Behind a lot of the work on this blog are a bunch of machine learning models which aim to predict elements of cycling races. I predict whether a race will end in a bunch sprint, whether the morning breakaway will win, which climbs will be most impactful, what the winning power efforts will be over 5 minutes and 40 minutes, which riders have the best chance of finishing highly, and roughly what those win probabilities are by rider. None of this stuff is crazy sophisticated, but the outputs are interesting to look at prior to a race.

With that in mind, I’ve setup a script to collate all of this data for interesting races each week and spit-out automated predictions for a range of models. If this experiment continues, I’ll have the script generate a post each evening and if time permits add a bit of commentary around the data. If not, you’ll just get data and charts.

Race Profile

Alcudia will have a single fairly benign climb in the last third of the race before a downhill drop to the flat finish.

Race Features

The models predict a small chance of the morning breakaway winning – which seems very unlikely to me – and good chance for a bunch sprint (20+ riders finishing together in leading group – which seems low considering last year was a sprint. We’ll see if any riders mix it up on the climb.

The predicted efforts by leading riders are 6.1 watts/kg & 420 absolute watts for 5 minutes and 4.3 watts/kg for 40 minutes. For 5 minute efforts, those are slightly above-average for pro races. For 40 minute effort, that is bang on average.

Race Favorites

These are explicitly generated without looking at betting markets which are very likely are generating better predictions. In particular, the markets seem much more convinced of a sprint.

Girmay won last year and is the favorite again. Presumably he will win in a sprint, though if a smaller group (say 10-20) goes to the line he could easily be in it. The leaders are divided pretty obviously into riders who will win in a sprint (Trentin, Garcia Cortina, Bouhanni, Senechal, Teunissen) and those who will win with a late attack on the climb (Powless, Martin, Konrad).

Historical Power Efforts

Last year’s parcours was very similar with more kilometers. It required fairly benign relative watts (6.2 watts/kg for 5 minutes and 5.4 watts/kg for 20 minutes) and larger absolute watts (430 watts for 5 minutes and 375 watts for 20 minutes). The Z-scores compare to all other pro races where larger watts were required for the longer efforts with fairly high absolute power required for 20 and 40 minutes. This race was fairly high intensity at the end in 2022.

Considering the profile is similar, we can look at where peak efforts occurred for 30 seconds and 2/5/10/20/40 minutes for four groups of riders (top 20 finishers, 21-60, 61+, and non-finishers). The race last year was 174 kilometers with the Sa Batalla climb at 138 kilometers.

Unsurprisingly for a race without much going on the main efforts from 5+ minutes happened on the climb. Top finishers did their strongest 30 second and 2 minute efforts at the end.

The Sa Batalla climb was raced with median 5.5 watts/kg and 371 watts in 2022 race with little difference between those who finished in final group (5.51 watts/kg) and not (5.39 watts/kg).

Top-level professional cycling teams typically turnover around 20-25% of their roster (~7-8 of ~30 riders) year-over-year. Along with organically developing talent, in and out transfers are the primary way teams can change their level of performance. By consistently acquiring better talent than they part with – and particularly talent which fits into their team and which they have a plan to develop, a team can aim for promotion to the World Tour and compete for monuments and grand tours. A team which consistently brings in inferior performers to what they send out will likely struggle to perform and retain sponsorship over the long-term.

Typically, transfer quality has been evaluated immediately prior to a new season by judging the quality of riders brought in (measured perhaps by UCI or PCS points) minus the riders lost. This method works as a rough accounting of riders in and out, but such a method fails to adequately judge transfers by 1) focusing only on the just-finished season performance (ie, a rider is considers to be their most recent body of work) and 2) not accounting for actual performance of the rider (which is subject to impact of age, new training methods, health, race schedule, and ultimately randomness, but is still an important factor to judging transfers).

For example, in the above link Quick Step going into 2022 ranked 18th of 18 World Tour teams in PCS points surplus for riders in vs riders out. They lost Almeida and Bennett, while signing a handful of younger riders. In the end, their five new young riders scored nearly 1000 PCS points (almost +800 vs 2020-21 average), while the riders they lost scored only 1600 PCS points (a drop of -600 vs 2020-21 average). Ultimately, based on improvements by riders coming in and declines by riders going out, Quick Step probably had a top three transfer performance among World Tour teams.

In-transfers

I introduce a new evaluation system which measures the change in PCS points won by riders in year N + 1 as compared to years N – 1 and N, while also looking at the source of a transfer (Continental team, junior/national/club team, or Pro/World Tour level team).

By this method, Quick Step stands out as the superior World Tour team in the period of N = 2012 to N = 2021 on average improving the output of the riders acquired by 81% (eg, an average of 1000 points in years N – 1 and N = 1810 points in year N + 1) compared to a range of -11% to +38% among other World Tour teams.

Just looking at transfers brought in from established professional teams Quick Step also leads with an average improvement of 49% year-over-year compared to a range of -22% to +22% among other teams. Quick Step has signed riders who produced an average of 346 PCS points vs 514 PCS points in their first season with Quick Step. The trailer in this regard is Cofidis who have signed riders with an average of 246 PCS points who have produced 192 PCS points in the first season with the team.

Quick Step isn’t necessarily shopping at the top of the market either given that their average PCS points per signing rank just 9th highest (about average) among World Tour teams at 346 per signing (just looking at riders signed from other pro teams). UAE Team Emirates ranks by far the highest with 446 points per signing while Intermarche – Wanty shops at the bottom of the market with 174 points per signing.

Teams don’t just sign riders from other professional teams; they have to identify and convince top juniors and U23 riders to join them directly or join the development team with a path to the World Tour. Looking at teams who sign riders from all non-professional sources (Conti level, juniors, national teams, club teams), Quick Step again stands out with acquired riders producing about six times (+521%) the average points they produced in the two previous years. This compares to a range of +19% to +490% for World Tour level teams. These massive gains are because PCS points scales aren’t designed to fully reward races below professional levels (.2, U23, Junior, and Nations Cup races) and riders race more often in World Tour.

