Zwift is a big thing to wrap your head around, especially if you’re new to cycling. First, you’ve got the hardware side of things: what do I need to own in terms of a bike and smart trainer? What computer should I use to run Zwift? And let’s not even start talking about fans, rocker plates, and trainer tables…

Secondly, once you’ve got your hardware up and running, you have to decide what to actually do in Zwift’s virtual world.

That’s what this post is all about. I aim to give you an overview of the sorts of activities you can do in Zwift, and a bit of guidance to help you maximize your enjoyment of each.

My Resume

How am I qualified to be your tour guide for all things Zwift? Here’s a bit about me:

• I joined Zwift in November of 2015
• Since then I’ve completed over 1100 races and ridden nearly 90,000 kilometers on the platform
• I’m at level 100 (the highest level Zwift currently has)
• I’ve also led many group rides, and ridden in lots more
• Most importantly, I’ve burned 5,922 slices of pizza while Zwifting

I’m also a Zwift superfan, having built this Zwift Insider website and published over 4500 articles to date covering all things Zwift.

Why have I done all this? Because I know from experience that Zwift is a special place where cyclists can make positive connections and receive motivation to achieve their goals.

With that out of the way, let’s begin. I group riding activities on Zwift into four broad categories: Exploring, Social Riding, Racing, and Structured Training. We’ll look at each one in turn.

Exploring

Zwift has 12 unique maps/worlds containing hundreds of kilometers of virtual tarmac. There are lots of different ways to ride these virtual roads, which leads to nearly 250 different routes spread across Zwift’s maps!

Browse the Master List of All Zwift Routes >

The most common thing people do on Zwift is simply ride various routes. Explore the different worlds. See all sites, and as fitness and time allow, conquer the biggest climbs and longest routes.

Nearly all routes in Zwift have an achievement badge which you earn the first time you complete the route. That badge comes with an XP bonus roughly worth the amount of XP you would get when riding the route, which means you effectively double your XP the first time you ride each route in Zwift.

If you’re looking to level up faster, riding new routes is a very effective way to do it. Of course, you can ride new routes in group rides, races, etc as well. But as you begin to cross routes off your to-do list, you will learn it’s not always easy to find group rides on the routes you need to finish. A solo effort may be needed.

You don’t have to follow a particular route when exploring Zwift roads, either. You get to choose which way you go at each and every intersection, so if you want, you can go your own way and ride a route nobody has ever pieced together before! That’s how the concept of Rebel Routes came to be, after all…

Need help finding your way around Watopia? Check out our map poster >

Social Riding

We all need connection, and cycling is a very social sport. So it’s no surprise that many Zwifters embrace the social side of Zwift.

I would break social riding on Zwift into three broad categories: scheduled events, RoboPacer groups, and Meetups. Let’s look at each of these.

Scheduled Events

As I compose this post, there are 1000+ group rides scheduled over the next 7 days on Zwift. That works out to almost 150 per day, or around 6 per hour on average. You can browse these rides on the Zwift Companion app (highly recommend, available on iOS and Android). Or if you want to do some “power browsing” check out ZwiftHacks’ event search tool, which lets you filter events on a huge number of parameters.

These rides are organized by teams in the Zwift community, and most of them recur each week, often rotating between various routes. There’s a lot of variety in group rides, so read the event description to make sure you know what you’re signing up for! A few ways group rides can vary:

• Pace: usually stated in watts per kilogram, this is the main determiner of how hard you’ll need to work to keep up with the group, unless it’s a banded ride.
• Length: every ride goes for a set time or distance, so you know how long you’ll be on the bike.
• Route: some groups ride the same route each week, while others rotate between a handful of routes and still others tackle tough routes to help you earn badges.
• Banding: some rides are “banded”, meaning everyone stays together as long as they keep pedaling. Most rides are not. Click “Rubberband” under the Rules section of the ZwiftHacks events app to see banded rides.
• Leaders and Sweepers: leaders are designated with a yellow beacon, sweepers with red. Some group rides have no designated leader and/or sweeper(s), but in my opinion, the best recurring group rides are those with regular leaders. They bring a personality to the event!

My advice? Join a group ride that fits your schedule and meets the parameters you’re looking for. If you like it, come back next week. If it wasn’t your cup of tea, try a different ride next time. The most rewarding group ride experiences I’ve had are on rides where I return week after week and get to know the other regulars.

RoboPacer Groups

RoboPacers are bots who ride at a particular pace on particular routes around the clock. What they effectively create is an always-on group ride. If you hop in with the same pacer around the same time each day, you’ll start to notice some of the same folks are there with you, which is why RoboPacer groups (especially the slower ones) can often be quite social!

Joining a RoboPacer is the easiest and most hassle-free way to start riding with others on Zwift because they’re always going and you can pop in and out whenever you wish.

To get started, just pick a group from the list of cards on your homescreen’s “24/7 Group Rides” carousel, and the game will drop you into that RoboPacer’s group. Start riding, and if the pace works for you, stick with it! Too fast or slow? Teleport to another RoboPacer.

Related Links:
All About Zwift RoboPacers >
RoboPacer Schedule >
All About Teleporting in Zwift >

Meetups

Meetups are a way to organize group rides with one or more friends. When you schedule a Meetup, you pick the date, time, route, length, and whether everyone should be kept together (banded) or not. Then invite your friends to join you!

Related: All About Meetups on Zwift >

One last bit of advice when it comes to being social on Zwift. Ralph Waldo Emerson famously said, “The only way to have a friend is to be one.” That’s true in life, and true on Zwift. Make friends by messaging in game and/or interacting with others in Zwift groups on various social networks (Facebook and Reddit are popular). The more you reach out, the more connections you’ll make.

