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Category: Statistical analysis

Biathlon World Cup wins by age | Women

Posted on 2021-12-09 | by real biathlon | Leave a Comment on Biathlon World Cup wins by age | Women

Women’s individual/non-team wins in World Cup level races by age (in y – years and d – days).

Biathlon World Cup, World Championships, Olympics – Women (1984- 2021).

Posted in Biathlon Media, Long-term trends, Statistical analysis | Tagged Data, data visualization

Looking back at Oestersund through data

Posted on 2021-12-06 | by biathlonanalytics | Leave a Comment on Looking back at Oestersund through data


With Oestersund coming to a close, it is time to review the Women’s individual performances and look at some athletes that stood out by their shooting and skiing performances based on the race data. It was nice to see that the wind that can be so typical for races in Oestersund mostly stayed away, giving us some tremendous races with fair conditions for all athletes!

The data and metrics

Based on IBU’s race data, the shooting charts shown in this article are simply expressed in the total shooting percentage (total misses divided by total shots taken). The skiing shown below uses the course time data and compares each athlete’s time with the fastest course time of the particular race. This gives us a “% behind the fastest skier” and gives us an idea of what an athlete must do to become the fastest skier of the pack.

Lisa Theresa Hauser

It is hard not to start with the current leader of the World Cup, and Hauser had some impressive races in Oestersund. And that with a ski speed that was slower (relative to the fastest skier) than her average based on the current and last season. Her shooting was top-notch and even above her already strong average of 86%. The chart below demonstrates these statistics per race event with the 2020-2021 season shown in green and the current 2021-2022 season shown in purple.

When we compare Hauser’s world cup points after four races to her previous two seasons’ four races, we can see that she is on a trend that will improve her final standing significantly if she can keep up this pace. It’s a bit early to say after only four races, but in any case, she is off to a great start of her season!

Anais Chevalier-Bouchet

Although Chevalier-Bouchet had a similarly strong start in the past season, she surprised me somewhat with her strong performance in Oestersund. Perhaps this was based on her decline at the end of last season. Her first race seemed to continue that trend, but after that first race she had some great results, especially in the shooting range. Her skiing was around her average for the current and previous season, so if she can improve there I think she’ll be someone to keep an eye on this season.

Denise Herrmann

It is an understatement that Herrmann’s previous season was disappointing, but based on her races in Oestersund Herrmann seems to be on her way back. With excellent shooting for her and improving ski speed, can she regain her form with which she won the 2019-2020 world cup sprint globe? With her ski speed still being under her average of the previous and current season, an improvement can be expected there. And if she then can keep shooting the way she was in Oestersund, contention for top spots are definitely within reach for Herrmann.

Dzinara Alimbekava

Like with Hauser, Alimbekava is a safe bet with her third position in the current world cup rankings. But I was really impressed with her consistency at a high level during her races in Oestersund. And when looking at her world cup points for the current season and comparing them to last season, this shouldn’t be a surprise. If she can avoid fading away a little like last season she could be a contender for the overall title. As she is turning 26 in January the blue bib is no longer something she can battle for, but I’m sure she would pick the yellow bib over the blue if she has the chance.

Elvira Oeberg

Lastly, the younger Oeberg sister was so impressive on her skis that I feel I cannot leave her out. Although her shooting was below her average from the current and last season, she made up many positions with her ski speed, being the fastest skier in three of the four races.

And currently in fourth place in the world cup rankings, she is right on pace with her season start last year. If she can improve on her shooting while keeping the speed it will be hard to imagine her out of the top five for upcoming races. Of course, this was a home event for Oeberg. And although that may come with some additional pressure, knowing the course really well and having a wax team that knows the conditions like no other team was a benefit she will no longer have in the rest of the season.

This concludes the women’s review of Oestersund. Part of this article was used in the IBU Biathlon Insider #2. If you are not yet subscribed to that, go to biathlonworld.com and scroll to the bottom then hit the Subscribe button! Or see the visuals “live” on my Tableau Public page. Or check my previous posts.