Since 2012, Quick Step has three of the eight best neo-pro transfers with Evenepoel in 2019, Gaviria in 2016, and Jakobsen in 2018.

The simplest way to illustrate Quick Step’s transfer success is to just look at the percentage of signings who score more PCS points in the next year for signings from other professional teams; across the World Tour that value is 40% for all signings. Quick Step manages to improve 60% of their signings – only BORA – hansgrohe crosses the 50% success mark.

Again, we can simply explain Quick Step’s success at signing non-professional riders by calculating the percentage of transfers who score 100+ PCS points in the next season (this is roughly the level of the 500th best rider in the pro peloton). Quick Step manages to get 65% of these transfers to this level compared to just 32% of riders on other World Tour teams. Only three World Tour teams manage even 50% of riders scoring 100+ points.

Out-transfers

Quick Step is also well-known as a team which knows when to allow a rider to leave (after a career year will make them too expensive or when age will cause their performance to decline). I repeated the same analysis for teams looking at how riders who left the team performed in the year after (N + 1) compared to an average of the two years prior (N & N – 1).

Again, Quick Step has distinguished themselves by ranking third best over this time period among current World Tour teams with their riders declining by -24%, behind Intermarche at -29% and BORA – hansgrohe at -27%. The trailers in this category (meaning riders leave and win more points) are Alpecin – Deceuninck (+39%) and Cofidis (+14%). Alpecin has had comparatively few and typically unproductive riders leave which might skew the numbers.

Quick Step has four of the seven riders who transferred out and lost the most PCS points dating back to 2012 – Elia Viviani (Cofidis in 2020), Marcel Kittel (Katusha in 2018), Philippe Gilbert (Lotto in 2020), and Michal Kwiatkowski (Sky in 2016).

Limitations

Riders who transfer in after injury or another less typical situation might artificially inflate certain team’s transfer successes. For example, it’s not immediately clear how much of Mark Cavendish’s relative success in 2021 vs 2019-20 was due to 1) Quick Step’s unique team situation, 2) improved health/ability to train, 3) dumb luck, or some other factor. In this analysis, Quick Step gets the credit for identifying his talent, convincing him to join them, and executing on returning him to greatness.

This approach also only considers the immediate N + 1 season where many riders are signed for 2+ seasons. Young riders particularly may be signed with an eye towards development by certain teams with the idea that they will pay-off in N + 2 or further seasons. Not considering contract length and performance over a contract is a limitation.

None of this analysis considers salary. A rider who produces less value than in previous years, but who was signed to a cheaper than expected contract could be a successful transfer. A rider who improves year-over-year, but was signed to a more speculative high-price contract may be an unsuccessful transfer. Without knowledge of salary it’s always going to be tough to evaluate transfer success. However, a very rough proxy for salary is a riders recent performance. A rider who scores 1000 PCS points and then signs a new contract will likely be paid more than a rider who scores 250 PCS points and then signs a new contract. Thus in the aggregate, we can probably judge a team who consistently signs a rider scoring 1000 points who then scores 800 points the next year as getting poor value.

Also, none of this analysis considers need or role. For example, a team which is desperate for a sprinter to fit in their team might be justified paying for a sprinter who is likely to underperform their prior seasons of performance. Also, a team with a GC captain, but lesser support riders, might be justified signing a few support riders who had bigger roles elsewhere knowing their output will decline, but on aggregate the team will achieve more.

This is a very interesting hilly stage which has the potential to turn out in a bunch of different directions after a start to the Tour which has pretty much followed the script so far.

Headline Numbers

These are outputs of machine learning models trained on top-level races in the last six years.

Climbing difficulty: 5.4 (on a scale where 0 = flat and 20+ = high mountains)

Probability of morning break winning: 32%

Probability of ending in bunch sprint: 8% (at least 20+ riders finishing together in winning group)

And 220 kilometers in length, which is the longest of this year’s Tour

Similar Stages

Recent similar stages in terms of parcours and uphill finish include Stages 1 and 2 in 2021, Stage 3 in 2019, Stages 5 and 6 in 2018, Stage 3 in 2017, and Stage 2 in 2016. Each had hilly parcours without any significant climbing efforts, but ending in a fairly short uphill finish. Those seven stages have been won 3x by Sagan, 2x by Alaphilippe, and once by MVDP (with Dan Martin winning also). So these stages tend to be won by ultra-elite punchy riders.

However, the yellow jersey was in play at least hypothetically for a bunch of riders entering those stages which kept their teams engaged in A) limiting who got away in morning breakaway and B) trying to pull that break back. In those seven stages, between 4 and 7 riders got into the morning breakaways and the groups were mostly riders from second tier teams with 2019 Tim Wellens being the best of the bunch.

In this case, only four other riders are within 30 seconds of Wout Van Aert. Of them, Lampaert and Boasson Hagen don’t have a chance of taking the jersey from Van Aert from the peloton tomorrow. Powless perhaps has a very outside shot. Pogacar probably has no interest with the efforts on the cobbles yesterday and a mountain top finish tomorrow. That leaves no team particularly interested to chase to try to get into yellow.

In terms of the stage win, this is not a finish for sprinters. Of the seven comparison stages, they were contested by final groups of 40 or fewer riders where Sagan, Michael Matthews, and Sonny Colbrelli were the most “sprinter-like” riders in the bunch. Translating that to 2022, that means Ewan, Groenewegen, Philipsen, and Jakobsen probably have no shot tomorrow. That means four fewer teams who will be interested in chasing things down; rather, they’ll want to fire riders up the road in the breakaway.

That leaves almost every team outside the six with GC favorites (UAE, Jumbo, INEOS, Movistar, Bora, and FDJ) interested in making sure they are represented in the breakaway. In the first week of stages in the last four Tours it has been extremely rare for double-digit riders to get into the morning breakaway. We’ve seen it only twice, once on Stage 6 in 2019 (summit finish) and once on Stage 7 in 2021. It is rare to see large breakaways go in the first week, but this could be the day.

How it could play out

I would amend the model’s estimate of the breakaway’s win probability upward to something like 80%. That remaining 20% is if Jumbo-Visma stubbornly brings the breakaway back to keep Van Aert in yellow/try to get another stage win or if something weird happens with morning break and a lot of strong teams don’t get someone in it.

