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Fastest skiers in biathlon (2001 – 2021)

Posted on 2021-12-28 | by real biathlon | Leave a Comment on Fastest skiers in biathlon (2001 – 2021)

The bars show a 7-race moving average for the percentage back from the top 30 median. Unfortunately, no data exists before the 2001โ€“02 season.

Women

Men

Posted in Biathlon Media, Long-term trends, Statistical analysis | Tagged skiing

Most improved athletes this winter

Posted on 2021-12-19 | by real biathlon | Leave a Comment on Most improved athletes this winter

Improvements in Total Performance Scores of regular World Cup athletes. The last row of both tables shows improvement and decline in overall scores for this season compared to performances last season (only athletes with at least 6 races this winter). 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

2021โ€“22 z-Scores compared to 2020โ€“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
1StefanssonMalteSWE
6-0.340.610.770.07-0.63
2DudchenkoAntonUKR
6-0.89-0.940.16-0.78-0.50
3StroliaVytautasLTU
8-0.91-0.490.38-0.63-0.42
4SmolskiAntonBLR
9-1.25-0.82-0.71-1.06-0.40
5KuehnJohannesGER
7-1.20-0.65-0.25-0.93-0.39
6SchommerPaulUSA
7-0.08-0.72-0.01-0.26-0.37
7LatypovEduardRUS
9-1.30-0.99-0.86-1.16-0.36
8HiidensaloOlliFIN
6-0.52-0.491.07-0.32-0.34
9ChristiansenVetle SjaastadNOR
9-1.38-1.40-0.53-1.29-0.30
10ClaudeFabienFRA
9-1.45-0.07-1.17-1.02-0.25
11NelinJesperSWE
6-1.280.09-0.10-0.74-0.25
12SeppalaTeroFIN
8-0.90-0.97-0.43-0.87-0.25
13BakkenSivert GuttormNOR
9-0.90-0.99-1.31-0.97-0.22
14FemlingPeppeSWE
7-0.50-0.72-0.87-0.61-0.21
15HornPhilippGER
8-1.02-0.29-0.21-0.71-0.20
16VarabeiMaksimBLR
7-0.930.330.61-0.38-0.19
17GowScottCAN
7-0.50-0.49-1.28-0.59-0.18
18GuigonnatAntoninFRA
9-1.30-0.40-0.22-0.91-0.17
19JacquelinEmilienFRA
9-1.72-0.49-0.91-1.26-0.14
20BormoliniThomasITA
9-0.50-0.82-0.83-0.63-0.12
21PidruchnyiDmytroUKR
6-0.86-0.68-0.60-0.78-0.11
22SamuelssonSebastianSWE
9-1.86-0.16-0.51-1.20-0.09
23LazouskiDzmitryBLR
8-0.35-0.200.57-0.20-0.09
24WegerBenjaminSUI
9-0.88-1.32-0.00-0.90-0.09
25LeitnerFelixAUT
9-0.77-0.90-0.14-0.73-0.09
26KhaliliSaid KarimullaRUS
9-0.70-1.07-0.19-0.75-0.07
27AndersenFilip FjeldNOR
7-0.720.41-0.44-0.36-0.06
28DesthieuxSimonFRA
9-1.39-0.49-0.66-1.04-0.02
29LangerThierryBEL
7-0.32-0.02-0.11-0.21-0.01
30StvrteckyJakubCZE
6-0.720.680.77-0.14+0.00
31NawrathPhilippGER
9-1.240.09-0.01-0.70+0.00
32BoeTarjeiNOR
9-1.39-0.90-0.52-1.15+0.02
33GowChristianCAN
7-0.33-0.95-1.08-0.60+0.02
34Fillon MailletQuentinFRA
9-1.55-0.82-0.97-1.27+0.02
35KobonokiTsukasaJPN
70.04-0.840.06-0.21+0.02
36GiacomelTommasoITA
7-0.810.68-1.00-0.40+0.05
37KrcmarMichalCZE
8-0.88-0.58-0.38-0.73+0.06
38OzakiKosukeJPN
8-0.09-0.100.700.00+0.08
39BrownJakeUSA
8-0.840.580.85-0.23+0.08
40DovzanMihaSLO
80.09-0.78-1.69-0.37+0.09
41ReesRomanGER
9-0.58-0.90-0.13-0.62+0.10
42LoginovAlexanderRUS
9-1.32-0.16-0.58-0.89+0.11
43DollBenediktGER
9-1.12-0.49-0.27-0.83+0.12
44YaliotnauRamanBLR
6-0.800.870.70-0.14+0.14
45EderSimonAUT
9-0.53-1.24-1.27-0.82+0.18
46ClaudeFlorentBEL
8-0.22-0.490.58-0.20+0.21
47BoeJohannes ThingnesNOR
9-1.59-0.57-0.64-1.18+0.22
48LesserErikGER
8-0.69-0.68-1.13-0.74+0.24
49LaegreidSturla HolmNOR
8-0.97-1.55-1.05-1.15+0.24
50MukhinAlexandrKAZ
6-0.060.820.490.26+0.24
51BocharnikovSergeyBLR
6-0.54-0.040.10-0.32+0.26
52BauerKlemenSLO
6-0.120.97-0.640.13+0.27
53WindischDominikITA
6-0.610.74-0.39-0.19+0.36
54IlievVladimirBUL
6-0.761.260.63-0.01+0.41
55PonsiluomaMartinSWE
8-1.311.26-0.87-0.51+0.46
56GuzikGrzegorzPOL
60.410.970.520.59+0.47
57HoferLukasITA
9-0.63-0.65-0.18-0.58+0.50
58KomatzDavidAUT
70.22-0.840.57-0.05+0.50
59DohertySeanUSA
8-0.040.58-0.380.10+0.56

