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Tag: ski speed

Cool ways to measure and display ski speed in biathlon

Posted on 2022-02-04 | by biathlonanalytics | Leave a Comment on Cool ways to measure and display ski speed in biathlon

Introduction

The ski speed in biathlon is measured and displayed in many different ways. This article makes an attempt to review those different ways and come up with a “best way” to display ski speed, as I believe that some of the current options make ski speed hard to understand. The goal is to have a clear measure and display unit that is understandable to both die-hard biathlon fans as well as the occasional biathlon watcher.

It is also important to know that I looked at these different options from both a per-race and a seasonal-average perspective.

Lastly, I want to emphasize that whatever I end up with, none of the options is bad or wrong, and I definitely don’t want to claim I have all the knowledge to make a final decision on what is best. This is my take, and I look forward to further discussing this topic.

Data

One way or the other, all the data eventually comes from the IBU data center. Here, the IBU provides race times, ski times and course times in different formats but all from the same source. Their data is tracked and collected by Siwidata by the use of trackers that all athletes get wrapped around their ankles and data collection points along the track.

Time data

The competition analysis report, available directly from the IBU data center, combines all the time information per athlete per loop and combined:

Course data

Also important for some calculations described further down in this article is that we have a total course length for the event, and this includes the skiing tracks as well as the range section:

Unfortunately, we do not have data for just the skiing part of the track versus the range part of the track. But when we take into consideration that there typically are 30 lanes of 2.75-3m width, and the range includes 10m on either end, we can guesstimate that the range length is about 110m long. This is a very small part of the total course length (even for a sprint it is 1%). And since we don’t have a better alternative, the total course length is used in the calculations for some of the measures further down in this article.

Course map

The following image clarifies what parts of the racetrack are considered course time, range time and penalty time:

It should be noted that a small section of the penalty loop overlaps with the “normal” track, which explains why every athlete will have a couple of seconds of penalty time per loop, even if they shoot clean. Important to note here is that for ski speed in biathlon, we use only the course time data.

Time data, part II

All races have data for the total race time and the course total time, as well as the penalty time for all races except the individual race discipline which uses the ski time:

  • Race time (above with the header “Finish”) typically called Loop time is the total time from start to finish, including range and penalty time;
  • Ski time is the Race time minus the one-minute penalty times in individual races (other race disciplines do not have ski time data);
  • Course time is the total time skiing, excluding time on the range and in the penalty loop. This is the data used for measuring how fast the athletes were skiing.

Measurements

The following is a list of measurements based on the data described above, currently used in the “biathlon world”. I try to give some pros, cons and comments on each of them.

  • Seconds behind: absolute measure of the distance between athletes in seconds behind the fastest skier at the finish line
    • Good way to show actual time distance between the athletes at the finish
    • Doesn’t work well for aggregating multiple race disciplines as 10 seconds behind on the sprint is different than 10 seconds behind on the individual
  • Seconds behind leader per 1,000 meter: absolute measure of the distance between athletes in seconds behind the fastest skier per 1,000 meters
    • This normalizes the distance between athletes in seconds so it can be aggregated between multiple race disciplines
    • Uses total course length to calculate
    • Used by the IBU in biathlon information
  • Seconds behind per penalty loop: absolute measure of the distance between athletes in seconds behind the fastest skier per 150 meters, the length of a penalty loop
    • Same as previous but normailzes to a distance people, both die-hard and occasional fans, can easily relate to
    • Can be aggreated between multiple race disciplines
    • Numbers can get very small
    • Uses total course length to calculate
  • Per cent behind, or per cent back: relative measure of the distance between athletes in a percentage of the ski time of the fastest skier
    • Fastest athlete is always 0%
    • There is no range for percentages; the slowest in one race can be +33% where in other races it can be 50%
  • Per cent of average ski speed (of the whole field): relative measure of the distance between athletes in a percentage of the average ski time of all skiers
    • Average ski time (0%) includes every athlete from best to worst
    • You don’t really know how fast or slow someone is, as you don’t know the minimal and maximum percentage values
    • The negative values (-3.4%) represent being faster than average so a positive result
  • Per cent of the average of top 5/10/30 skiers: relative measure of the distance between athletes in a percentage of the average ski time of the top 5/10/30 skiers
    • Average ski time can be focussed only on top 5/10/30 skiers
    • This can level the field when comparing sprints (over 100 athletes) to mass starts (30 athletes)
  • Meters behind leader: absolute measure of the distance between athletes in meters behind the fastest skier on the total course length at the finish line
    • Apparently the way Siwidata now measures for the IBU
    • Doesn’t work well for averaging multiple race disciplines as 10 meters behind on the sprint is different than 10 meters behind on the individual for example
  • Meters behind leader per penalty loop: absolute measure of the distance between athletes in meters behind the fastest skier per 150 meters, the length of a penalty loop
    • Same as previous but normailzes to a distance people, both die-hard and occasional fans, can easily relate to
    • Can be aggreated between multiple race disciplines
    • Numbers can get very small
    • Uses total course length to calculate
  • Ski speed: absolute measure of the difference between athletes in kilometres per hour
    • Doesn’t say much about how the speed relates to time difference between athletes
    • Has different effect on race depending on the race distance
  • Ski speed rank: absolute measure of the difference between athletes in the rank in ski speed
    • Fastest is rank 1, slowest is the highest number
    • Downside is that it loses the actual distance between racers. One can be the third ranked skier by two seconds behind the leader or two minutes behind the leader
  • Zscore: computed measure of the difference between athletes in the number of standard deviations by which course times are above or below the mean, based on seconds behind from median of all athletes
    • Can be hard to relate to by all fans
    • Although a precise value, only gives a general sense of someone being faster or slower than the field mean
    • The negative values (-3.4%) represent being faster than average so a positive result
  • Course time: absolute measure of the difference between athletes in the actual course times
    • Gives a good idea of how long the athletes took to ski the track
    • Need to calculate the actual differences
  • Time behind score: relative measure of the difference between athletes on a 0-100% range, where fastest athlete is 100% and slowest is 0%
    • Further explanation can be found in this post