Stage 7 from last year might be the template for how the stage goes. That was also the longest stage in the race after a first week where two hill top finishes and a time trial established a hierarchy. It was hillier with more climbing and less climbing at the very end of the race, but not dramatically so. In the end, nearly 30 riders got away in the first 50 kilometers of the stage including major one day race/classics/puncheurs like Asgreen, Van Der Poel, Van Aert, Mohoric, Stuyven, and Kragh Andersen. The GC group motored in five minutes down still 30 riders strong.

My model which is designed to predict which riders will get in breakaway based on tomorrow’s parcours predicts the following chances (trained on past breakaways so this considers both desire and ability to get into the break). All together, this model predicts 9 riders. So if we see something like 18 riders, we could multiply these chances by 2x. I’ve italicized anyone probably on team duties.

15%: Wellens, MVDP
14%: Gougeard
13%: Bonnamour
12%: Cort, Politt, Perez, Gallopin
11%: Storer, Clarke, Dewulf
10%: Rolland, Teuns, Oliveira, Bouchard
9%: Van Moer, Lafay, Mohoric, Soler, Gilbert, Simmons
8%: Goossens, Tratnik, Mollema, Sanchez, Houle, Van Der Hoorn, Benoot, Turgis, Martin, Kamna, Woods, Dillier

Notably on this list there isn’t a Quick Step rider as Cattaneo, Honore, Bagioli, and Asgreen are all 6-7%. Surely they will be represented in any move which has a chance to stick.

In addition, it’s possible we see non-traditional breakaway specialists try to get into the move. This could be someone like Sagan, Michael Matthews, or even Jasper Stuyven if he gets any freedom from the peloton.

Combining this intuition about break’s chances with support from the numbers I have the following probabilities for tomorrow given an 80% chance of morning breakaway winning:

Rider	Win Probability
Van Der Poel Mathieu	21.2%
Wellens Tim	4.2%
Mohoric Matej	4.0%
Woods Michael	3.5%
Matthews Michael	3.1%
Bonnamour Franck	2.5%
Teuns Dylan	2.1%
Pogacar Tadej	1.9%
Roglic Primoz	1.9%
Van Aert Wout	1.9%
Martin Guillaume	1.9%
Stuyven Jasper	1.8%
Mollema Bauke	1.8%
Ciccone Giulio	1.6%
Vuillermoz Alexis	1.6%
Asgreen Kasper	1.6%
Bagioli Andrea	1.6%
Lutsenko Alexey	1.5%
Honore Mikkel Frolich	1.3%
Barguil Warren	1.2%
Guerreiro Ruben	1.1%
Sagan Peter	1.0%
Kron Andreas	1.0%
Bardet Romain	0.9%

MVDP at 21% is pretty rich given his mediocre form so far, but given his overall ability + propensity to get into breakaways I can make sense of it. I doubt Bonnamour at 2.5% to get his first pro win today is close to right.

There’s a number of big stories on the general classification of this year’s race. Obviously Pogacar is going for his third straight Tour all before turning 24. He’ll get another showdown with Primoz Roglic after their tight battle in 2020 and Roglic crashing out of the race in 2021. Jumbo-Visma also has another contender beyond Roglic in the form of last year’s 2nd place Jonas Vingegaard. And a bit under-the-radar, but INEOS Grenadiers haven’t gone more than three grand tours without winning GC since 2015 (a time period during which they’ve won 9 of 21 GC titles).

Pogacar vs Roglic?

Pogacar is the bookmakers favorite – significantly – with a price of about 1.77 for/1.90 against at Pinnacle (implied about 52% to win the Tour). Both Roglic and Vingegaard are implied around 12-14% based on odds of about 5.0. Vingegaard has shortened significantly since a strong performance in the warmup Dauphine race as Roglic used to have roughly two thirds of the win probability among the two in March, but that has shortened to about 50/50 or even advantage Vingegaard in the last two weeks. So while this race will certainly be billed as Roglic vs Pogacar, Vingegaard is coming in very strong to have equal odds – especially given the team will certainly defer to Roglic a bit.

Of course the question must be asked whether Pogacar deserves to be the massive favorite? He is likely the biggest Tour de France pre-race favorite since Chris Froome in 2013 (I’ve seen about equal odds for Froome 2013 as Pogacar this year). In fact, that’s still true looking at all grand tours back to that 2013 TDF, so Pogacar’s as big a grand tour favorite as we’ve seen in 26 straight races.

If you average each rider’s top 7 GC performances in the last three years – using Pro Cycling Stats points system – Roglic and Pogacar come out well ahead of the competition, but close to one another. The 300+ points accrued by this scale is approximately what Roglic entered last year’s race at and similar to where Chris Froome entered the 2017 edition. Froome entered the 2018 Tour at over 400 points on this scale.

Rider	Average PCS Points of Top 7 GC Performances
Primoz Roglic	333
Tadej Pogacar	306
Geraint Thomas	202
Adam Yates	189
Enric Mas	184
Jonas Vingegaard	179

In fact, whatever way you slice and dice it, Roglic and Pogacar have gained points in GC races at nearly identical rates. So why is Pogacar such a massive favorite?

My hypothesis is that Pogacar has shown himself more capable of putting out truly dominant performances. I’ve generated a quick method to find the most dominant stage race performances in recent years. What I’ve done is strip out riders in the breakaway, and then take the average seconds gained over other top riders in the stage. We’re trying to identify performances like Chris Froome’s multi-mountain raid in Stage 19 of the 2018 Giro where he won by 180 seconds over 2nd place.

Indeed, among grand tour stages since 2018, Froome’s victory in that stage rates #1 with a weighted average of 273 seconds over the chasers. Pogacar’s Stage 8 victory in last year’s Tour ranks #2, and Richard Carapaz on Stage 14 of 2019 Giro ranks #3. That’s a pretty good short-list of dominating efforts – basically multi-climb mountain raids.

