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Most improved athletes this winter

Posted on 2022-12-24 | by real biathlon | Leave a Comment on Most improved athletes this winter

Season-to-season 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’s World Cup trimester 1 compared to performances in trimester 1 last season (only athletes with at least 5 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

2022–23 z-Scores compared to 2021–22 | 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
1HartwegNiklasSUI
6-0.97-1.41-1.47-1.16-0.99
2AndersenFilip FjeldNOR
8-1.17-0.85-0.44-0.99-0.63
3ClaudeFlorentBEL
8-0.64-1.420.25-0.76-0.56
4GuzikGrzegorzPOL
50.07-0.070.590.09-0.50
5GiacomelTommasoITA
8-1.210.20-1.92-0.88-0.48
6LaegreidSturla HolmNOR
8-1.59-1.42-1.85-1.57-0.42
7BoeJohannes ThingnesNOR
8-1.98-0.94-1.37-1.60-0.42
8PonsiluomaMartinSWE
8-1.490.40-0.91-0.87-0.36
9DohertySeanUSA
8-0.360.20-0.89-0.26-0.36
10ReesRomanGER
8-1.06-1.04-0.40-0.98-0.35
11StvrteckyJakubCZE
6-1.110.520.34-0.46-0.33
12IlievVladimirBUL
5-0.890.640.25-0.31-0.30
13StroliaVytautasLTU
8-1.01-0.91-0.42-0.91-0.28
14SimaMichalSVK
60.44-0.860.730.10-0.26
15LapshinTimofeiKOR
5-0.29-0.36-1.91-0.50-0.25
16KomatzDavidAUT
70.00-1.360.80-0.30-0.25
17MagazeevPavelMDA
60.09-0.821.950.05-0.25
18KarlikMikulasCZE
5-0.611.040.940.05-0.23
19HiidensaloOlliFIN
8-0.54-0.56-0.52-0.54-0.22
20TachizakiMikitoJPN
60.71-1.27-0.010.05-0.20
21DollBenediktGER
8-1.41-0.27-0.71-1.00-0.17
22ClaudeFabienFRA
8-1.48-0.75-0.76-1.18-0.16
23NelinJesperSWE
8-1.24-0.750.57-0.88-0.14
24KrcmarMichalCZE
8-0.98-0.75-0.12-0.81-0.08
25BrandtOskarSWE
5-0.901.350.65-0.06-0.07
26WrightCampbellNZL
50.160.29-0.240.15-0.06
27PerrotEricFRA
5-0.810.64-0.13-0.31+0.00
28ZahknaReneEST
70.52-0.80-0.130.06+0.07
29DudchenkoAntonUKR
7-0.62-0.68-1.15-0.70+0.08
30GuigonnatAntoninFRA
8-1.09-0.37-0.34-0.79+0.12
31Fillon MailletQuentinFRA
8-1.07-1.23-1.21-1.13+0.14
32LeitnerFelixAUT
8-0.31-1.04-0.71-0.57+0.16
33RunnallsAdamCAN
60.100.11-1.77-0.12+0.17
34LangerThierryBEL
6-0.350.80-0.29-0.01+0.20
35BoeTarjeiNOR
8-1.30-0.37-0.54-0.94+0.21
36SamuelssonSebastianSWE
8-1.23-0.75-0.38-0.99+0.21
37FemlingPeppeSWE
7-0.500.22-1.39-0.40+0.21
38ChristiansenVetle SjaastadNOR
8-1.52-0.47-0.20-1.06+0.23
39SeppalaTeroFIN
7-1.030.22-0.75-0.63+0.23
40JacquelinEmilienFRA
8-1.610.11-0.89-1.02+0.24
41NawrathPhilippGER
5-0.62-0.200.21-0.40+0.31
42KuehnJohannesGER
7-1.260.67-0.47-0.60+0.32
43EderSimonAUT
5-0.41-0.67-0.52-0.50+0.32

