training – but you can get 10 Watts faster overnight by paying more attention to your aerodynamics!

This blog is not one that’s about to tell you to simply spend £300 on uber chainwax or £1500 on a new front wheel but how you can train yourself to ride faster, not harder. This is our top 3 sessions on how to get faster at cycling, without getting fitter.

Getting faster doesn’t always have to mean an expensive trip to the Wind Tunnel – but even for those that find themselves sat at Silverstone, myWindsock is up on their laptops.

Top 3 sessions to ride faster, not harder

Session 1, the v:P maximiser

The aim of this session is to ride as fast as possible for as low an average power as you can. The goal is to maximise the ratio of v (velocity) to P (power). If you’re feeling extra fancy, you can “normalise” your score on this session by using the wImpact. In order to execute this session you take the following three steps…

  1. Pick a route with as few interruptions as you can reasonably find. In order to compare sessions and show improvement, you’ll need to repeat the session on the same route.
  2. Ride the route as fast as you possibly can, while going at a fixed average power (or choose an average speed target and try and ride as easily as possible).
  3. Analyse your ride in myWindsock, divide the ratio of your speed to power by the wImpact score and rank your rides. Hopefully you’ll see yourself improving over time.

You can improve your speed by playing around with where you use your power, holding experimental aerodynanmic positions while you ride or try out new kit!

Session 2, the Threshold Barber Chair

Maybe it’s just me, but I find getting a haircut extremely awkward as I’m forced to stare at myself in a mirror for half an hour. That’s why I called this session the threshold barber chair – as it requires doing threshold efforts with a mirror. The aim here is to prevent lazy position slipping throughout your TT.

  1. Plan to do your threshold session on the turbo and set up a mirror in front of the turbo.
  2. Do your intervals in the aero position (or holding an aero tuck if you’re on a road bike).
  3. Aim to keep yourself as small as possible throughout the efforts, using the mirror as a guide.

If you’re feeling extra committed, you can do this session indoors with your TT helmet on to optimise helmet and back interaction – but please keep in mind this could boil your head.

The yoga matt

This session isn’t really a session, more of a reminder. You’ll be able to hold your aero position more easily if you’re stronger. The main thing to do is, when you’re riding around in your most aerodynamic position – pay careful attention to what fatigues, aches and hurts. These are the areas you can focus on in the gym. It could be anything from hamstring flexibility to tricep strength and what to focus on will depend on your body and your position.

Getting faster and getting stronger are not the same thing. You measure your strength with your power meter but the most effective (and probably the most cost efficient) way to measure your ability to go fast is with a myWindsock subscription.

What makes a slow day?

We’re into hot day season, with a heatwave arriving in the UK it feels like a good time to talk about density. The density of the air is essentially “how many air particles exist in each metre cubed of air”. This is the cause of a day feeling slower than it should be. It’s usually the culprit of a windless, perfectly temperatured and otherwise faultless evening time trial being unreasonably slow for no reason.

Pressure and density are related, and if you’ve ever been on a trip away to the mountains, you might notice it on your weather trends plot…

As you can see, the density of air on my rides dropped off a cliff, right about the time I went to Andorra where I was staying at 1800m above sea level.

The maths

Density, pressure and temperature are all related to one another (and impact the power required to ride at a given speed). We’ll start with the relationship between the three…

Density is proportional to pressure and inversely proportional to temperature. Density drops when pressure drops and density drops when temperature rises.

The way to think of the difference between pressure and density is that pressure is the weight of the air above you (this changes with different weather systems and altitude) and density is the amount of air you need to push out of the way.

How does density impact our speed?

This the aerodynamic equation which explains how much power a rider needs to maintain a speed, v.

The power needed to ride at a given speed is directly proportional to the density (and thus pressure) of the air. On those days where you find your power numbers are high but speed is low for no reason, you can often blame the density. One thing you notice when you go up a mountain is how fast you start riding for low power which got me thinking, as density changes with altitude, is there a perfect altitude to maximise every speed?