Ways of communicating

Tables

All measures can be shown in a table, which provides a detailed overview of the race results per that specific measure. They are great for looking up specific athletes and giving the exact numbers, but they are harder to interpret quickly and to envision the fastest skiers and how far they are from each other.

Charts

Charts on the other hand are easy to interpret quickly while still proving detailed information per individual athlete (especially when created interactively), and context (see example at end of article) to make it even easier to read.

Description/talking

Probably the most complicated but least considered aspect of communicating ski speed is how it can be discussed. What does it mean when someone says Laegreid was -2,6% from the average, Latipov was 13 seconds behind, Boe was 16 meters behind, Lesser was 3% back, and so on? For die-hard biathlon fans this may make sense for those who are “into data”. For those who just love to watch biathlon and casual fans, I believe this way of describing ski speed is not very meaningful or useful.

Rankings are clear in the sense to discuss who was faster and slower, but not how much faster or slower. Measures per a relatable distance, like a penalty loop, are easy to understand and visualize for biathlon fans at all levels. They don’t even need to know the actual distance of a penalty loop!

Conclusion

When we take a look at most of the measurements in chart format, we can see that the majority show the same data but just with a different axis and units (the red, orange and yellow icons indicate rank 1, 10 and 30 respectively). And with all charts being equal we can decide which unit of measurement would be the easiest to communicate to all types of biathlon fans while having the ability to aggregate the data for a whole season.

I already mentioned that although Seconds behind, Meters behind leader, and Course time are easy to relate to, they are not ideal for aggregation as race disciplines have different distances. The opposite is the case for Per cent behind, Per cent of average ski speed, and Zscore, as they aggregate well but are not so easy to relate to for all fans. The Ski speed in Km/h is cool in the sense that it makes you realize how fast these athletes go. But it doesn’t say much about the end result (difference between athletes) and it would be hard to aggregate.

Ski speed rank shows a different picture of the data when we put it in a chart. The ski speed rank is easy to relate to and very clear to communicate and aggregate, but it loses the information about the space between athletes.

For both single races and season aggregations, the Meters behind leader per penalty loop is a measure that is easy to understand for any biathlon fan, can be aggregated for a whole season with different race disciplines as it is normalized to a specific distance (150 meters), and it keeps the information on space between athletes intact. And on top of that, it can be visualized in cool ways.

It is also very similar to what the IBU currently uses (seconds behind per 1km) but I think that meters behind are easier to visualize mentally and understand than seconds behind and that it is good to use a distance people can relate to directly. The only downside to using the 150-meter loop is that athletes do appear very close to each other.

What is your preferred way of measuring ski speed? And do you agree or disagree with my comments above? Let’s have a conversation on Twitter, I’d love to hear other people’s perspectives.

Posted in Statistical analysis | Tagged ski speed

Ski speed comparison – 2019–20 vs. 2020–21

Posted on 2021-03-23 | by real biathlon | Leave a Comment on Ski speed comparison – 2019–20 vs. 2020–21

Skiing was once again by far the most important factor to determine an athlete’s eventual World Cup rank. Not only did the two outright fastest skiers, Johannes Thingnes Bø and Tiril Eckhoff win the overall title, but out of the ten fastest skiers (per gender), eight made the World Cup top 10 on the men’s side, six on the women’s side. Let’s look at who managed to improve and whose ski speed declined season-to-season.