Racing

If you have a competitive spirit or just want to push yourself to the max, you’ve got to give racing on Zwift a try! There are around 650 races on Zwift each week, which works out to nearly 100 per day, or 3-4 each hour.

Like group rides, races vary in significant ways. But where most group rides are organized by Zwift community teams, a good chunk of the races on Zwift are actually organized by Zwift themselves.

When you sign up for a race, you’ll want to pay attention to a few details:

• Route: are you racing on a hilly course? A flat course? Knowing what to expect course-wise helps you play your pacing and strategy smartly.
• Type of Race: is this a standard “scratch race” (first across the line wins)? A points race? A time trial? Most races on Zwift are scratch races, so assume that unless the event description says something else.
• Categories: how are riders grouped in the race? Does everyone start together, or does each category start on its own?

These details and more can be discovered by using the ZwiftHacks events app.

Related: How to Race on Zwift (Setup, Strategy, and More) >

Finding a Team

Racing on Zwift is fun. Racing with teammates is more fun! Whether it’s the massive Zwift Racing League, a tiny team vs. team Club Ladder event, or a one-off race with a few teammates in the field, having friends in the pack always makes things more interesting and rewarding.

It’s also nice to be part of a larger organization since this provides you with a network of helpful friends who can answer your newbie questions or offer encouragement when you’re struggling. So I highly recommend joining a team on Zwift.

Related: Teams on Zwift: A Comprehensive Guide >

Just Do It

One last note on racing: some riders avoid racing on Zwift because they’re intimidated and fearful of “failing.” But here’s the thing: nobody is watching you that closely. Everyone is focused on themselves, working hard to keep up, and if you drop off the back or decide to exit the event early for any reason, chances are nobody will even notice!

So just jump in and give it a go. You may discover, like I have, that racing is the perfect motivation to push harder than ever and build your fitness to new heights.

Structured Training

While all activity on Zwift is “training” in some sense, structured training is a specific type of activity. We call it “structured” because each workout follows a precise plan, and often those workouts are part of a much larger months-long training plan.

Here’s an example of one structured workout:

The chart gives you a picture of what you’ll be doing during the workout. The height and color of each block tells you how hard the effort level will be (higher effort=taller blocks, and colors follow a standard power zone coloring scheme.) The width of each block tells you how long you’ll be holding that power level.

ERG Mode

Most people ride structured workouts in ERG mode, which is different from the SIM mode your smart trainer uses when simulating hills in game. ERG mode modulates your trainer’s resistance to force you to hold a particular power output. You don’t need to shift gears. Just keep your cadence where you’d like and the trainer will adjust resistance so you’re hitting the target power. Magic!

Related: All About ERG Mode on Zwift >

Your FTP

Target power numbers are generally set based on your FTP, so you’ll want to have your FTP set accurately before you take on a structured workout, otherwise it may be way too easy or way too hard!

How do you set your FTP if you don’t know it? Zwift can auto-detect your FTP if you ride at maximum average power for 8+ minutes, or you can take an actual FTP test.

Related: How (and Why) to Take an FTP Test on Zwift >

Browsing Workouts and Training Plans

Zwift has a huge library of individual structured workouts available by clicking “Workouts” from your homescreen. You can also click Training Plans from that screen to browse progressive, long-term plans that have you complete multiple workouts each week to build fitness in a structured way.

Training plans can feel very rigorous and… well… structured. But they’re also the most efficient way to build fitness on the bike, if you can stick to them!

Wrapping It Up: Find Your Joy

Every rider is different. Some people love exploring, while others love chatting and being social. Some are highly motivated by competition, while others prefer the rigors (and efficiency) of a structured training plan.

Most people are a combination of two or more of these things. I, for example, love social rides and races. These make up probably 95% of my Zwift activities.

There is no right or wrong here. The important thing is to find what motivates you. Because when you find activities you enjoy, they’ll drive you to get on the bike day after day. And it’s that consistency that builds real fitness on the bike!

Questions or Comments?

What gets you going on Zwift? Share below!

Recently, though, I’ve been messing around with AI-based podcast generation tools. We all know AI is the biggest thing happening in tech right now – and it’s only getting bigger. What you may not know is that AI is revolutionizing the way podcasts are created, since AI can greatly reduce the time required to edit a podcast’s raw audio to remove unnecessary content and tweak audio settings for an optimal listening experience. (Simon used Adobe’s AI tools to edit the latest episodes of the Zwiftcast, in fact.)

I was interested in going one step further, though. Having already spent the time to write up detailed articles on so many Zwifty topics, I was looking for a way to auto-generate a full podcast. Just point the robot at key source articles, let it consume the content, and spit out a podcast with real (simulated) human voices.

Enter Google’s just-released NotebookLM, which does exactly that. And does it very well.

List to our first (let’s call it beta) episode, a 12-minute romp on the topic of Trainer Difficulty:

This podcast was created by pointing NotebookLM to the following posts:

• Using the “Trainer Difficulty” Setting in Zwift
• Using Zwift Trainer Difficulty to Simulate IRL Climb “Feel”
• What’s the Best Zwift Trainer Difficulty Setting for Zwifters?
• Zwift Trainer Difficulty on Descents: Did You Know?
• Trainer Difficulty on Zwift: How Much of a Bigger Granny Gear Does 75%, 50%, and 25% Provide?
• Wahoo Kickr Climb Zwift “Trainer Difficulty” Wheelbase Hack

As you’ll hear, NotebookLM has two voices (a male and female) who riff off of each other on the topic at hand. Having listened to this particular episode multiple times, I’m impressed by how they organize the content thoughtfully, summarize it, and even add little comments that I don’t remember writing in my original posts. Maybe that info comes from user comments on the articles? Or maybe the bots are more Zwift-smart than anyone realizes?