Women

2022–23 z-Scores compared to 2021–22 | 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
1KlemencicPolonaSLO
7-0.91-0.290.20-0.59-0.68
2VittozziLisaITA
8-1.29-0.92-1.28-1.18-0.47
3KinnunenNastassiaFIN
5-0.48-0.040.56-0.23-0.46
4GasparinAitaSUI
8-0.53-0.75-0.88-0.64-0.45
5ComolaSamuelaITA
7-0.23-1.01-0.04-0.43-0.44
6SimonJuliaFRA
8-1.38-1.10-1.79-1.34-0.42
7MinkkinenSuviFIN
7-0.26-1.22-0.96-0.62-0.39
8EderMariFIN
8-1.350.46-0.09-0.67-0.37
9Batovska FialkovaPaulinaSVK
8-0.71-0.23-0.42-0.53-0.36
10TandrevoldIngrid LandmarkNOR
8-1.33-1.01-0.48-1.13-0.31
11KnottenKaroline OffigstadNOR
8-0.35-1.01-1.12-0.63-0.26
12ChevalierChloeFRA
8-0.99-0.49-0.13-0.74-0.26
13VoigtVanessaGER
8-0.92-1.360.36-0.90-0.25
14LunderEmmaCAN
6-0.54-0.76-1.49-0.72-0.25
15ZdoucDunjaAUT
70.15-1.01-0.79-0.30-0.23
16ReidJoanneUSA
6-0.17-0.130.14-0.12-0.22
17SchwaigerJuliaAUT
7-0.370.010.06-0.20-0.21
18PerssonLinnSWE
8-0.98-1.01-1.30-1.03-0.20
19MakaAnnaPOL
5-0.15-0.370.51-0.13-0.15
20TachizakiFuyukoJPN
7-0.28-1.010.79-0.36-0.13
21MagnussonAnnaSWE
8-0.71-0.84-0.82-0.76-0.12
22IrwinDeedraUSA
6-0.19-0.130.13-0.13-0.10
23WiererDorotheaITA
8-0.98-0.75-1.78-1.01-0.10
24ZukKamilaPOL
6-0.310.370.37-0.03-0.09
25TomingasTuuliEST
6-0.850.620.60-0.25-0.06
26LienIdaNOR
7-1.160.120.51-0.59-0.05
27Herrmann-WickDeniseGER
8-1.37-0.49-0.58-1.02-0.03
28KalkenbergEmilie AagheimNOR
7-0.25-0.60-0.79-0.42-0.03
29DavidovaMarketaCZE
8-1.02-0.92-1.20-1.01-0.00
30BendikaBaibaLAT
7-0.830.73-0.66-0.36+0.02
31Chevalier-BouchetAnaisFRA
8-1.22-0.49-1.13-1.00+0.04
32Haecki-GrossLenaSUI
8-0.940.46-1.09-0.55+0.04
33OebergElviraSWE
8-1.72-0.84-0.86-1.36+0.06
34HauserLisa TheresaAUT
8-0.93-0.84-1.44-0.97+0.16
35LieLotteBEL
7-0.38-1.22-0.13-0.59+0.17
36TodorovaMilenaBUL
7-0.540.32-0.32-0.26+0.19
37OebergHannaSWE
8-1.31-0.14-1.51-1.00+0.24
38PreussFranziskaGER
5-0.81-0.31-1.13-0.70+0.33
39StremousAlinaMDA
7-0.16-0.091.230.03+0.33
40JislovaJessicaCZE
7-0.15-0.70-0.49-0.35+0.40
41CharvatovaLucieCZE
6-0.401.25-0.880.02+0.42
42BlashkoDariaUKR
60.48-0.51-0.450.08+0.42
43FialkovaIvonaSVK
5-0.731.73-0.180.05+0.45
44BilosiukOlenaUKR
50.68-0.69-0.030.20+0.53
45NilssonStinaSWE
7-0.690.630.47-0.17+0.54

Posted in Statistical analysis | Tagged results, shooting, skiing

New biathlon point system

Posted on 2022-12-04 | by real biathlon | Leave a Comment on New biathlon point system

The International Biathlon Union (IBU) introduced a new scoring system for the Biathlon World Cup from this winter onwards: world championships will no longer be included in the World Cup score, no more dropped results and a major adjustment in the points system to increase the value between top results.