You can check out full season statistics for all World Cup athletes here:

  • Ski speed: Men | Women
  • Shooting percentage: Men | Women
  • Shooting Times: Men | Women

For patrons, the comparisons page allows you to compare all shooting and skiing stats on your own, not only season-to-season, but also by trimester.


Note: Only athletes with at least 4 non-team races last season and 15 non-team races this winter are included in the tables. “Back from Top30 median” is the percentage back from each race’s top 30 median Course Time (arithmetic mean per season).


Men

Tuomas Harjula and Jeremy Finello were the most improved skiers this season, both roughly 3.5% faster compared to 2019–20. Erik Lesser had an injury-affected winter last year and bounced back to his previous level. Johannes Kühn, the fourth-fastest skier last season, never managed recover from a pre-season injury and ended the season with the biggest decline among regular starters.

Johannes Thingnes Bø was not as dominating as many expected after the retirement of Martin Fourcade, however, his ski speed was not to blame: he set the top ski time in 20 out of 26 races. Sturla Holm Lægreid improved a lot, albeit he only appeared in four races last winter. Percentage-wise Quentin Fillon Maillet had a big decline in his skiing performances, even though his course times ranks were only 1.9 positions lower and he he finished the season third overall. Émilien Jacquelin‘s average was heavily influenced by the WCHs mass start (+12.1%); without that one race his speed would have been roughly 0.5% better.

NoFamily NameGiven NameNationRacesSki Rank
(avg)
Changeback from
Top30 median
(in %)
Change
NoFamily NameGiven NameNationRacesSki Rank
(avg)
Changeback from
Top30 median
(in %)
Change
1HarjulaTuomasFIN
1760.3-27.7+5.05-3.64
2FinelloJeremySUI
1924.3-34.4+0.84-3.47
3KomatzDavidAUT
2246.4-36.6+3.40-3.32
4LesserErikGER
2320.6-28.6+0.50-3.07
5PonsiluomaMartinSWE
268.8-18.3-1.16-2.68
6DovzanMihaSLO
2060.4-20.3+5.26-2.47
7SamuelssonSebastianSWE
2612.0-16.7-0.71-2.17
8LaegreidSturla HolmNOR
2611.2-12.3-0.79-2.16
9LatypovEduardRUS
2517.0-19.0+0.14-2.10
10SmolskiAntonBLR
2225.7-17.0+1.03-1.71
11BocharnikovSergeyBLR
2235.0-14.2+2.09-1.59
12BrownJakeUSA
1731.3-16.0+1.72-1.46
13SimaMichalSVK
1671.1-14.4+6.06-1.31
14GowChristianCAN
2150.1-11.6+3.50-1.24
15HoferLukasITA
269.4-6.3-1.04-1.15
16LangerThierryBEL
1854.6-5.5+4.08-1.03
17DombrovskiKarolLTU
1762.6-7.7+4.92-1.00
18FakJakovSLO
2622.7-7.3+0.70-0.99
19DaleJohannesNOR
265.5-4.4-2.00-0.82
20NelinJesperSWE
2316.2-8.4+0.16-0.79
21StvrteckyJakubCZE
1931.8-6.0+1.61-0.77
22VarabeiMaksimBLR
2041.4-10.3+3.12-0.74
23DudchenkoAntonUKR
1558.5-2.9+4.37-0.64
24GuigonnatAntoninFRA
2522.2+0.2+0.60-0.54
25MukhinAlexandrKAZ
1571.5-3.0+5.85-0.50
26ChristiansenVetle SjaastadNOR
2214.7-2.5-0.37-0.37
27WegerBenjaminSUI
2426.7-2.0+1.21-0.36
28PeifferArndGER
2113.9-1.7-0.39-0.34
29NordgrenLeifUSA
1759.4+1.9+4.40-0.30
30DohertySeanUSA
1947.6-1.9+3.32-0.26
31EderSimonAUT
2633.9-1.6+2.00-0.25
32BormoliniThomasITA
1843.2-3.6+2.96-0.23
33KrcmarMichalCZE
2027.3+0.1+1.28-0.20
34BoeTarjeiNOR
266.4-1.6-1.52-0.20
35BoeJohannes ThingnesNOR
261.7-1.3-3.10-0.20
36SeppalaTeroFIN
2128.0+0.1+1.17-0.17
37GuzikGrzegorzPOL
1562.5-2.1+4.95-0.06
38RastorgujevsAndrejsLAT
1919.8+2.2+0.42-0.04
39LoginovAlexanderRUS
2417.6+0.2+0.10+0.03
40ClaudeFabienFRA
2517.0+2.0+0.08+0.03
41WindischDominikITA
1924.2+1.6+0.82+0.08
42EliseevMatveyRUS
2533.0+5.4+2.17+0.08
43GaranichevEvgeniyRUS
1836.1-0.2+2.36+0.15
44TrsanRokSLO
1870.1-2.7+6.71+0.26
45JacquelinEmilienFRA
2611.8+0.1-0.22+0.27
46DollBenediktGER
2612.2+2.3-0.72+0.28
47PidruchnyiDmytroUKR
2229.8+5.8+1.57+0.32
48DesthieuxSimonFRA
2615.4+3.1-0.18+0.46
49ClaudeFlorentBEL
1945.4+5.2+3.44+0.49
50MoravecOndrejCZE
1844.6+4.9+3.32+0.50
51PrymaArtemUKR
1937.4+9.0+2.23+0.58
52LeitnerFelixAUT
2328.7+5.1+1.50+0.61
53GowScottCAN
1956.4+5.5+4.30+0.65
54StroliaVytautasLTU
1649.9+7.2+3.62+0.65
55FemlingPeppeSWE
2150.5+2.9+3.94+0.70
56Fillon MailletQuentinFRA
257.6+1.9-1.35+0.72
57IlievVladimirBUL
1731.0+9.0+1.61+0.92
58KuehnJohannesGER
1619.5+12.8+0.34+1.69