Air density drops linearly as you go up a hill, which means the power needed to ride at a given speed does exactly the same…

It’s not that simple though

You’d think this was an argument for doing an hour record attempt on the moon (in fact, if you had a velodrome on the moon travelling at 60kph would only need about 9W) but obviously as the density of air decreases so does the oxygen available to our muscles to produce power. VO2 max doesn’t drop linearly though, it starts off decreasing slowly before a slightly faster drop (but the point at which the decrease in VO2 max breaks linearity varies from athlete to athlete).

An hour record is typically raced at around a riders’ LT2, so we’ll use that as a reference point.

The ideal altitude sits at where the gap between an athlete’s LT2 power and the air density is biggest, which will usually be just before their power drop becomes non linear. If I was preparing for an hour record (which I’m not), I would acclimatise myself to around 2500m in training and do a lactate ramp at progressively lower altitudes (or maybe just a straight up 60 minute TT effort on the turbo).

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This week’s blog was inspired by weather trends, you can view yours by signing up to myWindsock here.

Getting a prediction horribly wrong

Yesterday, we predicted a winning time of 42:54 in the Giro d’Italia stage 10 time trial. Ganna, unsurprisingly, won the stage but he did so in a time of 45:53, almost 3 minutes slower than we predicted the winner would go. In his daily vlog, Victor Campenaerts said to Ganna that Visma had predicted his time as quite a bit faster than he ended up going.

On the vlog, the pair of them were discussing the rough road surface, which can lead to around double the rolling resistance as we see on a smooth surface. Ganna was almost exactly 1km/hour slower than we predicted him to be.

How does rolling resistance actually work?

Diagram from Wikipedia

Rolling resistance is the force that slows a bicycle down as the tires roll over the road. A cyclist must continuously supply power to overcome this resistance, even at a constant speed. The main cause is that bicycle tires deform when they contact the road surface and the rougher the road surface, the more deformations there are. Tires are not perfectly elastic, so some energy is lost as heat instead of being fully returned and on a warm day, rolling resistance can actually increase significantly – especially as the road surface also heats up.

Because of this, riding on rough asphalt requires more power to maintain the same speed compared with smooth asphalt. For cyclists, smoother roads generally feel “faster” because less energy is wasted overcoming rolling resistance.

The power required to overcome rolling resistance is directly proportional to the bike-rider system mass multiplied by the speed of a rider – so the bigger and faster you are, the more this impacts you.

Making excuses

The winner of Stage 10 of the Giro, Ganna, is as big and fast as pro cyclists get. As a result, the unexpectedly rough roads will have had a larger absolute impact on him compared to other riders.

If you think you can do a better job of estimating your next time trial time, which you probably can, check out myWindsock here.

Giro d’Italia TT – predicting the winning time

We’re going to put our money where our mouth is and try to predict the winning time of the Giro d’Italia Stage 10 TT then, after the race we’ll take a look at how we did and what this means for the first Tour de France time trial. This blog will not predict who will win the race, simply how fast someone who wants to win might have to go. The second part, which we’ll write after the TT takes place, will use Jonas Vingegaard’s data to predict his time on the TT in stage 1 of the Tour de France this coming July.

One quick caveat, the GPX files available online (that we use to make the forecast) are not perfect and sometimes race day has the start ramp or finish line in a slightly different position to where the file starts and ends. This may only be a handful of seconds over the course but it can sometimes make our predictions look worse than they actually are.

A quick rundown of the course

It’s quite flat, we won’t be making much of the elevation in today’s blog and expect to see some 60+ tooth chainrings in the paddock.

Stage 10, which also opens the second week of racing, is the only time trial of this year’s Giro. It’s 40 kilometers from Viareggio to Massa (a good old fashioned 25 pretty much), bringing the race back toward Italy’s western coast and the Tyrrhenian Sea.

The route is pan-flat from start to finish, with no climbs at all, making it one for the specialists where the big engines should come to the fore. With a straightforward, largely non-technical coastal course, there’s nowhere to hide, and if the wind picks up along the shoreline, it could easily become a decisive factor in the overall standings.