Your Feedback

I’m sharing this with the Zwift Insider audience because I want your honest feedback: do you believe a podcast with short episodes on specific Zwift features be useful to you, and/or the Zwift community at large?

Yes, no, maybe so… let me know in the comments below. You won’t hurt my feelings – after all, the episodes aren’t hard to create, and it’s not my voice you’re hearing!

But there’s a new sock on the block giving the fire socks some competition both in exclusivity and fun. Confetti Socks were released in April 2024 as a bonus unlock for level 100 Zwifters (who also unlock the level 100 kit).

How do they work? Here’s me dropping a Ride On bomb while wearing confetti socks:

Riders who wear confetti socks have a special ability: their Ride Ons are confetti-filled and include a +2XP bonus! That is, when you receive a Ride On from a confetti sock wearer, you’ll see confetti on your screen, plus that +2XP bonus.

(You’ll also unlock the “Party On!” badge the first time you get a Ride On from a level 100 Zwifter. This badge is worth an additional 50XP.)

The confetti is only visible to the rider who gives the Ride On and rider who receives it.

Like the fire socks, confetti socks can be put on or taken off in your garage:

I already enjoyed dropping Ride On bombs when riding in groups. Then, using Zwift Ride with Play Controllers made it even easier. And now with the confetti bursts and XP bonuses, I enjoy it even more! It’s like I’m a walking (riding) confetti cannon…

One Confetti Caveat

If you like to use the Companion app to give Ride Ons to friends who are riding while you’re sitting on the couch or hanging in the coffee shop, you should know that those Ride Ons aren’t confetti Ride Ons.

Basically, you have to be active in game in order for your Ride Ons to include the confetti burst.

Your Thoughts

Are you a fan of the confetti socks, or are you a party pooper? Share your thoughts below.

Zwift officially launched their Zwift Racing Score (ZRS) metric this week, and as one might expect, there’s been no shortage of feedback from the racing community. I’ve found myself in an interesting position, hearing feedback from the community but also conversing regularly with the team inside Zwift responsible for creating and continuing to improve ZRS.

Feedback from the community isn’t easy to summarize. On the one hand, we did an opinion poll where 57% of racers said ZRS events have been better than standard category enforced races they’ve recently joined. (21% said “about the same” and 21% said they were worse.) On the other hand, comments on ZRS-related posts here on Zwift Insider have largely been negative, with a few repeating themes:

• The range of abilities in each ZRS band is too wide (“I’m a C racing A and B riders!”)
• Heavier riders and sprinters are disadvantaged while lighter riders are advantaged with ZRS
• “My seed score is too high and racing isn’t any fun because I get dropped every time”
• Riders returning to Zwift are seeded too low due seed score being based on their 90-day power bests

Meanwhile, over at ZHQ I’ve been asking for details about how ZRS works, and why the team built it the way they did. As I’ve taken the time to hear and understand their reasons for doing things the way they have, I’ve generally agreed with the approach they’ve taken.

Both the community and ZHQ have valid points of view. But some comments from the community have simply been inaccurate – people “guessing” as to how things are working, with limited data. ZHQ, for their part, hasn’t answered or corrected many of those comments, because they are keeping some of the details of ZRS under wraps since it is a proprietary engine and they do have real competitors these days.

But I’m a big believer in how true, shared information keeps communities strong. So I asked Zwift if I could get some more detailed answers to questions about how and why ZRS works the way it does. That’s what you’ll find below. Here are my questions, and Zwift’s answers…

Did Zwift consider different approaches before deciding on ZRS? Why not just use ZwiftRacing.app’s algorithm?

Yes, we considered and even implemented several alternatives to Zwift Racing Score, but none made it past internal testing. These included using Machine Learning models to calculate seed scores, variations in score volatility, caps on score changes, and different score decay rates. We also explored automatically moving a user up or down after placing in the top or bottom y% of racers x times in their current category. 

We partnered with Tim Hanson, the creator of ZR.app, to discuss our proposed scoring system, and we continue getting feedback from him and from the community about ZRS. While ZR.app has a lot of very interesting features, and is not hard to grasp by people with some experience in cycling races, we were looking for a solution that would be extremely easy to understand by total beginners, as in a rating scale that ranges from 0 to 1000 (versus a typical ELO rating whose range is not just unbounded but also subject to inflation over time).

ZRS has been a few years in the making. What took so long?

Initially, we implemented a purely results-based solution, using USAC’s points system, similar to what ZwiftPower had done. It soon became clear that our USAC-style points system had problems. Points are earned every time one participates in a race, so people who race more frequently tend to have more points than others who race more seldom, but the former are not necessarily stronger than the latter. In short, points may work great as an incentive for engagement, not so much as a criterion for pen categorization. 

The project to switch from the USAC points system to ZRS started on 09/29/2023. Its central piece is a complex algorithm that has required plenty of analysis and testing. We also developed multiple tweaks during public testing (e.g. podium bonuses and UI improvements). In addition to developing and testing the scoring system, we overhauled our events logic and tooling to be flexible to the new categorization system and enhanced our race results user experience to display scores.

What are the trickier problems you are trying to solve with ZRS, and how have you gone about attacking each of them?

1: How to best categorize someone who has never raced?

We considered some Machine Learning techniques, but those models proved significantly challenging to maintain and evolve. We therefore evaluated an approach similar to that in ZwiftRacing.app, having worked with Tim Hanson himself, who has been immensely supportive in our quest.