Posted in Long-term trends, Statistical analysis | Tagged Biathlon Analytics, Biathlon Insider

Season-to-season comparison: Shooting Rank

Posted on 2021-12-05 | by real biathlon | Leave a Comment on Season-to-season comparison: Shooting Rank

Changes in Shooting Rank (Range Time + Penalty Time rank). The tables show improvement and decline in average shooting ranks (per race) for this season’s four non-team races in Östersund compared last season’s data.

Only athletes who appeared in at least half the races of this season and in half the races of last season are included. You can do your own season-to-season comparisons for all stats in the Patreon bonus area.

Men

2021–22 Shooting Ranks compared to 2020–21 | Non-Team events

NoFamily NameGiven NameNationRacesHit RateRange TimeShooting TimeShooting
Rank (avg)
Change
NoFamily NameGiven NameNationRacesHit RateRange TimeShooting TimeShooting
Rank (avg)
Change
1SchommerPaulUSA
493.3351.830.621.3-48.5
2KuehnJohannesGER
286.6750.931.328.5-32.6
3SeppalaTeroFIN
392.5047.427.715.7-31.0
4TrsanRokSLO
296.6750.128.09.0-19.7
5LatypovEduardRUS
491.6750.830.418.8-16.2
6KobonokiTsukasaJPN
491.6752.431.331.8-15.6
7GowScottCAN
490.0045.925.118.5-15.5
8StvrteckyJakubCZE
476.6754.233.655.3-13.5
9PidruchnyiDmytroUKR
486.6748.726.626.5-11.9
10ClaudeFlorentBEL
491.6752.931.530.0-9.6
11BrownJakeUSA
485.0054.833.752.8-9.1
12BormoliniThomasITA
485.0048.928.530.0-8.3
13DudchenkoAntonUKR
488.3350.230.037.0-8.3
14StroliaVytautasLTU
485.0054.233.348.0-8.2
15WegerBenjaminSUI
491.6752.531.321.8-6.5
16ChristiansenVetle SjaastadNOR
491.6751.431.221.8-6.2
17BoeJohannes ThingnesNOR
490.0051.131.221.8-4.9
18EderSimonAUT
495.0047.526.710.8+0.3
19GowChristianCAN
390.0047.426.628.7+0.9
20IlievVladimirBUL
475.0053.132.054.0+0.9
21DovzanMihaSLO
485.0045.825.626.8+1.3
22HoferLukasITA
486.6752.131.229.5+2.2
23ZahknaReneEST
390.0053.131.340.0+3.7
24DollBenediktGER
485.0051.030.738.8+4.6
25DesthieuxSimonFRA
485.0049.330.131.0+5.3
26NelinJesperSWE
480.0052.630.159.3+6.2
27LaegreidSturla HolmNOR
397.5048.928.517.7+7.8
28LeitnerFelixAUT
481.6755.429.746.0+8.1
29BoeTarjeiNOR
485.0051.630.236.0+8.3
30ClaudeFabienFRA
480.0047.828.246.8+8.4
31EliseevMatveyRUS
293.3351.530.125.5+8.4
32LangerThierryBEL
478.3351.329.860.8+10.4
33ReesRomanGER
488.3351.330.441.8+12.5
34SmolskiAntonBLR
480.0050.329.457.0+14.0
35KrcmarMichalCZE
488.3351.530.838.5+15.1
36BocharnikovSergeyBLR
480.0048.828.058.0+15.2
37GuigonnatAntoninFRA
483.3351.231.148.3+15.7
38SamuelssonSebastianSWE
481.6751.231.441.3+17.7
39LoginovAlexanderRUS
480.0050.429.845.0+17.9
40JacquelinEmilienFRA
481.6748.228.739.5+17.9
41WindischDominikITA
473.3348.030.370.0+17.9
42VarabeiMaksimBLR
476.6755.836.473.3+20.0
43HarjulaTuomasFIN
380.0048.526.156.0+20.6
44Fillon MailletQuentinFRA
481.6749.528.845.8+24.3
45FakJakovSLO
387.5050.628.641.0+25.5
46MukhinAlexandrKAZ
375.0053.728.782.7+25.7
47LesserErikGER
382.5048.128.352.7+28.8
48DohertySeanUSA
475.0050.931.368.5+29.7
49DombrovskiKarolLTU
380.0054.232.373.3+29.8
50GuzikGrzegorzPOL
370.0054.632.094.0+30.3
51BionazDidierITA
375.0055.634.280.3+31.3
52DaleJohannesNOR
481.6754.933.767.5+33.0
53FemlingPeppeSWE
377.5048.126.669.7+38.0
54KomatzDavidAUT
382.5054.632.968.3+41.7
55SinapovAntonBUL
362.5054.131.2103.3+42.3
56SimaMichalSVK
372.5051.929.188.0+45.6
57PonsiluomaMartinSWE
466.6748.428.281.0+45.8
58GaranichevEvgeniyRUS
273.3349.728.087.0+61.5