It’s arguably the biggest season-to-season change in the history of the sport and not everyone is happy with it.

Old vs. new biathlon point system

Rank Scoring system from
2008–09 to 2021–22
New scoring system from
2022–23
1 60 90
2 54 75
3 48 60
4 43 50
5 40 45
6 38 40
7-40 unchanged unchanged
(mostly) 2 dropped scores no dropped scores
WCH races count WCH no longer count

The IBU points system has always been an outlier compared to pretty much any other scoring system in sports, especially other FIS winter sports, because it greatly undervalued top results. Some people are concerned seasons will be decided too early now, others don’t like the fact that consistency is no longer as important. The fact that no results can be dropped any more has also been criticized by some athletes.

The new biathlon points system is still less extreme than the FIS scoring system or Formula One for example. Interestingly enough, the IBU prize money distribution has always been more top heavy than their scoring system. Let’s take a closer look at how previous seasons would have turned out with the new system.

For last season’s Overall World Cup, the new point system would have had very little effect. The top 3 for both men and women would be unchanged if you apply the rules of the new scoring system. The only World Cup score that would have been flipped is the women’s Mass Start score, which was won by Justine Braisaz-Bouchet, but now would go to Elvira Öberg with the new points system.

Both big crystal globes were won rather decisively, so it is no surprise a different scoring system wouldn’t change the outcome. For last season, there wouldn’t have been much difference in when the title race was over either. Both winners would have been crowned just one race earlier (Quentin Fillon Maillet would have clinched the title in the Otepää sprint, instead of the mass start, Marte Olsbu Røiseland would have won the title three instead of two races before the end of the season).

Things get more interesting for 2019–20. Here both the men’s and the women’s overall winner comes out different. It also gets quite complicated, because aside from the mere points, there’s also dropped results and the difference in world champion races to account for.

For the men, the season actually ended like this: Johannes Thingnes Bø 913, Martin Fourcade 911. With the new system Fourcade would have won 1019 vs. 1001. However, if you still count the world championship results, the outcome flips again, and Bø comes out on top (1286 vs. 1014).

It gets even more extreme on the women’s side. The actual score was very close: Dorothea Wierer 793, Tiril Eckhoff 786. However, using this winter’s scoring system, Eckhoff would have won the title quite easily (956 vs. 737). Mostly because of Wierer’s very strong and Eckhoff’s horrible 2020 WCHs in Antholz; results which would now no longer be included. If you count the championship races, Eckhoff still comes out on top (1039 vs. 1028), but only by 11 points, thanks to her 7 wins that season compared to Wierer’s 4.

Since 2011, five (out of 24) Overall World Cup decisions would have been changed due to the new scoring system (2011: Bø vs. Svendsen, 2014 Berger vs. Mäkäräinen, 2018 Mäkäräinen vs. Kuzmina, plus both winners in 2020 as mentioned above).

It seems that even with the new scoring system, World Cup seasons that were close before will still be close even with the bigger point spread. And for seasons with runaway winners, which we had several on the men’s side during the last decade, the point system doesn’t matter all that much. The biggest change is probably the fact that from now on wins and podiums will be much more important that consistent top 10 results.

Posted in Biathlon News, Statistical analysis

Most improved athletes of last season

Posted on 2022-03-28 | by real biathlon | Leave a Comment on Most improved athletes of last season

Improvements in Total Performance Scores of regular World Cup athletes season-to-season. The last row of both tables shows changes in overall scores for the 2021–22 season compared to performances one season earlier (only athletes who appeared in at least half the races each season). 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 2020–21 | Non-Team events

Winning his first top 10 result this season, American Paul Schommer was the most improved male athlete, with career bests both in terms of shooting accuracy and ski speed. Vytautas Strolia also managed his first career top 10 this winter, coming second on this list, mostly thanks to skiing almost 2% faster than last year. In contrast, Martin Ponsiluoma and Sturla Holm Lægreid both underperformed compared to 2020–21, even though Lægreid managed to finish the season strong and repeated his 2nd place in the overall standings.