The weather

It’s always a little bit risky talking about the weather with all forecasts subject to change, but seeing as a motorway bridge would look like a mountain on this course, it’s worth bringing up now as it’ll form the basis of our prediction. During the course of the day, the wImpact evolves from -3.9% to 1% for the final riders.

The wind speed is dropping throughout the time the GC contenders will be on course. The route is a forecasted tailwind point to point. If a TT specialist catches a fast pocket of time, the speeds will be obscene.

The winning time

World Tour cyclists have crazy power numbers, and those that want to are able to make themselves very aerodynamic. The question here is how fast will the fastest rider in the fastest conditions go on this course?

A central estimation for a generic TT specialist (no one in particular but someone with a great cda and a huge FTP) comes in at just below 56kph and a time of 42:54 for the course. Sub 43 is going to be needed to win this TT tomorrow.

With an expected winning speed of around 56kph, it’ll be interesting to see what Vingegaard does and how that translates onto the Tour de France course where he’ll face up to Pogacar and Seixas on day 1 in Barclona’s ITT!

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The physics of a Team Time Trial

If you’re allowed to share the work, why does a TTT feel so much harder than an individual time trial? This is, of course, dependent on the team. I’ve been in team time trials where I’m the strongest rider, and team time trials when I’ve been the weakest rider yet the hardest TTTs are always when you’re sharing the workload evenly. This is because, if you pace it right, you should come off the front of the group right on the limit of being able to get on the back, only then do you start recovering.

We can turn to academia for some insights as to why this is, though studying two or more riders in a line can be quite tricky (if you’ve ever been to a wind tunnel, you’ll know they’re not that big) so people who make these studies make these useful, but somewhat comical, little cycling figurines to make measurements.

We would like to thank the engineers from Eindhoven, Leuven and Liege for using models in myWindsock colours, presumably that was on purpose. If you’re interested in reading the paper in its raw form you can do so here.

The study we’ll use to look into the physics of a TTT, in order to try and figure out why they’re so hard, looked into where in the line drag changes, the impact on spacing between riders as well as how the number of riders can make an impact. The cyclists in the study were scaled models of a 183cm tall with a bodyweight of 72kg.

These are the measured, and calculated, drag values for a pace-line of four riders with a spacing of 15cm between each rider. The drag force slightly reduces from the second rider to the fourth though it’s hard to say whether or not you’d really feel this difference as a rider.
Seeing as it’s actually really hard to ride 15cm from the rider in front, for most riders, we’ll use the drag values for riders that are riding 50cm apart, a slightly more realistic distance for amateurs.

Those of you with a sharp eye will notice the rider at the front gets a slight reduction in drag force too. When two or more cyclists ride in a line, the front rider experiences a small reduction in aerodynamic drag because the riders behind slightly modify and stabilise the airflow in their wake, reducing the pressure difference behind them.

We know a rider in a 4-up TT experiences on average, 65.7% (let’s say 65% for simplicity from now) of the drag force and thus, their average cda over the ride is reduced by the same amount and, as such, they’ll travel at a much higher speed for less power. There are two moments during the TTT where every rider has to hold their speed or accelerate without any meaningful assistance though, while their on the front and while they’re drifting back.

In order to return to the back of the pace-line, it’s necessary for there to be a difference in speed between the rider peeling off and the rest of the group and that speed must be made up for with an acceleration in order to ‘get back on’ as the group passes. As you may remember from school, Isaac Newton’s second law tells us that the force required to produce an acceleration is proportional to the mass of the rider multiplied by that acceleration.

This acceleration is actually the reason team time trials feel so hard, this requires some depletion of a riders’ anaerobic capacity in order to produce enough power to make up that speed difference.

If you’re setting a forecast for your TTT, you can model how fast the team will go by using a cda that’s 65% (in the case of a 4-up TTT) of your usual value, so if your personal cda is 0.23 you can use 0.15 to calculate the speed that you might travel. If you agree the power you’ll ride on the front with your teammates beforehand, you’ll be able to use myWindsock to assess what’s possible.