Women

2021–22 Shooting Ranks compared to 2020–21 | Non-Team events

NoFamily NameGiven NameNationRacesHit RateRange TimeShooting TimeShooting
Rank (avg)
Change
NoFamily NameGiven NameNationRacesHit RateRange TimeShooting TimeShooting
Rank (avg)
Change
1LescinskaiteGabrieleLTU
495.0057.535.019.0-33.4
2JislovaJessicaCZE
490.0052.629.728.5-29.1
3BeaudrySarahCAN
491.6752.329.420.5-26.5
4IrwinDeedraUSA
485.0055.532.045.5-22.8
5OjaReginaEST
286.6750.527.739.0-14.5
6SolaHannaBLR
483.3348.727.734.3-13.0
7TomingasTuuliEST
485.0053.730.635.0-12.8
8DavidovaMarketaCZE
491.6754.232.924.5-12.2
9LieLotteBEL
493.3351.728.716.3-11.3
10HauserLisa TheresaAUT
495.0046.925.113.0-10.8
11AlimbekavaDzinaraBLR
491.6752.630.416.8-10.0
12NigmatullinaUlianaRUS
495.0053.733.618.8-9.7
13HaeckiLenaSUI
488.3348.326.728.8-7.4
14PuskarcikovaEvaCZE
488.3352.830.730.8-7.0
15EganClareUSA
486.6755.733.335.5-6.1
16Chevalier-BouchetAnaisFRA
488.3349.427.528.0-3.3
17GasparinSelinaSUI
481.6754.032.751.5-2.1
18MagnussonAnnaSWE
480.0054.531.549.5-1.9
19LunderEmmaCAN
488.3346.524.923.8-1.2
20KnottenKaroline OffigstadNOR
490.0048.927.616.3-1.1
21ZdoucDunjaAUT
491.6752.729.519.0-0.9
22RoeiselandMarte OlsbuNOR
490.0050.128.924.0-0.7
23HerrmannDeniseGER
490.0055.334.335.0+0.7
24VittozziLisaITA
481.6745.923.636.8+1.2
25BrorssonMonaSWE
486.6751.430.332.0+1.9
26KruchinkinaElenaBLR
481.6755.432.951.5+2.0
27SchwaigerJuliaAUT
486.6757.233.639.8+2.1
28BescondAnaisFRA
490.0054.632.736.5+2.7
29BilosiukOlenaUKR
290.0054.732.445.5+3.0
30BendikaBaibaLAT
377.5054.130.756.7+5.3
31TodorovaMilenaBUL
380.0053.129.655.7+5.4
32EderMariFIN
481.671:00.739.470.3+6.0
33HettichJaninaGER
488.3353.330.430.5+6.5
34DzhimaYuliiaUKR
486.6752.231.737.5+7.6
35MaedaSariJPN
471.6753.932.779.0+8.6
36LeshchankaIrynaBLR
483.3356.634.851.5+8.6
37PreussFranziskaGER
486.6750.027.729.8+9.2
38AvvakumovaEkaterinaKOR
385.0055.330.954.7+9.7
39KocerginaNataljaLTU
380.001:00.237.374.7+10.4
40TachizakiFuyukoJPN
385.0057.333.261.7+11.7
41LienIdaNOR
475.0057.635.061.3+12.1
42ChevalierChloeFRA
476.6755.532.462.5+13.3
43PerssonLinnSWE
481.6750.929.242.0+13.5
44Braisaz-BouchetJustineFRA
478.3352.730.957.0+14.6
45MironovaSvetlanaRUS
481.6752.030.453.3+15.5
46SemerenkoValentinaUKR
483.3352.430.248.0+15.5
47CharvatovaLucieCZE
372.5051.529.684.0+16.6
48GasparinAitaSUI
485.0051.128.949.3+16.7
49TandrevoldIngrid LandmarkNOR
486.6756.433.952.3+19.0
50ZukKamilaPOL
470.0055.833.977.7+19.9
51KuklinaLarisaRUS
481.6751.929.944.5+20.0
52OebergHannaSWE
480.0047.525.443.5+22.5
53HinzVanessaGER
483.3354.231.151.5+24.2
54OebergElviraSWE
478.3350.029.156.0+25.0
55MinkkinenSuviFIN
382.5055.232.062.0+26.8
56Hojnisz-StaregaMonikaPOL
382.5055.633.559.7+28.0
57TalihaermJohannaEST
375.0058.935.378.3+29.0
58WiererDorotheaITA
485.0054.232.745.0+29.1
59GasparinElisaSUI
380.0054.734.471.3+30.9
60KazakevichIrinaRUS
466.6755.434.182.0+31.8
61FialkovaIvonaSVK
370.0056.034.191.0+34.2
62DunkleeSusanUSA
275.0054.132.185.0+34.7
63KlemencicPolonaSLO
372.5055.231.794.0+34.9
64ReidJoanneUSA
367.5059.837.698.7+38.9
65SimonJuliaFRA
471.6748.526.877.8+39.3
66EckhoffTirilNOR
476.6750.630.165.3+40.8
Posted in Statistical analysis