Expanding out from grand tours, Pogacar also has >60 seconds gained dominant performances on Stage 6 of 2022 Tirreno Adriatico, Stage 20 of 2019 Vuelta, the Stage 20 Time Trial in 2020 Tour de France, Stage 5 of 2021 Tirreno Adriatico, and Stage 9 of 2019 Vuelta. That’s a total of six massive efforts in three years which won him four races and produced his shock podium at 2019 Vuelta.

In the same time period, Roglic has just three similar efforts – all in the final week of the 2021 Vuelta on Stages 17, 20, and 21 (and that Stage 20 effort was a group effort with other riders). Roglic just has not shown the ability to produce massive race-winning efforts nearly as often as Pogacar relying more on a very strong time trial and late attacks on climbs.

Of course, looking physiologically it’s also possible Pogacar just has more watts available for longer than Roglic. CronosWatts.com produced a phenomenal article comparing the two riders over their careers back in March, looking at their best climbing performances and the times and watts per KG they produced. I’ve overlayed their two graphs showing the two riders with Roglic represented by the green trend line and Pogacar in blue.

Frederic Portoleau’s conclusion:

The 2 Slovenians have a very similar level in the mountains for durations of effort of less than 25 minutes. For the long climbs, a small advantage for Pogacar. On a climb like Alpe d’Huez Pogacar must be able to achieve a time of 38min30sec or a little less in the event of maximum effort. Roglic for his part, has the potential to climb Alpe d’Huez in 39 min.

Frederic Portoleau from https://www.chronoswatts.com/news/203/

Perhaps you can argue Roglic is faster on the sub 10 minute climbs which might allow him to steal some time on the finishes of stages 6, 8, 9, and 14, but overall they are even on efforts like those faced on Planche de Belles Filles on Stage 7 and Peyragudes on Stage 17. Pogacar has the advantage on climbs like Col du Granon (Stage 11), Alpe d’Huez (Stage 12), and Hautacum (Stage 18) – at least using these historical values.

The same site has published summaries of 2020 and 2021 Tours with major climbs. Unfortunately they don’t include the Planche de Belles Filles time trial in 2020 or the full Ventoux ascent where Pogacar was dropped by Vingegaard and lost 40 seconds in 2021. They also include non-competitive climbs like Stages 6/16 in 2020 where GC riders were not riding full gas. Looking at the summary Average Standard Watts Pogacar beat out Roglic by maybe 0.5% in 2020 and Vingegaard by about 2% in 2021. The missing data works against us here, but just using their times in lieu of power estimates, Pogacar rode 8% faster than Roglic on Planche de Belles Filles and Vingegaard rode full Ventoux ascent 1% faster than Pogacar. Combining those values with other climbs says Pogacar has been about 1.5% better over the last two Tours. That seems like enough to call him a clear favorite.

Teammates

The Pogacar vs Jumbo-Visma battle won’t just be confined to those three riders; depending on tactics we could see one of Jumbo-Visma, UAE Team Emirates, or even INEOS Grenadiers try to control the race by leveraging their teams. In fact, we could see this early on potentially windy stages like 2, 3, and 4 or the cobbled stage 5.

I’ve ranked team quality on x-axis of who has the better time trial riders and y-axis of who has the better classics/one day riders. This might give us an indication of who is best setup to support their riders on the flat or hilly days where there is wind or cobbles in play.

Jumbo-Visma is the clear leader here as they have very strong time trial riders supporting Roglic like Van Aert and Vingegaard while also having strong classics riders like Laporte and Benoot. UAE is one of five strong teams behind Jumbo-Visma along with INEOS, Quick Step, and Bahrain, and BORA. Advantage Jumbo-Visma, but this isn’t a chasm like between Jumbo and Movistar.

Moving to the mountains, during the last two Tours there’s been a lot of talk about Pogacar’s team not being strong enough to support him, while Jumbo-Visma has been seen as a super team with multiple GC contenders lining up to support Roglic. Measuring a climbing domestique’s ability to support GC riders is still definitely not a solved problem, but I’ve tried leveraging my rider ratings which identify how good riders are at racing certain parcours based on their finishing position. Lower values below indicate better expected finish positions across the top 4 support riders on each squad.

Team	Average of #2-5 Climbers	Team Climbing Rank
2020 Jumbo-Visma	12.4	1st
2020 UAE	15.6	4th
2020 INEOS	15.8	5th
2021 Jumbo-Visma	11.8	3rd
2021 INEOS	11.0	1st
2021 UAE	16.5	4th
2022 Jumbo-Visma	9.7	1st
2022 UAE	12.8	2nd
2022 INEOS	15.5	4th

In 2020, Jumbo-Visma had by far the best climbing domestiques to back up Roglic and they rode a defensive race which delivered Roglic to the final time trial with a minute advantage. Roglic’s teammates could only watch as Pogacar made up the difference and won the Tour.

Last year, Jumbo-Visma again had a wide advantage over UAE, though INEOS was strongest, but a strong team was less important after Pogacar’s incredible first week and the team had an easy job to protect a five minute lead after nine stages.

This year, Jumbo-Visma will again have an advantage over UAE, but only because of how much stronger their lineup is this year. Both squads have improved vs 2020 and 2021. Sepp Kuss is likely the best pure climbing domestique in the race – ranking 14th in my climber rating – which will allow Jumbo-Visma to have something like three of the final 15 riders in the lead group. UAE added veterans Marc Soler and George Bennett over the offseason which should give Pogacar’s team something like 5 riders in the last 40 riders in the lead group compared to just two in 2021.

Other Contenders

Based on betting odds and making reasonable assumptions about where the vig is on the GC winner market, books are pricing Pogacar, Roglic, and Vingegaard at something like 80% for one of them to win. That leaves about a 20% chance of a big surprise whether from a former winner like Geraint Thomas, a perennial contender like Yates or Quintana, or one of the younger crowd of podium contenders like Vlasov or Enric Mas.