Ultimately ZRS predictions are not too far apart from ZR.app’s “compound score”-based solution in essence. We still employ a user’s recent critical power for some interval lengths (30s and 10min), both absolute and relative to weight, to obtain our predictions. The basic difference is that we were able to fine-tune the model a little bit further. Namely, we experimented with different relative weightings of those parameters, as well as different critical power interval lengths, to make our predictions provide a somewhat better fit in our tests, which we conducted on a massive amount of historical data.

2: How do we avoid Tanking and Sandbagging?

• We use 85% of the predicted score as a racing score floor
• We will soon start considering the player score at join time (rather than at signup, which may be done a long time in advance, in certain cases)
• We are considering discarding low-quality race participation (the player score will not decrease if we detect that there were no significant power efforts)

How did you test your ZRS algorithm(s) for accuracy? Was real Zwift racing data used in the analysis?

We used anonymized racing and power data from every distance-based race that has ever happened on Zwift to train and validate our scoring solution and the different score prediction models that we tested. 

How did you decide on the 10min and 30s intervals used to compute seed score?

Intuitively, among the main factors that affect one’s ability to perform well in a cycling race are their skill/strength in sustained efforts (say, for breakaways and climbing) and in sprinting (for mass finishes). While skill (namely, being well-positioned in the peloton, having an accurate sense of timing as to when to launch an attack, being able to decide whether to respond to someone else’s move, pacing yourself well when time-trialing or escaping solo, etc.) cannot be inferred from power figures, raw sprinting power and high sustainable power are certainly crucial for success and can be measured by short- and long-interval critical power, respectively. 

To arrive at our final interval lengths for the seed formula, we considered different power intervals and their correlation with the actual scores obtained from race results. The 30s interval was the one yielding the smallest RMSE (root mean squared error) overall. Among the long(ish) intervals, 10 minutes yielded good results and is more likely to be available and accurate in one’s recent activities (versus, say, a 30- or 45-minute interval), owing to the “sliding windows” nature of the critical power computation (smaller intervals are more abundant) and to the fact that, while training, most people tend not to keep their maximum sustainable power for a long period except in the rarer cases that their workout specifically tell them to.

How did you decide on the ratio between 10min and 30s in the final model?

When developing the seed score formula, we tested thousands of different combinations of power duration and rider weight with varying weights to each factor to find what best predicted the outcome of historical race data. What this revealed is 30s power, 10min power, and rider weight were the best predictors, with more emphasis on 10min power and less emphasis on 30s power. This even outperformed the 5min power interval used by traditional compound score formulas.

We are using the results of this analysis as our starting point for the seed score formula fully realizing it may need to be refined in the future as we shift racing categorization away from power-based categories.

What factors might cause an inaccurate seed score, and what have you done to mitigate these?

Sure enough, the seed score is but a best-effort attempt to estimate ZRS based on some input parameters (power and weight). It will never be 100% accurate. The error is inherent to the statistical regression method. 

Let’s look into the most obvious problems that may arise and how we mitigate them:

1. The outcome of a statistical regression is a curve (i.e., a mathematical function) that adequately maps the input (in our case, the critical power for the chosen interval lengths and the rider weight) onto the intended ZRS seed. For Zwifters who have already completed a scored race, we want to use the seed score as a floor in order to preclude sandbagging. However, since the curve was produced out of a “cloud” of actual scores from existing users (during the regression), some users will naturally fall above, and some below the curve that was found to be the best possible fit. If we were to use the curve itself (i.e., the very ZRS seed) as a score floor, then those users who sit a little below the curve for those input parameters would end up being overseeded (a floor would be set too high). To mitigate that, we use just 85% of the seed as our ZRS floor.
   
   Note that, for someone who has never raced before on Zwift, we do not want to risk underseeding them too badly, because an underseeded race participant will likely spoil the party of a number of other players by winning a race that was too easy (whereas an overseeded participant may have a bad personal experience but will not ruin the fun of anybody else). That is why after the first ZRS race, when we already have at least one instance of power effort and scored race result, we let the player’s score go 15% below the seed. When the score of a user touches the floor (e.g., after performing poorly in a scored race), of course there are reasons to believe that the score of that user must indeed go down; we just don’t want it to go down too much to avoid abuse. A 15% deduction looked reasonable after gauging the number of Zwifters that would touch the floor.
2. Another possible problem may arise, so to speak, from the very user attitude to training. If, in the last 90 days, the user has failed to perform close to their peak in the relevant critical power intervals (namely, 30 seconds and 10 minutes), their seed score will be lower than it should have been. We are planning to mitigate this by establishing a threshold based on their last year performance. If their performance in the last 90 days falls below the threshold, we will use the full one-year critical power figures to generate a seed score.

Once you have your seed score, what are the main variables in the model that impact progression up and down?

• Race results (win/loss)
• Field quality in the races you participate (how strong are your opponents compared to you, in terms of ZRS)
• Variations in Critical Power (adjusts your ZRS floor)

How have you been tuning these, and do they currently feel accurate?

• We run analyses on anonymized data comparing power and ZRS, for all race participations (and also on sampled production data).
• We check ZRS distributions, and also how many Zwifters are sitting on their floor. Depending on the value, it could indicate that we should tune thresholds and other scoring model parameters.
• Based on results from ranked races we feel confident that ZRS is making racing at Zwift a fairer and more enjoyable experience.

What are the main things you learned during the public testing period that began in June 2024?