Improvement season-to-season

Posted on 2021-11-28 | by real biathlon | Leave a Comment on Improvement season-to-season

Changes in the Total Performance Scores of regular World Cup athletes. The tables show improvement and decline in z-scores from this weekend’s Season Opening in Östersund compared to trimester 1 of last season (roughly December 2020, only athletes with at least 3 races in last winter’s trimester 1). You can do your own season-to-season comparisons for all stats in the Patreon bonus area.


Note: The scores are standard scores (or z-scores), indicating how many standard deviations (SD) an athlete is back from the World Cup mean (negative values indicate performances better than the mean). The Total Performance Score is calculated by approximating the importance of skiing, hit rate and shooting pace using the method of least squares (for more details, see here and here), and then weighting each z-score value accordingly.


Men

2021–22 z-Scores compared to Trimester 1 of 2020–21 | Non-Team events

NoFamily NameGiven NameNationRacesSki Speed
Score
Hit Rate
Score
Range Time
Score
Total
Performance
Score
Change
NoFamily NameGiven NameNationRacesSki Speed
Score
Hit Rate
Score
Range Time
Score
Total
Performance
Score
Change
1TodevBlagoyBUL
20.84-0.53-0.940.23-1.06
2GowScottCAN
2-0.25-1.56-1.74-0.81-1.00
3DudchenkoAntonUKR
2-0.76-0.53-1.04-0.73-0.72
4BrownJakeUSA
2-1.05-0.531.02-0.65-0.54
5SchommerPaulUSA
2-0.11-1.21-0.15-0.44-0.50
6DesthieuxSimonFRA
2-1.53-1.21-0.72-1.34-0.49
7StvrteckyJakubCZE
2-0.78-0.180.95-0.40-0.44
8KobonokiTsukasaJPN
20.24-1.210.33-0.17-0.41
9DovzanMihaSLO
20.17-1.21-1.40-0.42-0.40
10ZahknaReneEST
20.45-0.870.430.07-0.37
11StroliaVytautasLTU
2-0.90-0.531.30-0.53-0.36
12TsymbalBogdanUKR
20.11-0.53-1.50-0.27-0.31
13StefanssonMalteSWE
2-0.211.190.860.32-0.29
14ClaudeFabienFRA
2-1.73-0.18-1.50-1.26-0.28
15GowChristianCAN
2-0.47-1.21-1.33-0.79-0.27
16LeitnerFelixAUT
2-1.08-0.18-0.55-0.76-0.27
17PidruchnyiDmytroUKR
2-0.54-0.87-0.82-0.67-0.24
18StalderSebastianSUI
2-0.04-0.18-0.97-0.19-0.22
19MagazeevPavelMDA
20.24-0.53-1.34-0.17-0.21
20LatypovEduardRUS
2-1.00-1.21-0.01-0.95-0.15
21SiimerKristoEST
21.030.500.310.79-0.10
22DombrovskiKarolLTU
2-0.35-0.180.21-0.23-0.09
23ClaudeFlorentBEL
2-0.22-0.530.28-0.25-0.08
24NelinJesperSWE
2-1.32-0.180.52-0.77-0.04