Contenders other than Roglic, Pogacar, Jonas	Implied Probability of Winning
Geraint Thomas	3%
Daniel Felipe Martinez	2.5%
Aleksandr Vlasov	2%
Ben O’Connor	1.5%
Enric Mas	1%
Jack Haig, Damiano Caruso, Adam Yates	<1%
Jakob Fuglsang, Romain Bardet, Nairo Quintana	<1%
Alexey Lutsenko, David Gaudu, Rigoberto Uran	<1%

This gives INEOS perhaps a 6-7% chance of winning their first Tour in three years. Thomas has just won the Tour de Suisse – one of two big warm-up races, but only after the favorite Vlasov left with a positive Covid test. Martinez had an incredible spring with a win in the Tour of the Basque Country and podiums after two other big races, but looked undercooked at the Suisse warmup and has a best grand tour GC result of just 5th. The final INEOS rider Adam Yates ranks as the third best performing rider on climbing stages in the race, but has just two 4th places in his GC career largely due to a poor time trial and big drop-off in performance in later stages of races.

Of the remaining riders, Mas, O’Connor, and Haig will likely be done in by the 40km time trial on stage 20 where they could easily lose two minutes plus to the Slovenians/Vingegaard. O’Connor was the final rider dropped by Roglic/Vingegaard on the final stage of the Dauphine tune-up race and while he finished 4th last year, he benefitted from gaining 6.5 minutes on other GC riders in a breakaway and likely wasn’t the 4th best rider in the race.

Vlasov has a string of strong week-long GC performances in the spring including a massive win in the Tour de Romandie mountain time trial, but he left Tour de Suisse with Covid. If he’s back on form he has a decent podium chance as his team support ranks 3rd best in the mountains with a strong squad of Austrian/German climbers.

One of the biggest stories leading into the 2022 Tour de France was whether Quick Step will select young sprinting star Fabio Jakobsen or 34-time Tour de France stage winner Mark Cavendish to lead them on sprint stages. That was resolved today with Jakobsen’s selection. That significantly clears up what should be a very compelling sprint battle between two young stars – Jakobsen and Alpecin’s Jasper Philipsen – and a host of veterans including Caleb Ewan, Dylan Groenewegen, Peter Sagan, and Wout van Aert.

Who are the best sprinters?

I’ve written this year about my Bunch Sprint Model which evaluates sprinting success based on finishing position solely in sprints a rider contests while also considering the strength of opposition a riders sprints against again considering only those opposing sprinters who contested the sprint. You can read more about methodology and results at this link. Think of this model as looking to identify the best sprinters if they all had a chance to sprint against one another.

Back in February this model loved Fabio Jakobsen due to a very high hit rate in sprints he actually contested. Since then, Jakobsen has continued to sprint at a high level with six wins on a variety of parcours, while Jasper Philipsen performed very well at UAE Tour and then hasn’t done much since. This model evaluates the two of them as neck-and-neck on top of the sprinting world.

Behind them, the model rates Cavendish 3rd and Olav Kooij 4th. Cavendish failed to be selected, while Kooij also couldn’t rate selection on Jumbo-Visma’s GC focused squad. Caleb Ewan (5th) and Wout Van Aert (6th) are the other two elite sprinters at this year’s Tour. Van Aert has only participated in a bunch sprint seven times in 2022, but six have been podiums.

Further down the list are veterans like Alexander Kristoff, Dylan Groenewegen, Peter Sagan, and Mads Pedersen. Kristoff landed Stage 1 and the yellow jersey in 2020, but hasn’t won a World Tour sprint since. Sagan has had multiple covid bouts, but finally landed his first win in Tour de Suisse a few weeks ago. Pedersen might be more of factor on the more classics-like finishes as three of his five 2022 victories have come on either uphill finishes or finishes with a small climb right before the finish.

Groenewegen has been a bit in the wilderness due to his suspension, being eclipsed by younger riders at Jumbo Visma, and his subsequent transfer to Bike Exchange. He’s won five times this year, but has only a single podium finish in World Tour sprints. He’s actually won his last three contested sprints across three sub-World Tour races, but was dropped on several climbs in Dauphine and left that race without contesting a sprint.

The only other sprinters it makes sense to mention are Team DSM’s Alberto Dainese and Bike Exchange’s second sprinter Michael Matthews. Dainese won a shock victory in Stage 11 of the Giro, but doesn’t have another finish better than 5th in a sprint all year. Matthews is really more of a tough parcours sprinter at this point in his career as his only wins since 2020 have come in one day classic Bretagne Classic and on a tough stage of the Volta a Catalunya this spring.

Ewan’s Lotto Soudal Team Changes Strategy

Caleb Ewan’s Lotto Soudal team has a well established approach to grand tours since landing Ewan in 2019. They’ve brought the 6th, 2nd, and 2nd heaviest lineups to the last three Tours de France and 4th, 5th, and 4th heaviest to the 2019, 2021, and 2022 Giros – driven by big engines like Roger Kluge, Jasper De Buyst, and Thomas De Gendt. Beyond the size of Ewan’s teammates, they relied on experienced riders to back Ewan, regularly trotting out lineups where 3-4 riders had ridden 25+ bunch sprints with Ewan in recent seasons. That element will be different in 2022 as while they will again have one of the heaviest starting squads, Ewan’s teammates have very little experience supporting him in sprints. Riders like Kluge, De Buyst, and recent additions Michael Schwarzmann and Rudiger Selig were left out in favor of more classics focused engines like Frederik Frison and Florian Vermeersch. It will be interesting to see if their tactics shift more towards Ewan surfing wheels rather than utilizing a big sprint train.

Philipsen’s Rise

Jasper Philipsen was always a highly touted sprinter, landing three World Tour stage wins before his 23rd birthday, but he was squeezed out of UAE Team Emirates by veteran sprinters and the team’s GC focus around Tadej Pogacar and transferred to Alpecin for the 2021 season. There he has blossomed into potentially the best sprinter in the pro peloton thanks to a massive 2021 season.

His 2021 story was inextricably tied to Mark Cavendish as he was Cav’s main opponent in his breakout Tour of Turkey in 2021 (Cav landed four wins to Philipsen’s two) and again he kept coming up short to Cavendish in the Tour de France where Philipsen reeled off six stage podiums, but couldn’t score a win. Philipsen followed up the Tour with two Vuelta stage wins and four one day race wins, including on cobbled terrain. If the cobbled stage 5 turns out to be less vicious than expected it wouldn’t be a surprise to see Philipsen sprinting for the win as he’s handled similar terrain in the past.