• Mechanisms that accelerate score progression are important to increase racing fairness. We implemented a podium bonus system after reviewing test outcomes and the feedback we received from the community during the testing period.
• The daily score decay applied after the user’s last race shouldn’t be too aggressive, or it might impact the score progression of Zwifters who don’t race too often. We tuned our decay rate during the testing period.
• The straightforward multiplication of absolute and relative power does not necessarily produce the best-fitting curve to map critical power intervals and weight onto a racing score that is meant to reflect a user’s likelihood to perform well on a Zwift race. Refined combinations of “weights” (exponents) of the input parameters do indeed provide better results.

How do the current ZRS boundaries differ from the previous category boundaries?

In the past, category boundaries were based on fixed power (to weight) thresholds, regardless of the number of users that would belong in each category. The way it is now, we rank the users by ZRS and impose moving thresholds meant to establish cutoff ZRS levels that will distribute the number of users into each category according to a predefined Gaussian curve (fewer people in the extremes of the spectrum, more people towards the “central” categories). 

Another advantage of using ZRS for category boundaries is that it is much more flexible for customization by our event organizers.

Do our current boundaries please everyone? Zwifters who happen to be near the boundaries might feel like they are at a disadvantage. The difference is that, now, if you are in a category that feels too strong for you, you will soon have the opportunity to move down, since your scores will likely reflect the fact that you are not obtaining good relative performances in that former category. 

Will Zwift Racing Score ever be ‘finished’? What’s next?

Rating systems need ongoing monitoring and occasional maintenance. We also anticipate continued constructive feedback and feature requests from the community, so we plan to keep evolving ZRS for the foreseeable future.

Future developments include implementing anti-tanking and anti-sandbagging measures, as mentioned above, as well as incorporating course profiles into our scoring system.  We’re also exploring ways to improve our category ranges, including increasing the number of pens and also dynamic ranges. 

Are you planning to reset scores regularly in the future?

No, unless the scores start to appear inaccurate for some reason. In that case, we would not only reset the scores but also investigate the issue and adjust the model as needed.

We might explore the idea of “seasons,” where scores reset at the beginning of each season, similar to other MMOs. However, this is not currently part of our roadmap.

What are some of the common misconceptions you’re seeing about ZRS, and how would you answer them?

A major misconception about ZRS is the overemphasis on the seed score’s impact on individual scores. While the seed score does set a baseline (which isn’t intended to be very restrictive), most Zwifters are not expected to remain at this score. Their scores will naturally fluctuate up and down as they participate in race events.

Another misconception is that the 30-second critical power used to calculate seeds may inflate certain scores, suggesting other intervals should be used instead. However, our correlation analysis between multiple power intervals and scores found that using both the 30-second and 10-minute intervals provides the best fit, with the 30-second interval having less influence than the 10-minute interval in the formula.

My Takeaways

I think there are a few key takeaways from Zwift’s answers above which speak to some of the recurring concerns I’m hearing from the community.

• First, their explanation of why they didn’t just use the ZR.app algorithm. Basically: Zwift wanted to make ZRS Zwifty. That means keeping it simple.
  
  While ZR.app has a lot of very interesting features, and is not hard to grasp by people with some experience in cycling races, we were looking for a solution that would be extremely easy to understand by total beginners, as in a rating scale that ranges from 0 to 1000 (versus a typical ELO rating whose range is not just unbounded but also subject to inflation over time).
• I’ve seen comments like, “Did Zwift even test this? Why did they choose 30s and 10-minute intervals, because those seem like the wrong ones to use!” But Zwift chose those intervals after lots of analysis.
  
  We used anonymized racing and power data from every distance-based race that has ever happened on Zwift to train and validate our scoring solution and the different score prediction models that we tested. 
• It sounds like Zwift is working to include more historic data in the seed score calculation, which will be welcomed by just about everyone.
  
  We are planning to mitigate this by establishing a threshold based on their last year performance. If their performance in the last 90 days falls below the threshold, we will use the full one-year critical power figures to generate a seed score.

While Zwift’s current implementation of ZRS isn’t perfect, I’ll say what I’ve said in other posts: it’s much better than the old system. Things may feel a bit messy right now as riders haven’t done enough scored races for their ZRS to accurately reflect their abilities, but over time I think we’ll see scores settle in and races become more competitive and fun for everyone.

Questions or Comments?

Hopefully, this deep dive has clarified some things for the Zwift community. Still got questions or comments? Share below!

Yesterday, Zwift officially graduated Zwift Racing Score (ZRS) from Zwift Labs and released it as the de facto race categorization method on the platform. As of today, the vast majority (over 80%) of public races on Zwift are using ZRS.

It’s a big change in the world of Zwift racing, and it comes after no small amount of development work by Zwift’s team plus months of testing and feedback from the Zwift racing community. I’ll be diving down the ZRS rabbit hole later this week, but first, here’s a straightforward post covering key Racing Score topics. Let’s go!

Zwift Racing Score: How It Works 

Every rider is given a ZRS between 0-1000 (higher is better). But where does that score come from, how does it change over time, and how is it used in Zwift races?

Your Starting Score

Your score begins with what Zwift calls a seed score, and it is based on your weight and historic power numbers. Zwift looks at all your activities in the past 90 days and pulls out your best 30-second and 10-minute power performances, then plugs those values into their super-secret algorithm to produce a seed score between 0 and 1000. It’s this initial score that determines which group(s) you can join for your first scored race.

Your Race Category

While not all races on Zwift use ZRS for categorization, as of October 7, 2024, almost all races do. And while races can use custom ZRS bands, most scored races, including all Zwift-owned races, use the following category ranges:

• 690-1000
• 520-690
• 350-520
• 180-350
• 1-180

See below for more on joining your first scored race.

Updating Your Score

As you race, your score changes based on where you finished (podium? last place? somewhere in between?), as well as who you raced against (strength of field).