25FemlingPeppeSWE
2-0.470.16-1.29-0.38-0.02
26SmolskiAntonBLR
2-1.28-0.180.23-0.78-0.02
27LazouskiDzmitryBLR
2-0.20-0.181.04-0.05+0.01
28HornPhilippGER
2-0.860.16-0.90-0.57+0.05
29ChristiansenVetle SjaastadNOR
2-1.50-0.870.64-1.06+0.10
30BoeTarjeiNOR
2-1.38-0.87-0.59-1.14+0.10
31BormoliniThomasITA
2-0.31-0.53-0.93-0.45+0.10
32BauerKlemenSLO
2-0.040.50-1.09-0.01+0.11
33SzczurekLukaszPOL
21.131.190.551.08+0.11
34GuigonnatAntoninFRA
2-1.210.16-0.39-0.71+0.11
35HiidensaloOlliFIN
2-0.210.160.800.02+0.12
36BanysLinasLTU
20.950.50-0.410.66+0.12
37EderSimonAUT
2-0.41-1.21-1.55-0.78+0.15
38SlotinsRobertsLAT
20.420.851.490.67+0.15
39SamuelssonSebastianSWE
2-2.000.160.44-1.08+0.15
40ReesRomanGER
2-0.900.16-0.15-0.50+0.18
41MukhinAlexandrKAZ
20.280.850.450.46+0.18
42VarabeiMaksimBLR
2-0.951.191.39-0.05+0.20
43BoeJohannes ThingnesNOR
2-1.61-1.210.02-1.30+0.20
44IlievVladimirBUL
2-0.460.500.38-0.08+0.22
45JacquelinEmilienFRA
2-1.990.50-0.63-1.10+0.23
46OzakiKosukeJPN
2-0.180.851.970.38+0.26
47BalogaMatejSVK
21.350.50-0.140.92+0.27
48TrsanRokSLO
21.20-1.56-0.680.18+0.27
49WindischDominikITA
2-0.421.19-1.09-0.03+0.28
50LoginovAlexanderRUS
2-1.210.16-0.48-0.73+0.29
51LangerThierryBEL
2-0.100.50-0.080.08+0.30
52RasticDamirSRB
20.660.503.220.92+0.33
53BocharnikovSergeyBLR
2-0.820.85-0.79-0.33+0.34
54LaegreidSturla HolmNOR
2-0.71-1.56-0.91-0.98+0.34
55Fillon MailletQuentinFRA
2-1.36-0.18-0.71-0.94+0.39
56DollBenediktGER
2-0.98-0.18-0.28-0.67+0.39
57KrcmarMichalCZE
2-0.740.160.08-0.38+0.40
58FakJakovSLO
2-0.37-1.21-0.85-0.67+0.42
59HarjulaTuomasFIN
20.620.16-1.650.21+0.43
60YaliotnauRamanBLR
2-0.511.531.180.28+0.43
61WegerBenjaminSUI
2-0.37-0.870.17-0.45+0.43
62KomatzDavidAUT
20.16-0.530.540.01+0.45
63GuzikGrzegorzPOL
20.141.190.710.51+0.46
64BionazDidierITA
20.11-0.180.610.09+0.47
65DohertySeanUSA
20.020.85-0.240.23+0.48
66SimaMichalSVK
20.550.850.080.58+0.54
67DaleJohannesNOR
2-1.240.160.88-0.58+0.64
68TachizakiMikitoJPN
21.03-0.870.680.44+0.65
69EberhardJulianAUT
20.060.16-0.270.05+0.72
70SinapovAntonBUL
20.421.530.760.78+0.72
71EliseevMatveyRUS
20.71-1.21-0.260.04+0.85
72VaclavikAdamCZE
20.031.881.190.70+0.88
73PonsiluomaMartinSWE
2-1.532.56-1.12-0.29+0.91
74GerdzhikovDimitarBUL
20.452.560.151.03+0.99
75HoferLukasITA
20.14-0.530.930.04+1.00
76GaranichevEvgeniyRUS
20.590.85-0.800.50+1.21