Women

Dzinara Alimbekava was the most improved skier in the women’s field, skiing an incredible 5.8% faster than last year and lowering her average ski rank by 49.6! Dunja Zdouc managed to improve even more than her Austrian teammate Lisa Theresa Hauser. Skiing 3.9% faster, Hanna Sola set the fastest ski time twice this winter and made her first two career podiums. After setting the fastest ski time in one of the races at the season-opener in Kontiolahti (for the first time in her career), Hanna Öberg had an abysmal final month of the season.

Tiril Eckhoff dominated the World Cup action after Christmas – not because of improved skiing however, she remained more or less at the same (high) level as last year. Dorothea Wierer‘s skiing improved slightly over the course of the season, but last year’s World Cup winner was still 1.2% slower, which gave her little chance to defend her title. Denise Herrmann, last winter’s overall fastest saw her ski speed decline considerably, even though she still remained one of the field’s top 5 skiers.

NoFamily NameGiven NameNationRacesSki Rank
(avg)
Changeback from
Top30 median
(in %)
Change
NoFamily NameGiven NameNationRacesSki Rank
(avg)
Changeback from
Top30 median
(in %)
Change
1AlimbekavaDzinaraBLR
2613.8-49.6-0.30-5.79
2ZdoucDunjaAUT
2541.4-35.2+2.92-4.39
3SolaHannaBLR
2311.5-35.9-0.56-3.85
4BeaudrySarahCAN
1566.6-16.5+5.84-3.85
5TomingasTuuliEST
1545.7-30.3+3.80-3.68
6BlashkoDaryaUKR
2044.5-18.3+3.68-3.33
7LieLotteBEL
1872.0-12.8+6.87-3.31
8CadurischIreneSUI
1652.1-18.9+4.13-2.80
9ReidJoanneUSA
1547.5-20.8+3.29-2.74
10HauserLisa TheresaAUT
2611.8-22.8-0.58-2.66
11TodorovaMilenaBUL
1933.9-17.0+2.14-1.84
12OebergElviraSWE
2516.3-9.2-0.11-1.72
13ChevalierChloeFRA
1826.0-18.7+1.25-1.68
14TalihaermJohannaEST
1842.2-12.1+3.10-1.38
15PreussFranziskaGER
2611.5-10.7-0.68-1.34
16SchwaigerJuliaAUT
1937.7-12.8+2.43-1.25
17MaedaSariJPN
1647.4-6.8+3.49-1.07
18CharvatovaLucieCZE
1719.6-5.3+0.50-0.97
19BendikaBaibaLAT
1624.0-9.4+0.85-0.95
20MinkkinenSuviFIN
1867.9-0.9+6.03-0.69
21PerssonLinnSWE
2618.2-4.4+0.16-0.66
22KnottenKaroline OffigstadNOR
2342.7-2.2+3.24-0.65
23GasparinElisaSUI
2145.4-4.8+3.33-0.45
24SimonJuliaFRA
2613.8-0.7-0.55-0.45
25BelchenkoYelizavetaKAZ
1572.3-1.6+7.05-0.40
26TandrevoldIngrid LandmarkNOR
259.3-3.4-0.94-0.39
27GasparinSelinaSUI
1914.4-3.7-0.13-0.30
28KlemencicPolonaSLO
1569.6-2.8+6.56-0.29
29DavidovaMarketaCZE
258.5-2.4-1.05-0.22
30JislovaJessicaCZE
1751.7-1.5+4.02-0.17
31DzhimaYuliiaUKR
2129.8+0.4+1.54-0.08
32MironovaSvetlanaRUS
2220.0+0.8+0.38-0.01
33HettichJaninaGER
2436.4-1.6+2.32+0.02
34RoeiselandMarte OlsbuNOR
265.2-1.9-1.85+0.04
35EganClareUSA
2331.3-0.2+1.95+0.08
36LunderEmmaCAN
2242.0+3.5+2.92+0.14