Don’t believe the forecast

When planning my week, I used to use my Apple weather app to decide which days I’ll ride inside vs outside yet increasingly, as winter turns to spring, I find myself sat on the turbo looking out the window at a sunny day. This is the result of weather forecasts being weighted toward pessimism. If you don’t pack your kagool on a day with a 40% chance of rain, you’ll blame the weather forecaster – if you pack it and don’t need it, you’ll think you got lucky. This asymmetry means the weather app is incentivised to tell you it’s going to rain, even when it might not.

This is my phone’s assessment of the weather today with a 10% chance of rain. It has been bright sunshine all day where I’m writing from with a couple of fluffy clouds in the sky.

This is the season for moderate chances of rain, but your weather app will always tell you it’s definitely going to rain with those odds.

How do weather forecasts work, and why are they often wrong for cycling?

When you check the weather now, it’s easy to forget just how much machinery sits behind that little icon on your phone. It feels like a simple guess, sun, cloud or rain. In reality it’s built on a constant stream of data being gathered from all over the world. On the ground, weather stations quietly measure temperature, wind, and pressure throughout the day, many of them run by organisations like the Met Office. At the same time, weather balloons are drifting up through the atmosphere, sending back snapshots of conditions far above where we live.

Further out, satellites operated by groups such as NASA and the European Space Agency are watching entire weather systems unfold, tracking clouds as they build and move across continents and oceans. Closer to home, radar systems are scanning the skies to see exactly where rain is falling and how fast it’s approaching. Even planes and ships chip in, feeding back data from places that would otherwise be blank spots on the map.

All of this information is pulled together and fed into powerful computer models that try to simulate what the atmosphere will do next. These models don’t produce a single answer, they produce a range of possible outcomes, each with its own probability. That’s where the uncertainty creeps in, and where the forecast you see becomes less of a certainty and more of a carefully weighted judgement.

By the time it reaches your phone, what looks like a simple prediction is really the end result of a global system trying to make sense of an atmosphere that is constantly shifting and, at times, stubbornly unpredictable. Here’s the thing though, the weather apps are drawing conclusions from these models to help people get dressed for a morning on the high street, not for a 4 hour bike ride.

That’s ok though, because we have access to this weather data as well, and we put it all in one place for you…

myWindsock will give you an objective assessment of the weather, we’re incentivised by accuracy – not your wardrobe choices. Most weather apps optimise for simplicity and caution. myWindsock focuses on accuracy, timing, and conditions that actually affect performance on the bike.

So, when you’re preparing for a ride or race, the Met Office app or Apple Weather isn’t going to cut it.

Sign up to myWindsock here.

How to make the most of a club time trial

Club TTs are a fun affair. Collecting numbers out the back of someone’s car, pinning each other in a freezing cold car park, handing over cash and lining up in a lay-by. To the uninitiated, it could look a bit odd. Recently, there was a club TT in my village so I can attest to this as my dad looked extremely confused holding my coat before I started. I have heard riders complain about the futility of club events, saying they’re pointless. I couldn’t disagree more. This is an instruction guide about how you can make the most out of your next club TT.

This is me heading off for my club 10 on Saturday, laughing as the time keeper counted down and then forgot to say go!

Do it on your training set up, do it tired

Lots of riders turned up to this race on a training set up, I did my Sunday ride before the TT and headed over after 4 hours on the bike and a couple of other riders were doing similar. Some riders may view this as doing a race by half measure, the antithesis of the approach taken by many time trialists but there’s two main advantages:

  • Reduce your pre race admin

Time Trials are an administratively heavy form of cycling, but not a club TT. Just roll up on your training wheels and bash round as fast as you can. Rough and ready!

  • Race under fatigue

If you’re like me and prefer a longer time trial to a ten, doing a ten mile TT at the end of a longer ride is a great training session to work on that durability for the 50 and 100 mile races later in the year.

Collect data

A club TT is a good opportunity to try race pace, in position, going similar speeds to what you might in an event that you’re targeting.