Bike Exchange All in For Groenewegen

Before Bike Exchange’s team announcement there was all possibility of them sending a balanced team to chase GC or stages with Simon Yates, but instead they’ve gone all in on Groenewegen and Matthews as of their announced team only Nick Schultz is anything of a climber. They will likely have the heaviest lineup at the Tour at 73.75 kg; that would also be the heaviest of any team at the Tour since Lotto Soudal’s 2016 team built around Andre Greipel and his sprint train. Bike Exchange will hope that extra power will allow them to keep Groenewegen up front during potentially windy stages 2, 3, and 4.

Team	Average Weight of Riders in KG
Bike Exchange	73.8
Alpecin	73.0
Lotto Soudal	72.6
Quick Step	71.5
Bahrain	70.8

Fabio Jakobsen + Michael Morkov

Michael Morkov’s dominance as a leadout man has been well established in recent years as he’s guided Sam Bennett and Mark Cavendish to back-to-back green jersey wins and six Tour de France stage wins. Of course combining him with Fabio Jakobsen should produce good results. However their success in 2022 has been massive with Jakobsen winning five of seven sprints he has contested with Morkov in the lineup.

It’s difficult to know which are the best leadout riders on Quick Step as the team is just phenomenally well drilled overall, but it seems like Jakobsen has ridden more with the ‘B’ team than the elites. Since last July when Jakobsen started sprinting again he’s ridden most often with Florian Senechal and Bert Van Lerberghe in bunch sprints. On the other hand, Cavendish has been most often deployed with Morkov and Davide Ballerini.

I’ve written in the past about how tough it is to evaluate sprint helpers and that the best guide may just be to look at how teams deploy riders in different races. With a start in 2022, Morkov will now have raced four straight Tours for Quick Step (2019-22) – as well as the 2022 Giro with Cavendish. Compare that record to Senechal and Van Lerberghe. Senechal has ridden just two grand tours (neither the TDF) in that time period, while Van Lerberghe has similarly raced just two grand tours and won’t feature in this TDF either. While Quick Step’s full sprint train might be a bit lighter than past years, combining Jakobsen with Morkov could still produce tons of success.

Van Aert’s Green Jersey Bid

Van Aert appears to be a massive favorite for the green jersey points competition as his odds – even after a minor injury last week – sit at 1.65 (implied at around 56%). He benefits from a race bereft of many true sprint stages (only four are evaluated in the Tour regulations as flat stages: 2, 3, 19, 21) where true sprinters could challenge him, while there are also a lot of classics-esque and medium mountain stages where he should find great success from a reduced peloton.

Year	Stages evaluated as flat by organizers
2022	4
2021	8
2020	7
2019	7
2018	7

This graph above shows the result of a model which considers whether a rider was able to survive in the group and sprint for the win (finish in top 25 in a bunch sprint race) depending on the climbing difficulty of the parcours. Something like stage 6 into Longwy or stage 8 in Lausanne would rate a 5.5 on this scale, while the flat stages 2 and 3 would rate <1. Stage 10 which features a long, shallow drag to the finish in Megeve would rate just off this scale ~8.5.

Van Aert, Matthews, and Philipsen show fairly consistent ability to stick with the front group as climbing intensifies, but the other sprinters show degraded abilities on tougher terrain – particularly Jakobsen and Groenewegen.

It will be a huge advantage for Van Aert that he has been >85% to survive to the sprint finish regardless of the difficulty of the climbing that day. His ability to survive on those tougher sprint days like stages 4, 6, 8, 13, and 15 and to even get into the break on harder days will make him tough to defeat.

Looking at the last 10 points competitions, we can split up the source of points between finish-line sprints and intermediate sprints. Finish-line sprints can be accrued by being a great bunch sprinter, while intermediate sprints can be accrued by getting breakaways or by tactically out-sprinting opponents on the road. In the last 10 competitions, the green jersey winner ranked 1st in points from finish-line sprints 8 times and 2nd twice. The record on intermediate sprints was more mixed with Kittel, Cavendish, Bennett, and Sagan twice taking green without gathering the most intermediate sprint points. We haven’t recently seen someone take green by dominating intermediate sprints and not being one of the two best on finish-line sprints. Will Van Aert be one of the two best sprinters on finish-line sprints?

If not, the market shows Jakobsen and Philipsen as the best odds among pure sprinters. Jakobsen won the points jersey at 2021 Vuelta and might look to follow Cavendish and Bennett and Quick Step green jersey winners. Philipsen was fairly close to Jakobsen in points competition when he abandoned Vuelta, but he managed only 4th in green jersey race in 2021 Tour de France due to hardly contesting intermediate sprints.

I introduced a very basic model for rating riders two months ago which simply took the natural logarithm of finishing rank in each race to make the stat Log Rank. At the end of that piece, I introduced a way to model Log Rank over long time periods to find whether riders a) achieve better or worse finishing ranks overall, b) achieve better or worse ranks in bunch sprint finishes, and c) achieve better or worse ranks in races with a lot of climbing. That ranking model does a good job of distinguishing riders who are expected to perform better or worse in bunch sprints, but not a great job at distinguishing truly great from merely good sprinters.

The issues with that Log Rank model are: 1) it considers all different parcours of races in building the overall impact data point, not just races ending in bunch sprints, 2) it considers all bunch sprints for a rider, even those where a heavier sprinter was jettisoned a climb and failed to participate in the sprint finish, 3) it considers bunch sprints where a rider was present in the bunch, but was actually helping a teammate (eg, Davide Ballerini often sprints for himself in smaller races, but is in the sprint train for bigger ones), and 4) it doesn’t consider the quality of the sprinters participating alongside each rider in the sprint (ie, the competition on that day may be much reduced by tougher parcours, mechanicals, crashes, or splits in the bunch).