37HammerschmidtMarenGER
1751.1-0.9+4.26+0.23
38KruchinkinaElenaBLR
2318.8-1.3+0.47+0.25
39EckhoffTirilNOR
264.1-1.4-2.22+0.28
40OebergHannaSWE
2616.8+2.7-0.05+0.34
41GasparinAitaSUI
1950.2+7.0+3.99+0.54
42BescondAnaisFRA
2621.9+4.4+0.73+0.67
43PidhrushnaOlenaUKR
1836.4+7.2+2.33+0.67
44InnerhoferKatharinaAUT
1725.4+7.0+1.03+0.77
45VittozziLisaITA
2526.8+6.8+1.34+0.80
46KryukoIrynaBLR
1540.4+11.9+2.50+0.84
47Braisaz-BouchetJustineFRA
268.3+2.5-1.15+0.86
48EderMariFIN
1719.9+6.4+0.40+1.03
49HinzVanessaGER
2235.1+12.0+2.11+1.07
50TachizakiFuyukoJPN
1855.3+6.7+4.74+1.08
51KuklinaLarisaRUS
1644.5+9.2+3.39+1.12
52WiererDorotheaITA
2617.3+7.2+0.19+1.18
53DunkleeSusanUSA
1946.3+13.3+3.49+1.38
54HaeckiLenaSUI
2131.3+14.3+1.77+1.59
55ZukKamilaPOL
1734.4+13.9+1.99+1.62
56BrorssonMonaSWE
2239.9+12.1+2.98+1.70
57HerrmannDeniseGER
2510.0+7.4-1.02+2.01
58Hojnisz-StaregaMonikaPOL
1634.5+17.5+1.94+2.07
59PuskarcikovaEvaCZE
1860.0+22.9+5.46+2.48

Posted in Statistical analysis | Tagged ski speed

Ski speed – First vs. second trimester

Posted on 2021-01-28 | by real biathlon | Leave a Comment on Ski speed – First vs. second trimester

The season is already more than halfway over. Who managed to improve their ski form during the winter? In this post, I looked at changes in ski speed for World Cup trimester 1 compared to World Cup trimester 2 (November/December 2020 vs. January 2021). For patrons, I recently updated the comparisons bonus section – there you can compare all shooting and skiing stats on your own, not only season-to-season, but also by trimester now.


Note: Only athletes with at least 5 non-team races in trimester 1 and trimester 2 of the current season are included in the tables. “Back from Top30 median” is the percentage back from each race’s top 30 median Course Time (arithmetic mean per trimester).


Men

Surprise podium finisher Felix Leitner managed to improve his ski speed by roughly 1.3% compared to pre-Christmas races. Lukas Hofer improved by virtually the same amount, although he did so on a much higher level (he was the fourth-fastest skier overall for trimester 2). A lot has been made about Johannes Thingnes Bø not dominating as he did in previous seasons, however, his ski speed certainly isn’t to blame; he set the top course time in 5 out of 6 races in January!

Jakov Fak had a great start to his season (four top 10s in a row), but his ski speed is now trending in the wrong direction before the upcoming world championships in Pokljuka. Sebastian Samuelsson‘s speed has declined 1.4% post-Christmas, his average ski rank is 10.9 positions lower. Fabien Claude isn’t doing much better, he also has a ski rank now roughly ten places lower compared to World Cup trimester 1.