This section, taken from the back straight and as you can see from the wImpact it was into a headwind, will form the basis of our analysis. The reason I’ve taken this section of course is that it was the only part of the course that was unencumbered by the state of the road and sharp corners. It was a pretty flat, straight road with a decent enough surface.

From the above section we can see that my cda is 0.239, now let’s imagine a rider with these numbers has a desire to ride sub 20 minutes for a 10 mile TT this year. Using these numbers, plus a little creative accounting for a disc wheel and a race chain (let’s imagine our race set up is 5% faster so our 0.239 goes to 0.227) we can see how it’ll look on a course that’s being used as an open 10 this coming weekend.

myWindsock allows us to upload courses from CTT directly into the forecast.

For this demonstration, I’ve chosen the West Kent Open 10 course, the Q10/24. Using my numbers from the club TT, I would be able to ride a 21:05 on this course.

From this we can see I’m a minute off with my numbers, I either need to train harder or take a trip to the wind tunnel and find some gains.

I should adjust my expectations a little and aim instead for sub 21 minutes rather than sub 20. However, we forgot to add the race kit and adjust our cda to our new estimate of 0.227. Let’s see what happens to the new estimate? Any chance of sub 20?

We’re getting closer, but that extra 44s is a lot to ask.

This gives us an adjusted expectation to go into the next race with, however, and it all came directly from the calculations based off the club 10 that we took part in. We made the most of the club 10, and when I’m 30-45s off my target pace at the open I won’t be too upset as I had a great idea of where I was at thanks to the information collected from the club TT.

Lesson here: Sign up to your local club TT!

Be prepared for your next time trial with myWindsock.

The early season time trials

They’re often cold, statistically windy and most definitely slow (according to the laws of physics) – so why on earth should anyone do an early season time trial? Well, there are many reasons it’s worth embracing a slow time and a cold morning and this blog will talk you through them. Here in the UK, we have CTT and their listings of early season club TTs are substantial. There’s probably two or three viable options for every rider in the UK each weekend and it’s nice to see some strength in British bike racing.

You can find an event here.

The benefits of an early season TT are…

  • They help you gather information on how your winter training has gone
  • You gain some performance data to help you prepare for bigger goals
  • It’s a good chance for a win

Early season TTs are a great test of form. You can see how your power goes down on the road, in the TT bars which is something you can’t achieve in a Zwift race. There’s a level of satisfaction achieved from a power PB on the A4 that one can’t achieve in Watopia. Getting power out on the road is not the same as indoors either, and it’s vital to ensure your indoor numbers translate outside before big late season goals come round.

They can also act as fantastic training sessions in their own right, doing a club time trial as part of a longer ride can break up the long ride and be a great replacement for some otherwise slightly boring intervals. For me, they allow me to get a little bit more out myself than I’d be able to achieve from just chasing power numbers with an added element of specificity.

We know that early season time trials are slower and there’s a physics based reason for this. Drag force is directly proportional to the density of air.

When the temperature drops, the air molecules have less energy which means they float around a bit slower. This means, in any given imaginary box of air, there’s more air particles in it as each individual particle takes up less space over time (as it moves slower than if it was warmer). As such, a cyclist on a cold day literally has to push more air out of their way than on a warm day.

This simple bit of physics shouldn’t put us off though, as we can rearrange this nice equation and replace the air density with “summer numbers” after the race to calculate our “fast day equivalent” time (or just use myWindsock, of course). We can also dial in equipment choices from our winter’s aero tests, be they in the mirror on the turbo or at Silverstone.

These early season time trials are a great opportunity to achieve some finish positions not usually attainable at the slightly more competitive mid summer TTs when all the hitters finally come out of their shed. Whether it’s an age group result, a top 10 or a win that you’re gunning for an early season time trial can have a softer field which never hurts morale heading toward summer. As well as the reasons we laid out, we asked CTT’s new chair, Tim Smith, if he had any ideas. He mentioned to us that it’s a great opportunity for riders to ‘see friends they may not have seen over winter’ as well as bringing up the raw love of racing that many time trialists share – a great reason to do any race.