Quentin Fillon Maillet only improved marginally over last winter (1.3% better hit rate, 0.5% faster skiing), but it was more than enough to win his first Overall World Cup title comfortably. Johannes Thingnes Bø had by far the worst shooting stats of his career (82.1% hit rate, a whole 10% lower than only two seasons ago), however, he was still the field’s fastest skier and he delivered when it counted most in Beijing, winning 4 Olympic gold medals.

2021–22 z-Scores compared to 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
1SchommerPaulUSA
18-0.18-0.68-0.35-0.35-0.45
2StroliaVytautasLTU
23-0.67-0.51-0.15-0.56-0.35
3DudchenkoAntonUKR
14-0.65-0.810.59-0.55-0.27
4SmolskiAntonBLR
19-1.19-0.690.20-0.88-0.22
5FemlingPeppeSWE
14-0.44-0.81-0.95-0.61-0.21
6LatypovEduardRUS
14-1.34-0.62-0.28-1.01-0.21
7SeppalaTeroFIN
25-1.03-0.50-0.45-0.80-0.19
8KuehnJohannesGER
21-1.210.02-0.03-0.71-0.18
9ChristiansenVetle S.NOR
24-1.24-1.24-0.52-1.15-0.17
10KobonokiTsukasaJPN
20-0.09-1.04-0.11-0.37-0.14
11LesserErikGER
20-1.01-1.21-1.44-1.12-0.14
12ReesRomanGER
25-0.75-1.25-0.17-0.82-0.11
13Fillon MailletQuentinFRA
26-1.55-1.19-1.01-1.38-0.09
14BormoliniThomasITA
25-0.58-0.66-0.60-0.60-0.09
15BrownJakeUSA
19-0.80-0.000.71-0.39-0.08
16ClaudeFabienFRA
24-1.17-0.10-1.00-0.84-0.07
17LangerThierryBEL
14-0.32-0.340.26-0.25-0.06
18GowScottCAN
16-0.45-0.23-1.10-0.46-0.05
19StvrteckyJakubCZE
18-0.830.680.84-0.19-0.05
20DollBenediktGER
25-1.28-0.63-0.45-0.99-0.04
21WegerBenjaminSUI
18-0.76-1.24-0.32-0.85-0.03
22LeitnerFelixAUT
23-0.67-0.80-0.31-0.66-0.02
23GuigonnatAntoninFRA
21-0.90-0.39-0.92-0.75-0.01
24SamuelssonSebastianSWE
24-1.44-0.62-0.54-1.09+0.02
25DesthieuxSimonFRA
26-1.18-0.81-0.51-0.99+0.02
26GowChristianCAN
18-0.18-1.24-1.00-0.58+0.03
27DovzanMihaSLO
15-0.06-0.78-1.16-0.40+0.06
28LoginovAlexandrRUS
18-1.41-0.26-0.14-0.92+0.08
29PidruchnyiDmytroUKR
14-0.91-0.07-0.20-0.58+0.09
30BoeTarjeiNOR
22-1.31-0.92-0.28-1.07+0.09
31BionazDidierITA
14-0.33-0.190.81-0.16+0.09
32ZahknaReneEST
150.34-0.720.02-0.00+0.10
33NelinJesperSWE
17-0.900.370.38-0.38+0.11
34JacquelinEmilienFRA
25-1.28-0.44-1.04-1.01+0.11
35IlievVladimirBUL
18-0.880.590.48-0.29+0.13
36KrcmarMichalCZE
25-0.79-0.660.01-0.65+0.14
37ClaudeFlorentBEL
20-0.24-0.530.24-0.27+0.14
38EderSimonAUT
25-0.57-1.31-1.19-0.86+0.14
39BoeJohannes T.NOR
17-1.78-0.40-0.28-1.20+0.21
40LaegreidSturla HolmNOR
23-1.35-0.90-0.90-1.17+0.22
41PonsiluomaMartinSWE
23-1.390.59-0.86-0.75+0.22
42DohertySeanUSA
21-0.430.26-0.36-0.22+0.24
43WindischDominikITA
18-0.770.490.00-0.31+0.24
44MukhinAlexandrKAZ
15-0.110.740.980.26+0.24
45HoferLukasITA
24-0.82-0.96-0.30-0.80+0.28
46GuzikGrzegorzPOL
140.160.910.540.42+0.30
47SimaMichalSVK
150.190.120.210.17+0.30
48KomatzDavidAUT
18-0.05-0.800.51-0.20+0.34
49SinapovAntonBUL
130.011.040.960.42+0.57