Changes in Ski Speed World Cup Trimester 1 vs. World Cup Trimester 2 | 2020–21 season

NoFamily NameGiven NameNationRacesSki Rank
(avg)
Changeback from
Top30 median
(in %)
Change
NoFamily NameGiven NameNationRacesSki Rank
(avg)
Changeback from
Top30 median
(in %)
Change
1LeitnerFelixAUT
619.8-16.6+0.71-1.29
2HoferLukasITA
66.2-7.2-1.51-1.26
3GuigonnatAntoninFRA
620.0-11.0+0.44-1.16
4EliseevMatveyRUS
518.8-17.0+1.07-1.07
5DollBenediktGER
612.5-3.5-0.92-0.92
6FinelloJeremySUI
518.4-9.2+0.26-0.90
7PeifferArndGER
611.5-6.5-0.73-0.90
8BoeJohannes ThingnesNOR
61.3-1.1-3.36-0.70
9DesthieuxSimonFRA
614.7-4.9-0.15-0.60
10EderSimonAUT
634.0-5.2+2.04-0.54
11Fillon MailletQuentinFRA
58.6-2.4-1.11-0.47
12LaegreidSturla HolmNOR
69.7-3.9-0.95-0.41
13KomatzDavidAUT
640.8-5.6+3.18-0.37
14LatypovEduardRUS
616.2-2.7+0.18-0.23
15DaleJohannesNOR
63.0-3.1-1.99-0.02
16JacquelinEmilienFRA
610.5+0.3-0.71+0.10
17BoeTarjeiNOR
66.0+1.4-1.55+0.23
18FakJakovSLO
623.2+3.2+0.71+0.25
19PonsiluomaMartinSWE
67.8+2.2-1.40+0.27
20RastorgujevsAndrejsLAT
522.8+2.2+0.82+0.32
21LesserErikGER
621.5+2.8+0.70+0.34
22WegerBenjaminSUI
624.8+4.6+0.98+0.39
23FemlingPeppeSWE
542.2-9.7+4.06+0.41
24BionazDidierITA
544.6+0.2+3.65+0.45
25ChristiansenVetle SjaastadNOR
518.2+4.9+0.11+0.74
26LoginovAlexanderRUS
521.2+7.5+0.52+0.77
27BocharnikovSergeyBLR
532.6+5.1+1.98+0.92
28ClaudeFabienFRA
619.8+9.6+0.39+1.07
29SamuelssonSebastianSWE
619.2+10.9+0.26+1.39


Women

Elena Kruchinkina, who set the fastest course time in the first Oberhof sprint (before that she never had a top 3 course time), is the most improved skier among regular female starters: 2.4% faster compared to December and her average ski rank is now 16.5 positions lower. Yuliia Dzhima and Svetlana Mironova come second and third, skiing 2.0% and 1.6% faster respectively. Two-time winner Julia Simon improved almost as much percentage-wise, but more importantly, she was the fourth-fastest skier in January.

Monika Hojnisz-Staręga is missing here, because she only appeared in three races in January, however, she would have topped the ranking, 3.4% faster than in trimester 1. Dorothea Wierer‘s skiing has improved slightly, but her average ski rank in January (16.8) is still way behind her average from last season (10.0). Elvira Öberg and Mona Brorsson have been struggling in recent races, both roughly 3% slower in January.

Changes in Ski Speed World Cup Trimester 1 vs. World Cup Trimester 2 | 2020–21 season

NoFamily NameGiven NameNationRacesSki Rank
(avg)
Changeback from
Top30 median
(in %)
Change
NoFamily NameGiven NameNationRacesSki Rank
(avg)
Changeback from
Top30 median
(in %)
Change
1KruchinkinaElenaBLR
510.2-16.5-0.84-2.39
2DzhimaYuliiaUKR
523.0-18.6+0.81-1.96
3MironovaSvetlanaRUS
612.2-13.3-0.57-1.59
4SimonJuliaFRA
66.5-12.8-1.57-1.42
5HettichJaninaGER
627.5-15.3+1.62-1.32
6HinzVanessaGER
530.8-14.2+1.88-1.15
7KaishevaUlianaRUS
625.8-13.3+1.55-1.02
8VittozziLisaITA
521.2-10.2+0.95-0.88
9HerrmannDeniseGER
64.2-4.2-1.90-0.65
10ZdoucDunjaAUT
636.2-15.4+3.16-0.55
11WiererDorotheaITA
616.8-4.3+0.11-0.49
12EckhoffTirilNOR
62.3-3.2-2.38-0.44
13HauserLisa TheresaAUT
610.5-2.2-0.76-0.39
14PavlovaEvgeniyaRUS
524.4-5.1+1.09-0.35
15RoeiselandMarte OlsbuNOR
62.8-1.7-2.24-0.28
16DavidovaMarketaCZE
66.5-0.4-1.29+0.14
17PreussFranziskaGER
612.7+0.6-0.39+0.17
18LunderEmmaCAN
535.8-1.3+2.59+0.18
19BescondAnaisFRA
619.0+3.0+0.34+0.18
20PerssonLinnSWE
623.3+4.0+0.68+0.35
21AlimbekavaDzinaraBLR
615.7+1.4+0.12+0.46
22Braisaz-BouchetJustineFRA
67.8+2.1-1.03+0.59
23OebergHannaSWE
616.7+4.7-0.09+0.62
24Chevalier-BouchetAnaisFRA
613.2+5.7+0.08+1.23
25TandrevoldIngrid LandmarkNOR
520.0+12.9+0.58+1.86
26EganClareUSA
634.7+6.6+3.12+1.88
27KnottenKaroline OffigstadNOR
647.3+14.4+4.56+2.67
28OebergElviraSWE
624.5+17.8+1.25+2.89
29BrorssonMonaSWE
546.6+17.7+4.72+3.17