If you want to prepare as well as you possibly can for early season races, sign up to myWindsock here. You can find a TT event to race in here.

Milan – San Remo 2026

The 2026 edition of the men’s and woman’s MSR is taking place this weekend and while everyone is wondering who will win the direction of the wind has caught our eye here at myWindsock HQ. Of course, we pay more attention to this sort of thing than the cycling journalists typically do who are often caught up checking the form book from previous races at this point in time.

The nice thing about forecasting this race is that you can ignore everything up until the final 27km, when it all kicks off. In the past couple of editions of the men’s race, UAE have gone to the front into the foot of the Cipressa and launched an attack. As mentioned on the GCN race preview, the last 27km of the race was ridden at around 47kph last year by Ganna who ended up finishing second after UAE split the race on the Poggio.

As things stand, the wind forecast for the final 27km is a strong headwind.

The forecast for the pair of climbs does not suit an early attack going, or sticking if it does go. A headwind changes the aerodynamic calculus for any attacking rider. If a rider attacks with a tailwind and gets clear of the peloton they benefit from the fact that the bunch behind them must now chase through the same air the attacker is moving through, meaning the peloton’s size advantage in sharing the workload is somewhat offset.

A rider doing 50kph into a 20kph headwind, however, is fighting 70kph of effective airspeed, meaning aerodynamic drag, which is proportional to the square of that figure, becomes enormous. The peloton behind, sharing the load between dozens of riders. Headwind solo attacks rarely work – even Pogacar can’t defy physics.

This is the wind forecast at the time of writing.

The wind speed forecasted at the final 27km of this race is around 15kph, with gusts around 20kph. This is not particularly strong if you’re stood still, however for a solo rider it turns a 45kph solo raid into the equivalent of 60kph in still air.

The wind forecast for the final 27km of Milan – San Remo can be seen here. If you want to see specific sectors like the Poggio or Cipressa climbs individually, you can “star” the segments on Strava and see them straight in your myWindsock account.

Sign up to myWindsock here.

What is yaw angle?

As you ride, both wind speed and wind direction shift relative to you, meaning one of the key factors in aerodynamics—the yaw angle—rarely stays consistent for long. Despite this, manufacturers often claim they have optimised their designs for particular yaw angle ranges. Some even argue that certain tube and rim shapes can behave like sails, helping to push the bike forward when the wind strikes from the right angle. Data from myWindsock shows us that over most rides, races or training, that yaw angle changes constantly. We thought we’d write a blog that tells you what Yaw angle is and how it can impact your aerodynamics.

Data from a recent ride uploaded to myWindsock shows how we detect yaw angle changing over the course of a ride, it’s extremely variable for typical cycling speeds. Local topology and directional changes both play a role in the yaw angle experienced by a rider.

What is Yaw Angle?

In cycling aerodynamics, yaw angle is the angle between the rider’s direction of travel and the apparent wind (the vector sum of the rider’s forward speed and the true wind). A yaw angle of 0° means the wind hits the rider directly head-on, while higher positive or negative yaw angles occur when crosswinds shift the apparent wind sideways relative to the bike’s path. That is to say “what direction does it feel like the wind is coming from relative to my direction of motion?”.

This diagram shows that yaw angle is the “average direction” of the wind felt.

In this blog we wrote a little about the idea of “yaw dependent” cda, that is to say that your aerodynamic properties are dependent on the angle the wind comes from.

This graph shows CdA (the measure of how aerodynamic you are) as a function of yaw angle taken from wind tunnel data. It shows that, at different speeds, yaw angle can highly impact CdA.

How does all this impact my forecasts?

It’s early TT season as we write this and while this is a difficult time to get new PBs, it’s a great time of year for data gathering. One useful piece of information you can gain from this time of year is how the wind can impact your cda and while obtaining granular yaw dependent cda is tricky, but not impossible, with myWindsock you can very easily get an idea of whether you’re particularly “un-aerodynamic” on windy days.

This will help improve the accuracy of your forecasts which will allow you to preserve your biggest performances for days when a PB is more likely.

Sign up to myWindsock here.