Women

2021โ€“22 z-Scores compared to 2020โ€“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
1JislovaJessicaCZE
9-0.62-1.09-0.65-0.76-0.65
2LieLotteBEL
9-0.43-1.41-0.83-0.76-0.56
3SolaHannaBLR
9-1.47-0.28-1.62-1.14-0.55
4OebergElviraSWE
9-2.06-0.28-1.06-1.42-0.51
5MagnussonAnnaSWE
9-0.82-0.44-0.30-0.65-0.50
6BescondAnaisFRA
8-1.45-0.910.26-1.09-0.46
7VoigtVanessaGER
9-0.71-1.090.70-0.65-0.41
8StremousAlinaMDA
8-0.65-0.541.94-0.31-0.38
9NilssonStinaSWE
7-1.440.420.12-0.71-0.38
10FialkovaIvonaSVK
7-0.840.46-0.34-0.40-0.32
11BrorssonMonaSWE
9-1.04-0.36-0.73-0.81-0.32
12IrwinDeedraUSA
70.15-0.560.36-0.03-0.27
13Braisaz-BouchetJustineFRA
9-1.960.68-0.43-1.01-0.25
14Chevalier-BouchetAnaisFRA
9-1.31-0.36-1.32-1.03-0.25
15VinklarkovaTerezaCZE
60.57-0.130.410.34-0.23
16NigmatullinaUlianaRUS
9-0.81-1.09-0.62-0.87-0.19
17AlimbekavaDzinaraBLR
9-1.28-0.84-0.87-1.10-0.18
18TodorovaMilenaBUL
6-0.800.26-0.47-0.45-0.17
19VittozziLisaITA
9-0.970.20-1.68-0.71-0.17
20OebergHannaSWE
9-1.730.04-1.87-1.24-0.16
21MaedaSariJPN
6-0.831.100.21-0.14-0.15
22RoeiselandMarte OlsbuNOR
9-1.50-1.17-1.30-1.38-0.12
23SimonJuliaFRA
8-1.390.40-1.83-0.93-0.10
24KlemencicPolonaSLO
7-0.000.34-0.150.08-0.09
25TachizakiFuyukoJPN
80.05-1.010.26-0.23-0.07
26ChevalierChloeFRA
7-1.160.340.82-0.48-0.06
27HauserLisa TheresaAUT
9-0.96-1.25-1.68-1.13-0.06
28DavidovaMarketaCZE
8-1.30-0.82-0.05-1.01-0.06
29KalkenbergEmilie AagheimNOR
6-0.36-0.630.02-0.39-0.06
30CharvatovaLucieCZE
7-1.071.02-0.53-0.40-0.04
31HerrmannDeniseGER
8-1.54-0.350.16-0.99-0.03
32MironovaSvetlanaRUS
9-0.86-0.44-0.64-0.71-0.01
33MinkkinenSuviFIN
70.22-1.12-0.39-0.24-0.01
34TomingasTuuliEST
7-0.410.120.17-0.19+0.02
35PerssonLinnSWE
7-1.13-0.33-0.49-0.82+0.03
36EganClareUSA
7-0.34-0.670.10-0.38+0.03
37AvvakumovaEkaterinaKOR
6-0.09-0.440.49-0.12+0.07
38TandrevoldIngrid LandmarkNOR
9-1.18-0.440.05-0.82+0.09
39KinnunenNastassiaFIN
60.070.121.300.23+0.10
40PuskarcikovaEvaCZE
70.06-0.67-0.24-0.18+0.10
41PreussFranziskaGER
6-1.50-0.26-0.61-1.03+0.12
42KruchinkinaElenaBLR
7-0.480.010.12-0.27+0.15
43HaeckiLenaSUI
8-0.47-0.54-1.26-0.59+0.15
44HinzVanessaGER