Overall, the Swedes arguably stand out the most, doing particularly poorly after Christmas – all of their regular starters declined in the new year (often by a lot). Alternatively, you could look at it the other way around: they simply outperformed, especially in Kontiolahti, and now regressed to a more normal level.

Posted in Statistical analysis | Tagged ski speed

Ski Speed comparison season-to-season

Posted on 2020-12-02 | by real biathlon | 5 Comments on Ski Speed comparison season-to-season

It’s probably no use to look at shooting percentages after only 30 shots at the beginning of a season, however, the ski speed at the first World Cup weekend might already tell us at least a little bit where the season is going and how the ski form for some of the top athletes might have changed over the summer.

If you can’t find a specific athlete, you can always look up complete World Cup statistics for the ongoing season here:

  • Ski speed: Men | Women
  • Shooting percentage: Men | Women
  • Shooting Times: Men | Women

Note: Only athletes with at least 15 races last season and 2 races this season are included in the two tables below. “Back from Top30 median” is the percentage back from each race’s top 30 median Course Time (arithmetic mean per season).


Men

Sergey Bocharnikov was the most improved overall; he skied 4.7% faster and lowered his average ski rank by 38.7. Maybe even more impressive though, Sebastian Samuelsson and Martin Ponsiluoma both improved by 3.7%, and did so on a much higher level. Surprise winner Sturla Holm Lægreid does not show up here, because he only appeared in 4 races last season, however, he did improve his speed by 1.7%

Johannes Thingnes Bø continued where he left off: he was not simply the fastest overall (over 1% ahead of the 2nd fastest, his brother Tarjei Bø), he also set the top Course Time in both races. One of the pre-season favorites, Quentin Fillon Maillet, shot great (96.7%), but did not have the best weekend skiing-wise (his average ski rank increased from 5.6 to 15.0). Dmytro Pidruchnyi struggled the most, he was 3.3% slower than last season.

Changes in Ski Speed compared to 2019–20 season

NoFamily NameGiven NameNationRacesSki Rank
(avg)
Changeback from
Top30 median
(in %)
Change
NoFamily NameGiven NameNationRacesSki Rank
(avg)
Changeback from
Top30 median
(in %)
Change
1BocharnikovSergeyBLR
210.5-38.7-0.99-4.67
2SamuelssonSebastianSWE
23.5-25.2-2.23-3.69
3PonsiluomaMartinSWE
24.5-22.6-2.16-3.67
4NelinJesperSWE
28.5-16.1-0.95-1.89
5FakJakovSLO
217.5-12.5+0.10-1.58
6MoravecOndrejCZE
231.5-8.2+1.45-1.37
7ChristiansenVetle SjaastadNOR
29.5-7.6-1.26-1.26
8BoeTarjeiNOR
23.0-5.0-2.48-1.15
9BauerKlemenSLO
236.0-10.2+2.17-1.10
10JacquelinEmilienFRA
26.5-5.2-1.41-0.92
11BoeJohannes ThingnesNOR
21.0-2.0-3.61-0.71
12ClaudeFlorentBEL
237.0-3.2+2.37-0.58
13ClaudeFabienFRA
212.5-2.5-0.44-0.48
14RastorgujevsAndrejsLAT
218.0+0.4+0.16-0.31
15LoginovAlexanderRUS
213.5-4.0-0.21-0.28
16HoferLukasITA
217.5+1.8-0.09-0.20
17DaleJohannesNOR
210.0+0.2-1.28-0.09
18PeifferArndGER
216.5+0.9-0.13-0.08
19IlievVladimirBUL
224.0+2.0+0.72+0.02
20KrcmarMichalCZE
232.0+4.8+1.51+0.02
21SeppalaTeroFIN
232.5+4.7+1.62+0.29
22EliseevMatveyRUS
235.5+7.9+2.39+0.31
23WegerBenjaminSUI
234.0+5.3+2.00+0.43
24LeitnerFelixAUT
230.0+6.5+1.36+0.47
25GuigonnatAntoninFRA
232.5+10.5+1.66+0.52
26BjoentegaardErlendNOR
216.5+6.4+0.08+0.97
27DesthieuxSimonFRA
221.0+8.7+0.40+1.04
28EderSimonAUT
245.0+9.5+3.60+1.35
29PrymaArtemUKR
243.0+14.6+3.13+1.48
30Fillon MailletQuentinFRA
215.0+9.4-0.30+1.76
31DollBenediktGER
225.0+15.1+0.92+1.92
32EberhardJulianAUT
229.5+18.4+1.38+2.09
33KuehnJohannesGER
223.5+16.8+0.79+2.14
34FemlingPeppeSWE
265.5+17.9+5.54+2.31
35PidruchnyiDmytroUKR
257.0+33.1+4.59+3.33