This makes intuitive sense, of course. A high finish against strong competitors should increase your score more than the same finish against weaker competitors.

Your score can also change (increase) if you set a new 30-second or 10-minute power best. And it may decrease if a current power best ages out of that 90-day window and gets replaced by a lower number.

There’s also a bit of decay built into the scoring algorithm, so if you don’t race or set new power bests, you’ll see your score slowly decrease over time.

If your score decreases, take heart: your personal score is just a moving probability of predicted race results. As it adjusts based on race results and 90-day power numbers, you should find yourself placed in groups that deliver a challenging yet enjoyable race experience.

Finding Your Racing Score

Your ZRS can be found in the Zwift Companion app and on your profile at zwift.com:

It is also visible on your ZwiftPower.com profile page.

Joining a Scored Race

You don’t need to know your racing score to race on Zwift, though! When browsing races in Companion or at zwift.com/events, Zwift highlights the “Recommended for you” group based on your current score:

Click the (+) sign to join your desired group. You can join a higher-scored group, but you cannot join a group below your current Racing Score.

Note: you must have at least three 10+ minute activities recorded in the last 90 days in order to race a scored event. This helps ensure an accurate seed score, thus improving Zwift’s choice of category for your first race.

Understanding Race Results

When you finish a scored race, your ZRS is recalculated so it remains an accurate reflection of your current abilities.

You can see your new ZRS under your profile as shown above, and it is also saved in the event results in Zwift Companion and on zwift.com under your activity details or the event’s homepage:

Race results show your new Racing Score, and an arrow indicating whether it increased or decreased as a result of this race:

A down arrow with a line below means you’ve hit your floor score – the lowest possible score you can reach based on your 90-day power numbers.

An up arrow with a line below means you set a new power best, which increased your seed (and thus your floor) score. This arrow only shows when your new floor exceeds what you would have otherwise had as a result.

What’s Next?

While Zwift officially launched ZRS this week, they’ve been very clear in saying that they will continue to monitor feedback and metrics and work to evolve ZRS for the foreseeable future.

Zwift says they are investigating the following:

• Enhancing the seed algorithm to incorporate a broader range of historical data, considering the performance of racers who are transitioning back indoors after an outdoor riding season
• Measures to prevent intentional score manipulation
• Category enforcement applied when joining an event instead of at sign-up
• An historical view of how your score has changed over time
• Incorporating course profiles into the scoring system
• Improving category ranges, including increasing the number of pens and also dynamic ranges

Concluding Thoughts

The implementation of Zwift Racing Score is the most game-changing update to Zwift racing that we’ve seen in recent years. Now, instead of categories being based purely on riders’ power numbers, they are results-based, taking racing smarts and other factors into account.

ZRS is the results-based categorization system Zwift racers have been requesting for a long time. While it may not be perfect in the eyes of some, it’s vastly improved in the eyes of most, including myself. Here are some of the ways the new ZRS system beats the old category system, in my opinion:

• Harder to sandbag: in the old system, riders in every category below A could simply sit at the top of their category, winning race after race, without ever being upgraded. That will happen much less with ZRS, thanks in part to podium bonus points being added to scores.
• Custom categories: race organizers can define custom category bands much more easily with ZRS than with the old system’s zMAP and zFTP metrics. This encourages events that group riders in fresh ways, mixing up who is at the top and bottom of each category.
• Immediate feedback: your updated Racing Score provides immediate feedback as to whether you placed above or below your expected position in each race. This is a new, immediate feedback metric that wasn’t available with the old system.
• A global KPI: While ZwiftPower’s Rider Rankings work decently well, the metric is flawed in various ways and not available on Zwift Companion or zwift.com. Zwift Racing Score is the closest we’ve ever come to a simple, single Key Performance Indicator that can be used to assess a rider’s overall racing ability.

There are improvements still to be made to the new ZRS system, of course. I’m particularly looking forward to Zwift incorporating more historical data into riders’ seed scores to help prevent them from blowing up lower-category races when they return to Zwift racing after taking a few months off.

But for now, I’ll take the much-improved system over the old one any day. Ride on!

Questions or Comments?

If you still have questions about Zwift Racing Score, you may also want to visit Zwift’s support page on Racing Score.

If that doesn’t answer your questions, or you have feedback on your race experience in scored events, please share below!

How To Block Another Zwifter

To block a Zwifter, you’ll need to use the Zwift Companion app for iOS and Android. Look up the Zwifter’s profile Companion (More>Find Zwifters is one way, but there are others). Tap their name to access their profile page, then tap the 3-dot menu at the top-right and tap “Block User” then tap it again to confirm. You’ll see a confirmation message whenever you visit their profile:

You can easily unblock anyone you’ve blocked by following the basic instructions above: look up their profile, tap the 3-dot menu, then tap “Unblock User”.

What Does Blocking Do?

When you block another Zwifter, they cannot:

• Send you direct messages in game/via Companion
• Follow your profile (which means they will never see you listed on the “Join a Zwifter” feature)
• View your activity history in Zwift

Even though you block a user, they can still:

• See you in game if riding nearby
• See your name listed in race results (since those are public)
• Look up your profile using the Companion app (but they cannot see your profile details). They will see a basic profile screen with your name, profile image, and country, plus the message “This user is private. You must request to follow them before you can see their full profile.” (As far as I can see, if the Zwifter attempts to follow you from this screen, the attempt is essentially ignored by Zwift. Which is good.)

Read more about blocking at support.zwift.com/blocking

Questions or Comments?

Want to test the new blocking feature? Search on “insider” and block any of Zwift Insider’s bot accounts. You won’t hurt their feelings.