So how to account for these issues. First, we want to just evaluate sprinters based on bunch sprint finishes. Anything which doesn’t end in a bunch sprint is ignored by this new model. Second, we want to ignore any race for a rider where they didn’t finish with the first group in the sprint AND in the top 25 positions; this indicates they were capable of sprinting. Third, we want to ignore any race where a rider wasn’t the top finisher on the team. Many riders participating in as a lead-out man can rack up 10th place finishes which can pollute our understanding of them as sprinters in races where they compete as team leader. And fourth, we consider the cumulative strength of the sprinting field which meets these first three criteria based on the simple Log Rank model outputs.

Determing strength of sprinting field

How does point #4 above work in practice? Seventeen sprinters in UAE Tour stage 1 on Sunday qualified for these criteria including the top 13 finishers. My basic Log Rank model predicts following finishing positions in a generic strong race for those seventeen riders.

Rider	Predicted Rank
Jasper Philipsen	3.0
Arnaud Demare	3.2
Sam Bennett	3.3
Pascal Ackermann	4.0
Dylan Groenewegen	4.9
Elia Viviani	6.9
Mark Cavendish	7.0
Marijn van den Berg	9.3
Olav Kooij	9.6
Marc Sarreau	10.1
Rudy Barbier	10.8
Max Kanter	16.5
Emils Liepins	27.7
Jonathan Milan	29.7
Tom Devriendt	34.5
Michael Schwarzmann	35.2
Jonathan Canaveral	47.3

A lot of very talented sprinters were in this race – including seven with an expected finishing rank of 7.0. Compare to stage 1 of Tour of Oman where the top sprinters were Fernando Gaviria (5.0), Mark Cavendish (7.0) and no one else with a predicted rank better than 10.0.

To determine the cumulative strength of sprinting field, I just take the reciprocal of each rider’s predicted log rank (1 / predicted log rank) and add them together. A top sprinter like Bennett or Philipsen will contribute 1/3 or 0.33 points while someone with a very low prediction like Canaveral or Schwarzmann will contibute 1/40 or 0.03 points.

The top races for sprinters tend to be the Tour de France, Milano-Sanremo, Paris-Nice, and UAE Tour with cumulative strength of sprinting fields around 3.0 to 4.0 depending on the specific day. World Tour races in general average just under 2.0, with a wide range, while .Pro races average just above 1.0, again with a wide range. The lowest pro races at .1 level tend to average just below 1.0 with hardly any rating better than 1.5.

With that data calculated, it is simple to specify a model using this strength of sprinting field and rider to predict both finishing rank and whether a rider won the sprint. Both of these models find 1) the impact of individual rider on success metric and 2) a potentially non-linear impact of the cumulative strength of sprint field.

To Predict Finishing Rank:
gam(log(finish_rnk) ~ rider + s(strength_sprint_field))

To Predict Win:
gam(win ~ rider + s(strength_sprint_field))

I ran both models for this example on data since the start of 2020, only considering riders who participated in at least 16 sprints meeting the criteria laid out above. This ranged from Wout Van Aert with 19 sprints to Philipsen/Ackermann with 45.

Who is the top sprinter in early 2022?

Both models produce similar results given the data. Fabio Jakobsen is seen as the most likely sprinter to win a given race and the sprinter who will finish with the best finishing position overall. For example, in a typical World Tour level sprint the models predicts Jakobsen to win 53% of the time and finish an average of 1.9. Wout Van Aert is predicted 2nd in win probability at 44% and 4th in finishing rank at 2.7. Sam Bennett is tied with Caleb Ewan for 3rd in win probability at 38%, but slightly ahead of him for 2nd place in finishing rank at 2.2. Ewan is predicted at 2.6 in finishing rank.

Those four comprise a fairly clear top group with Jakobsen fairly clearly the #1 sprinter in the world. Behind those four are guys like Philipsen, Groenewegen, Cavendish, and Demare. As a sign of his diminished form in recent years, Peter Sagan ranks outside the top 25 in predicted win probability and 15th in predicted finishing rank.

Fabio Jakobsen

Looking at the data in this way it’s obvious why Jakobsen is the top predicted sprinter while ranking only fifth in the PCS Sprinter Ranking and 14th (!) in my own basic Log Rank model. Jakobsen had three week long stage races in his comeback from serious injury last year where he didn’t compete as a sprinter. Basically, the basic Log Rank model sees a guy who was “awful” at sprinting for a dozen sprints. But, when we restrict just to races where he was the team leader and he was in the sprint pack, the graph below shows he has been dominant.

Jakobsen is winning nearly 70% of his sprints where he is the leader and is contesting the sprint since the start of 2020. That blows everyone else away, with Van Aert and Ewan managing only a mid 40% win rate in that time. Jakobsen has raced lesser competition than guys like Van Aert, Ewan, and Bennett, but he’s dominated that competition.

One of the big stories of this and last cycling season is Mark Cavendish’s return to massive success with Quick Step, including tying the record for career Tour de France stage wins. He has twelve wins since the start of 2021 – including two this season – and easily rates as a top 10 sprinter in the world right now. Because he and Jakobsen race for the same team, only one of them is likely to make the Tour de France team where Quick Step sprinters have been steered to 14 sprint stages in the last five races. Unfortunately for Cavendish, Jakobsen isn’t simply just another top 10 sprinter – he’s the best in the world right now.

Pro cycling teams have to juggle a lot of goals: for the season, for a stage race, for an individual race. They also need to juggle ambitions of ~30 riders of varying levels of experience and skill. In most races, teams only ride for a designated leader or maybe 2-3 designated leaders. Based on the parcours and who is performing best, teams decide who are the protected leaders and who will be riding in support in each race.

As we move into a new season, teams have hired new riders and let others go. I had a go at making some basic projections on how teams strengthened or weakened their squad with transfers, age based regression, and natural regression/progression in points earned. One of my caveats in that article was that the projections did not account for team strategies or rider schedules based on transfers. There are only so many leadership positions to go around and teams who hire more leaders are at risk of needing to demote some leaders to support roles in certain races.