9-0.57-0.60-0.37-0.56+0.18
45KazakevichIrinaRUS
9-0.830.520.24-0.31+0.18
46EderMariFIN
9-1.190.841.30-0.30+0.19
47WiererDorotheaITA
9-1.03-0.60-1.05-0.91+0.19
48LienIdaNOR
7-1.200.460.25-0.55+0.19
49HettichJaninaGER
7-0.61-0.44-0.07-0.49+0.20
50LunderEmmaCAN
60.05-0.88-2.07-0.47+0.21
51FialkovaPaulinaSVK
6-0.720.680.45-0.17+0.23
52BilosiukOlenaUKR
70.05-1.23-0.03-0.33+0.27
53KuklinaLarisaRUS
6-0.510.12-0.64-0.35+0.28
54BendikaBaibaLAT
6-0.870.400.19-0.37+0.29
55Vishnevskaya-SheporenkoGalinaKAZ
60.17-0.441.250.12+0.29
56GasparinAitaSUI
6-0.03-0.30-0.71-0.19+0.29
57LeshchankaIrynaBLR
7-0.32-0.220.77-0.16+0.34
58ReidJoanneUSA
7-0.431.020.410.09+0.35
59KnottenKaroline OffigstadNOR
60.06-1.01-0.96-0.37+0.36
60ZukKamilaPOL
6-0.581.240.350.06+0.38
61EckhoffTirilNOR
7-1.500.34-0.66-0.86+0.41
62DzhimaYuliiaUKR
9-0.750.31-0.57-0.42+0.43
63Hojnisz-StaregaMonikaPOL
7-0.29-0.720.10-0.37+0.44
64ZdoucDunjaAUT
60.35-0.86-0.23-0.07+0.58
65BeaudrySarahCAN
61.12-0.72-0.320.41+0.62
66TalihaermJohannaEST
60.530.260.510.45+0.77

Posted in Statistical analysis

Biathlon World Cup wins by age | Men

Posted on 2021-12-16 | by real biathlon | Leave a Comment on Biathlon World Cup wins by age | Men

Men’s individual/non-team wins in World Cup level races by age. Biathlon World Cup, World Championships, Olympics – Women (1958 – 2021).

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

An analysis of the always exciting pursuit races

Posted on 2021-12-10 | by biathlonanalytics | Leave a Comment on An analysis of the always exciting pursuit races

I did an analysis of the 142 pursuit races from the 2012-2013 season up to today (I’m writing this after the 2nd world cup of the 2021-2022 season). I wanted to see what the odds are of winning based on the starting position, expressed in seconds behind the first starter, based on previous results. The outcome was pretty interesting and somewhat unexpected!

Read the analysis below or use the interactive version on my Tableau Public page.

Posted in Long-term trends, 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

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