Women

2021–22 z-Scores compared to Trimester 1 of 2020–21 | Non-Team events

NoFamily NameGiven NameNationRacesSki Speed
Score
Hit Rate
Score
Range Time
Score
Total
Performance
Score
Change
NoFamily NameGiven NameNationRacesSki Speed
Score
Hit Rate
Score
Range Time
Score
Total
Performance
Score
Change
1BendikaBaibaLAT
2-0.74-0.87-0.34-0.73-0.83
2LieLotteBEL
2-0.31-1.28-0.67-0.63-0.61
3SolaHannaBLR
2-1.29-0.05-1.47-0.95-0.55
4NigmatullinaUlianaRUS
2-0.60-1.68-0.33-0.88-0.43
5MagnussonAnnaSWE
2-0.72-0.46-0.13-0.57-0.37
6DavidovaMarketaCZE
2-1.24-1.68-0.15-1.24-0.37
7KliminaDaryaKAZ
20.16-0.052.040.33-0.35
8JislovaJessicaCZE
2-0.37-0.46-0.51-0.41-0.30
9FialkovaIvonaSVK
2-0.481.180.350.10-0.25
10AlimbekavaDzinaraBLR
2-1.46-1.28-0.44-1.29-0.23
11WeidelAnnaGER
2-0.09-2.09-0.74-0.75-0.23
12AvvakumovaEkaterinaKOR
20.27-0.46-0.060.02-0.22
13LescinskaiteGabrieleLTU
20.88-1.680.760.12-0.21
14CharvatovaLucieCZE
2-0.880.77-1.04-0.42-0.19
15BrorssonMonaSWE
2-1.09-0.46-0.84-0.88-0.18
16BescondAnaisFRA
2-1.32-0.05-0.29-0.83-0.17
17PuskarcikovaEvaCZE
2-0.44-0.46-0.11-0.40-0.16
18VittozziLisaITA
2-0.920.36-1.99-0.68-0.15
19EderMariFIN
2-1.05-0.051.45-0.46-0.14
20HauserLisa TheresaAUT
2-0.95-0.87-1.97-1.05-0.14
21KondratyevaAnastassiyaKAZ
21.80-0.873.001.17-0.13
22Chevalier-BouchetAnaisFRA
2-1.21-0.05-1.16-0.87-0.10
23LienIdaNOR
2-0.92-0.051.01-0.43-0.07
24IrwinDeedraUSA
20.300.360.190.31-0.05
25Braisaz-BouchetJustineFRA
2-1.650.36-0.40-0.91-0.05
26TodorovaMilenaBUL
2-0.650.77-0.26-0.19-0.03
27KalkenbergEmilie AagheimNOR
2-0.25-0.05-0.71-0.25-0.01
28OebergElviraSWE
2-2.150.77-0.91-1.15+0.00
29DzhimaYuliiaUKR
2-0.74-0.05-0.23-0.48+0.03
30RoeiselandMarte OlsbuNOR
2-1.63-0.46-1.32-1.25+0.05
31HerrmannDeniseGER
2-1.23-0.870.41-0.93+0.06
32PreussFranziskaGER
2-1.51-0.05-0.83-1.00+0.06
33KruchinkinaElenaBLR
2-0.35-0.05-0.35-0.26+0.07
34MironovaSvetlanaRUS
2-0.820.36-0.44-0.43+0.11
35KlemencicPolonaSLO
20.021.180.130.37+0.11
36TachizakiFuyukoJPN
20.06-0.870.93-0.11+0.12
37ChevalierChloeFRA
2-1.021.18-0.30-0.29+0.12
38LunderEmmaCAN
2-0.04-1.28-2.13-0.65+0.16
39EganClareUSA
2-0.51-0.460.51-0.37+0.17
40TomingasTuuliEST
2-0.31-0.46-0.01-0.32+0.18
41KuklinaLarisaRUS
2-0.58-0.05-0.61-0.43+0.19