Women

Among regular starters, Elvira Öberg was by far the most improved, 3.7% faster than last season. Her sister Hanna Öberg also improved a lot; the Kontiolahti sprint was her first ever race setting the top ski time. Lisa Theresa Hauser and Franziska Preuß also got considerably faster, but their improvement might not have been as obvious, because both hit only 25 out of 30 targets (83.3%), some 3-5% below their shooting percentage from last winter.

Lena Häcki, Julia Simon and Monika Hojnisz-Staręga all struggled to get going, skiing at least 3% slower. Hojnisz-Staręga had a particularly bad season opening, her average ski rank was 46.5 higher than last season, 5.0% behind her ski speed from last winter. Alongside the Öberg sisters, Tiril Eckhoff was fastest overall (but only managed a 66.7% hit rate). Last year’s top skier, Denise Herrmann, was not at her peak speed yet (+1.2%), however, her career-high 86.7% hit rate looks promising.

Changes in Ski Speed compared to 2019–20 season

NoFamily NameGiven NameNationRacesSki Rank
(avg)
Changeback from
Top30 median
(in %)
Change
NoFamily NameGiven NameNationRacesSki Rank
(avg)
Changeback from
Top30 median
(in %)
Change
1OebergElviraSWE
23.5-22.0-2.07-3.68
2HauserLisa TheresaAUT
216.0-18.7+0.16-1.93
3OebergHannaSWE
23.5-10.6-2.02-1.63
4PreussFranziskaGER
212.0-10.2-0.26-0.92
5TalihaermJohannaEST
250.0-4.3+3.85-0.64
6TandrevoldIngrid LandmarkNOR
26.0-6.7-1.18-0.63
7BrorssonMonaSWE
222.5-5.3+0.65-0.62
8GasparinAitaSUI
247.0+3.8+3.34-0.11
9KryukoIrynaBLR
227.5-1.0+1.58-0.09
10LunderEmmaCAN
240.5+2.0+2.70-0.09
11CharvatovaLucieCZE
226.0+1.1+1.43-0.05
12DavidovaMarketaCZE
210.5-0.3-0.55+0.28
13Braisaz-BouchetJustineFRA
26.5+0.7-1.71+0.30
14BescondAnaisFRA
217.5+0.1+0.40+0.33
15EckhoffTirilNOR
24.0-1.5-2.15+0.35
16GasparinElisaSUI
261.5+11.3+4.42+0.64
17PerssonLinnSWE
226.5+3.9+1.50+0.69
18EderMariFIN
216.5+3.0+0.07+0.71
19RiederChristinaAUT
272.5+14.2+6.25+0.92
20SanfilippoFedericaITA
247.0+8.4+3.54+1.07
21InnerhoferKatharinaAUT
225.0+6.6+1.37+1.12
22PuskarcikovaEvaCZE
255.5+18.4+4.10+1.12
23HerrmannDeniseGER
26.5+3.9-1.85+1.18
24ZbylutKingaPOL
271.0+18.1+5.81+1.63
25OjaReginaEST
279.5+20.2+7.41+1.90
26ZukKamilaPOL
238.0+17.5+2.42+2.05
27WiererDorotheaITA
225.0+15.0+1.33+2.32
28HinzVanessaGER
250.5+27.4+3.62+2.58
29VittozziLisaITA
243.5+23.5+3.27+2.74
30KuklinaLarisaRUS
258.0+22.7+5.03+2.77
31SemerenkoVitaUKR
273.5+28.5+6.25+2.89
32HaeckiLenaSUI
245.5+28.6+3.35+3.17
33SimonJuliaFRA
247.5+33.0+3.28+3.38
34Hojnisz-StaregaMonikaPOL
263.5+46.5+4.87+5.01
Posted in Statistical analysis | Tagged 2020–21 season, ski speed, skiing

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