In this piece I define “leader” as the top finisher for a team in a race. Of course the top finisher is not always the rider(s) who were designated as the leader at the beginning of the race. However, the top six riders in % of races as leader in 2021 were Nairo Quintana, David Gaudu, Giacomo Nizzolo, Guillaume Martin, Aleksandr Vlasov, and Tadej Pogacar so I think it’s a reasonable proxy.

How This Plays Out For Teams

A quick example, UAE Team Emirates transferred in five major signings who spent at least some races in 2022 as their team’s leader – sprinters Pascal Ackermann and Alvaro Hodeg and climbers Joao Almeida, George Bennett, and Marc Soler. They transferred out four major riders who spent some races as leaders – sprinter Alexander Kristoff, climbers Joe Dombrowski, and David De La Cruz, and puncher Sven Erik Bystrom. Five in, four out. The riders leaving were UAE’s #1 rider on a race day 52 times. The riders coming in were their team’s #1 rider on a race day 76 times. UAE also hired wunderkind climber Juan Ayuso who was the leader in a race – primarily at U23 level – 17 times in 2021. In total, they raced 233 times in 2021 and the riders on their team for 2022 were the #1 rider on their team 288 times – a surplus of 55 races.

We can repeat that same calculation for the other 17 World Tour teams and actually most teams have a surplus; 11 have at least 7% more leaders in their team than 2021 race days, another 5 are within +/- 3%, and only Lotto Soudal (6% fewer) and DSM (13% fewer) aren’t equal or with a surplus. Overall, the surplus is 12% at World Tour and 8% at Pro Tour level. This makes total sense. Teams tend to discard riders who don’t have the capacity to be leaders anymore and hire those that do as a natural progression of the sport. However, some teams are legitimately going to be squeezed for leadership opportunities in 2022 – even if we don’t see Covid related cancellations like the prior two years.

EF Education is probably the most over-subscribed in terms of leaders. They hired riders who were team leaders 102 times in 2021, but got rid of riders who were team leaders just 36 times in 2022 – a surplus of 66 races. Their issues might not be as extreme as represented here as many of their additions come from non-World Tour level teams and/or are developing riders who might need a year before becoming full-fledged leaders. In fact, only 77% of the 2021 leaders on EF came while racing for a World Tour level team (86% is the average for the full World Tour).

All Leaders Aren’t Equal

We need to account for the difference acquiring a leader like Giacomo Nizzolo (who finished 1st on his team 60% of races at World Tour level) and one like Marijn Van Den Berg (moving to aforementioned EF Education) who led his team in 45% of races at U23 level. If we arbitrarily assign a weight of 1x for leaders while riding for World Tour teams, 0.67x for leaders while riding for Pro Tour teams, and 0.33x for any other leaders, we can get a better idea of how much competition there will be for leadership roles. At EF, they now rank third with a surplus of about 18%. The World Tour in general averages a 3% surplus by this method.

Doing that weighting shows BORA and Jumbo Visma as the two with the most competitive leadership competitions. BORA ranked 4th best in adding talent through transfers per ProCyclingStats and 2nd best at adding talent by my projections. They added climbers Aleksandr Vlasov, Jai Hindley, and Sergio Higuita who combined to lead their team 62 times in 2021, and sprinters Danny Van Poppel and Sam Bennett who combined to lead 41 times. Sprints-wise, they should be fine as they’re also losing Peter Sagan and Pascal Ackermann (47 races as leaders) and Van Poppel has also said he’s switching to support Bennett.

Where BORA will see the squeeze is in general classification and hilly/mountain stage leadership. Just filtering to leadership in hilly/mountainous races, BORA rode 94 races in 2021, while their currently employed riders were leaders of their team in such races 146 times! That’s a greater than 50% surplus – far beyond any other World Tour team.

Flip that around to flatter/classics races and Jumbo Visma looks to be the team with the most issues with too many leaders. Despite moving star sprinter Dylan Groenewegen onwards, they’ve still a tight squeeze. They have a surplus of 36% due to adding Christophe Laporte (punchy sprinter), Tosh Van Der Sande (leadout man), and Tiesj Benoot (classics rider). What looks most likely is that those three will simply sacrifice more of their own ambitions to support Wout Van Aert in classics and young sprinters like David Dekker and Olav Kooij in flatter races.

I wrote in my 2022 team projections piece about DSM’s losses in the transfer market. They were especially hard hit in the climbers/GC riders department where they lost Michael Storer, Jai Hindley, Tiesj Benoot, and Ilan Van Wilder. Those four combined to lead in 34 of DSM’s 102 hilly/mountainous races in 2021 and the other transferred out riders combined for 9 more for a total of 42% of DSM’s races being led by riders leaving the team. They only added a sprinter – John Degenkolb – from a World Tour team, with the rest of their additions coming from lower level squads. Still on the team is Romain Bardet (leader in 63% of hilly/mountainous races he entered), but no one else who led in more than 20% of their hilly/mountainous. In races without Bardet, they’ll be handing out leadership opportunities to their wide array of young climbing talent and hoping for quick development.

Competition for Leadership vs Depth/Optionality

The flip-side of framing this as an issue of too many leaders is that talented riders who were leaders in smaller teams can now move up and support superstars like Van Aert. The team also has cover in case of injury; for Jumbo Visma, if Van Aert suffers an injury their spring classics season isn’t completely ruined as they can plug in competent classics riders like Benoot or Laporte.

Bora-Hansgrohe Grand Tour plans:

🇮🇹 Giro: Hindley, Kelderman, Buchmann
🇫🇷 Tour: Bennett, Schachmann, Grossschartner, Vlasov
🇪🇸 Vuelta: Higuita

— Daniel Friebe (@friebos) January 17, 2022

BORA just released their preliminary plans for the three grand tours, but they also have the option within those plans to either leave off a rider who is struggling with form or choose to fully back a rider in strong form for GC. Between Buchmann, Vlasov, Kelderman, Hindley, and Schachmann they have riders who have finished 4th in Tour de France, 4th in the Giro, 2nd/3rd in the same Giro, and won a World Tour stage race in back-to-back years. And that ignores Higuita, Konrad, and Kamna who have won grand tour stages in the last three years. There’s definitely option value there in knowing that you can select the best of that bunch for your main focus in major races.