42GasparinSelinaSUI
2-0.20-0.05-0.59-0.20+0.20
43PerssonLinnSWE
2-1.210.77-0.99-0.61+0.21
44HinzVanessaGER
2-0.31-0.46-0.13-0.33+0.21
45KocerginaNataljaLTU
20.410.361.160.49+0.24
46HettichJaninaGER
2-0.51-0.05-0.61-0.39+0.25
47LehtlaKadriEST
21.76-1.28-0.410.62+0.32
48TandrevoldIngrid LandmarkNOR
2-1.19-0.050.46-0.66+0.33
49EckhoffTirilNOR
2-1.631.18-0.82-0.71+0.34
50OebergHannaSWE
2-1.670.77-1.40-0.93+0.34
51Hojnisz-StaregaMonikaPOL
2-0.330.36-0.20-0.11+0.35
52KadevaDanielaBUL
20.610.77-0.060.58+0.38
53JankaErikaFIN
21.500.36-0.190.97+0.38
54BeaudrySarahCAN
21.26-1.28-0.900.27+0.41
55HaeckiLenaSUI
2-0.230.36-1.25-0.18+0.41
56KnottenKaroline OffigstadNOR
20.23-1.68-1.25-0.50+0.42
57MaedaSariJPN
2-1.013.23-0.570.27+0.42
58ZdoucDunjaAUT
20.51-1.28-0.40-0.11+0.42
59GasparinElisaSUI
2-0.120.36-0.120.02+0.49
60GasparinAitaSUI
20.040.36-0.800.03+0.49
61SchwaigerJuliaAUT
20.07-0.460.32-0.05+0.49
62ZukKamilaPOL
2-0.331.590.750.36+0.58
63SimonJuliaFRA
2-1.121.59-1.38-0.36+0.58
64WiererDorotheaITA
2-1.16-0.051.65-0.50+0.59
65MinkkinenSuviFIN
20.51-0.050.550.36+0.60
66HorvatovaHenrietaSVK
22.24-0.46-0.111.18+0.61
67RiederChristinaAUT
20.61-0.460.310.27+0.61
68SemerenkoValentinaUKR
20.14-0.05-0.86-0.03+0.62
69BekhEkaterinaUKR
20.391.59-0.950.58+0.66
70LeshchankaIrynaBLR
2-0.110.360.560.11+0.79
71ReidJoanneUSA
2-0.151.591.370.53+0.81
72TalihaermJohannaEST
20.881.181.121.00+0.83
73HachisukaAsukaJPN
21.711.591.891.70+1.08
74SabuleAnnijaLAT
22.910.77-0.011.94+1.20
75KazakevichIrinaRUS
2-0.693.640.530.71+1.31
Posted in Long-term trends, Statistical analysis | Tagged 2021–22 season, shooting, skiing

Arnd Peiffer: Biathlon Legend?

Posted on 2021-07-16 | by Brian Halligan | Leave a Comment on Arnd Peiffer: Biathlon Legend?

In this video I contemplate the idea that Arnd Peiffer might be a biathlon legend. By comparing his results to German biathlon legends from the past, it’s easy to see that Arnd had been earning impressive results through out his 13 year biathlon career. The Olympic Gold medalist from PyeongChang 2018 should be considered one of the biathlon greats.

Posted in Biathlon Media, Statistical analysis

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