If you have any thoughts about this new feature or questions about how it works, go ahead and comment below.

Zwift rolled out their Video Screenshots feature in the first half of 2023, making it easy for many Zwifters to save video snippets of their activity for sharing on Strava or other platforms. Here’s an example of a video from a recent race:

Read below to learn all about Zwift’s Video Screenshots feature.

Recording a Video Screenshot

The Video Screenshots feature records 15-second video snippets of game play. These snippets are automatically recorded in certain cases, but recording can also be manually triggered.

If you have Video Screenshots enabled, most of the highlights you’ll want to capture are automatically saved. Automatically captured highlights include:

• Taking a segment jersey
• Setting a new PR
• Finishing a challenge or mission
• Gaining a level
• Unlocking an achievement
• Finishing an event
• Completing a workout or training plan 
• Completing a new route
• Completing a goal

You can also manually trigger a 15-second video screenshot by clicking the button highlighted below in game or in the Companion app. This will save a recording of the previous 15 seconds of gameplay to your device.

Once you click to a video screenshot, you’ll have to wait 5 seconds before clicking to record another.

Supported Devices

Due to the processing power required to record video screenshots, this feature is only supported on higher-powered Windows PC, Mac, iOS, and Apple TV devices. It is not currently supported on any Android devices.

See the “Device Compatibility for Capturing Video” section of Zwift’s support page for details on supported devices.

About the Video Files

Video Screenshots are saved as .mp4 files with H.264 encoding, and are automatically downscaled to a maximum height of 720 pixels regardless of the resolution in which you’re running the game. Audio is encoded using AAC at 48 kHz. Files are typically ~4MB in size.

Video files are saved to the following locations, where you can access or delete them whenever you’d like:

• iOS: Apple Photos app
• macOS: Movies/Zwift folder
• Windows: Videos/Zwift folder

Due to limitations on Apple TV, your video recordings aren’t saved in a location you can manually access. They’re saved to temporary memory in your Apple TV, and will be deleted eventually by the OS.

Uploading to Strava

You can choose up to one video screenshot to upload to your Strava activity, along with up to five photos. This is done on the End Ride screen:

The first video screenshot recorded during your activity will be automatically selected for upload, but you can click to ignore a video and add a different video if you’d like.

Turning Video Screenshots On or Off

If your device supports Video Screenshots in Zwift, you’ll see an option to enable/disable the feature under Settings>Preferences:

The option is enabled by default, but you can disable it if you’d like.

A Note about CPU Usage on Windows

In tests on multiple Windows PCs, we’ve seen Zwift’s CPU usage increase by around 20% when Video Screenshots are enabled:

If you have a strong enough PC this shouldn’t impact your game experience, since the Video Screenshots feature is multi-threaded and won’t use the same CPU core that Zwift heavily uses for gameplay.

That said, riders on weak or overloaded systems may see an impact. If you notice your system performs poorly with Video Screenshots enabled, simply disable it.

Questions or Comments

Do you use Zwift’s Video Screenshots feature? Got questions or comments about how it works? Share below!

The paint scheme is a white frame with a shiny Zwift logo on the downtube, mimicking the Zwift Ride’s real-life paint scheme:

Once you update to Zwift version 1.69 or later and enter the game with your Zwift Ride frame controllers paired, you will see a banner notifying you of the unlock:

From there, just click on the custom paint scheme at the bottom-right after picking the Zwift Concept Z1 frame in order to get the white “Ride In Style” paint scheme:

It’s important to note that pairing a Zwift Ride only unlocks the paint scheme. It doesn’t unlock the actual bike(s)! You’ll still need to earn your Tron bike before you can apply the new white paint.

Still pondering a Zwift Ride purchase? Use the links below to shop now and support this site…

Purchase Zwift Ride

Last week, Zwift granted access to Shane Miller (GPLama), Nathan Guerra (Zwift Community Live), and myself to ride The Grade and livestream the experience. Shane couldn’t ride it with us due to his travel schedule, but you can watch his video here. Nathan and I (along with Nathan’s wife Gabi) livestreamed our ride up The Grade one day later – see my video below:

The Grade: How It Works

The Grade is a 3.5km-long climb that is fairly steady (8.6% average), apart from short flat bits at the start, middle, and finish. It’s a KOM segment like other KOMs in Zwift, but The Grade is special in that it also functions as an FTP test!

How does that work? Well, Zwift looks at your average power and time up The Grade, then computes your FTP estimate based on those two figures. Zwift says they can do this with reasonable accuracy because they’ve analyzed the results of over 700,000 FTP tests on the platform and computed a curve which, when combined with an average power number and time value, lets them compute your FTP.

(I was going to create a sample chart here to illustrate, but I don’t want to confuse people who may think this is the actual curve from Zwift. So I’ll wait to do that until I’ve run enough tests to publish an actually accurate chart).

The curve Zwift put together would have percentage on the Y (vertical) axis, and time on the X (horizontal) axis. Time (X axis) would begin at 8 minutes (Zwift says they can’t compute accurate FTP for times shorter than that, but don’t worry, since you’d have to hold 8 W/kg to do The Grade in 8 minutes). Percentage (Y axis) would be maybe 85% at the lowest, all the way up to 100%.

This is basically a “lookup curve”, with the charted line climbing from left to right as time gets longer. If you were doing this manually you’d go to the spot on the X axis that matches the time it took you to climb The Grade, then look at the percentage value (Y axis) at that spot. Then you’d multiply your average power for the segment by that percentage to compute your FTP.

For example: it’s generally accepted that your FTP is equal to 95% of your best 20-minute power. (This is how Zwift has automatically detected FTP game-wide since the early days, in fact). So if it took you exactly 20 minutes to finish The Grade, and you averaged 200W during that time, Zwift would calculate your FTP as 200W x .95 = 190W.

Based on Nathan, Gabi, and my results, we can calculate at least three points on Zwift’s curve. But more on that below…

My Strategy

Heading into this FTP test, I wasn’t really sure where my FTP was at. I hadn’t tested it in months, hadn’t been doing any structured training, and my performance in recent races had been a bit erratic (not helped by swapping on and off various trainers/setups I’ve been testing).

My guess was that my FTP was between 300 and 310W. So, I decided to start by trying to hold 320W, then when I reached the halfway point, I would bump that up if possible.

Why this strategy? Well, because starting a bit conservatively is the best way to approach an FTP test if you’re unsure about your current FTP. But also, and perhaps more importantly, I didn’t want to blow up early and embarrass myself on a live stream!

What that plan in place, I headed out to warm up for about 30 minutes while I chatted on Discord with Nathan and Gabi and we got our livestreams set up. When the time arrived, we all picked the “Oh Hill No” route, and the fun began!

Ride Experience

The Oh Hill No route starts you just a few feet away from The Grade start line, so there’s no warmup here. (If you want to warm up first, do your warm up then pick this route and go. Or choose “Elevation Evaluation” as your route, which gives you a few km of warmup before starting The Grade.)

I hit the pedals hard to get up to speed, then tried to quickly settle into my target 320W pace.

A few minutes passed, and my legs were feeling pretty good. My average power (which is displayed on screen during the test) was holding right around 330W, but I decided not to ease up. I kept pedaling at what felt like a sustainable pace.

My power average read 328W as the road leveled out at the halfway point. I had to shift up two gears keep my power up on the short flat section, then the grade turned uphill again, and I finished sector 5. Halfway there!

I could hear Nathan doing his angry gorilla roaring, 70 seconds up the road. Gabi was 40 seconds up the road and silent. Both were putting out strong numbers in the 5 W/kg+ range, while I was barely breaking 4 W/kg. But this was no surprise, since both Nathan and Gabi are some of the best racers on Zwift!

My legs were feeling better than anticipated as I wound my way up the twisty second half of The Grade, so I increased my power to what I thought I could hold to the end. And I began doing the math in my head to estimate how much longer I had left.

I heard Nathan finish his test in 10:37, with an FTP detection of 335W. Spot on what he had guessed his FTP was currently at (4.97 W/kg based on his weight in ZwiftPower.)

A bit later Gabi finished in 11:46, with an FTP of 251W detected (4.54 W/kg based on her weight in ZwiftPower.)

(I should note here that Nathan and Gabi had done a 5-hour maximal effort ride 2 days earlier, so their legs weren’t exactly fresh for this effort.)

My average power was showing as 336W, but I was up over 370W now. Just one hairpin left! The gradient was 12%, but thanks to my 50% trainer difficulty plus virtual shifting, I had plenty of gears and was spinning at 95RPM. I stayed seated (is that still a rule for FTP tests?) and hammered my way up the final climb, spinning at 105RPM+ to keep my power high as the gradient slackened and I crossed the line:

Final FTP test results from The Grade:

• Nathan: 388W average for 10:37, 335W FTP (86.34% of average)
• Gabi: 287W average for 11:46, 251W FTP (87.45% of average)
• Me: 340W average for 14:02, 302W FTP (88.82% of average)

Concluding Thoughts

My first thought when I crossed the line and saw the 302W FTP value was, “That seems too low.” Yes, my test had only lasted for 14 minutes, but I had averaged 340W! Heading over to intervals.icu, I saw that their system estimated my FTP from the effort at 317W. That made me feel better.

As I turned around on the top and began descending The Grade, my next thoughts were that the time had passed quickly, and the test wasn’t as terrible as I thought it would be. I think the passing scenery and chasing other riders helped. Of course, knowing people were watching my effort on the livestream also helped!

Pacing oneself properly is a big part of maximizing your FTP test results, but this isn’t a straightforward proposition your first time up The Grade. I didn’t know how long it would take me to get to the top, and the 10 segments (each 357 meters long) vary somewhat in gradient, so you can’t just estimate your time based on which segment you were on.

Now that I know the layout of the climb and that I did it in 14 minutes, I think I’ll be able to pace myself better next time and bump up my FTP result by at least a few watts. I may even turn my trainer difficulty to zero so I don’t need to worry about shifting as the gradient changes.

The Best FTP Test?

Surely, The Grade’s launch is going to reopen lots of debate about FTP testing. It’s already kicking off in various chats on Reddit, Facebook, etc! Many riders are confused by how Zwift can estimate FTP using a climb segment. Others say it’s not possible to accurately detect FTP with these shorter efforts.

Here’s where I land: I think all FTP tests are just estimates, since your results are based on imperfect pacing and results calculations that are estimates themselves. 20-minute tests and that 95% figure? That’s an estimate. Ramp tests? An estimate which delivers too high of a result if you’re anaerobically-gifted. The Grade? I’m not sure, but my result felt a bit low. (Nathan said his was right on.)

In the end, the best FTP test may just be the one you’re willing to take. And I’ll be taking The Grade again, because it didn’t suck nearly as bad as the standard 20-minute FTP test!

Your Thoughts

Are you looking forward to trying out “The Grade”? What do you think of its methodology? Share your thoughts below…

Also featured in this week’s picks are videos on sprinting, steering, life after Zwift Academy Finals, and a race recap.

Got a Great Zwift Video?

Share the link below and we may feature it in an upcoming post!