Women

Jessica Jislová was the most improved athlete on the women’s side, skiing roughly 1% faster than last season and raising her non-team hit rate by 13.9% (among regular World Cup athletes, she was the 4th-most accurate overall). She is followed by Deedra Irwin, who managed the United States’ best ever non-team result in Olympic history, and Sweden’s Anna Magnusson, who got her stats almost back to her 2016–17 level, her career best season.

While Marte Olsbu Røiseland did improve over last winter (-0.2%), her performance uptick wasn’t as extreme as you might expect. Last year’s World Cup winner Tiril Eckhoff was worse, but according to this metric only marginally (+0.1%); in fact, her hit rate didn’t change much at all (-2.1%). Clearly, it’s sometimes more important when you miss your shots, not so much how you average out over a season.

2021–22 z-Scores compared to 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
1JislovaJessicaCZE
25-0.59-1.11-0.49-0.73-0.62
2IrwinDeedraUSA
19-0.33-0.510.32-0.31-0.54
3MagnussonAnnaSWE
16-0.84-0.40-0.51-0.67-0.52
4LieLotteBEL
22-0.39-1.03-0.87-0.63-0.44
5OebergElviraSWE
24-1.79-0.51-1.06-1.33-0.42
6SolaHannaBLR
18-1.620.28-1.10-1.01-0.41
7BrorssonMonaSWE
21-1.00-0.70-0.83-0.89-0.40
8FialkovaIvonaSVK
19-1.060.66-0.26-0.47-0.39
9ChevalierChloeFRA
20-1.14-0.17-0.28-0.76-0.34
10MinkkinenSuviFIN
17-0.10-1.21-0.78-0.50-0.27
11Braisaz-BouchetJustineFRA
25-1.840.42-0.50-1.02-0.26
12TodorovaMilenaBUL
18-1.020.19-0.00-0.55-0.26
13Chevalier-BouchetAnaisFRA
24-1.22-0.51-1.48-1.05-0.26
14RoeiselandMarte OlsbuNOR
24-1.66-1.09-1.34-1.45-0.20
15AlimbekavaDzinaraBLR
19-1.39-0.77-0.49-1.10-0.19
16TomingasTuuliEST
18-0.66-0.160.45-0.39-0.18
17SimonJuliaFRA
25-1.27-0.13-1.74-0.99-0.17
18TachizakiFuyukoJPN
18-0.26-0.650.20-0.32-0.15
19KlemencicPolonaSLO
17-0.200.48-0.060.02-0.15
20BescondAnaisFRA
25-1.25-0.07-0.20-0.78-0.15
21MaedaSariJPN
15-0.760.960.43-0.12-0.12
22OjaReginaEST
16-0.090.21-0.60-0.06-0.08
23NigmatullinaUlianaRUS
18-1.01-0.50-0.14-0.76-0.08
24TandrevoldIngrid L.NOR
23-1.31-0.70-0.18-1.00-0.08
25HerrmannDeniseGER
23-1.55-0.34-0.18-1.04-0.08
26EderMariFIN
24-1.300.520.51-0.56-0.07
27OebergHannaSWE
24-1.560.03-1.79-1.13-0.05
28HettichJaninaGER
16-0.88-0.44-0.82-0.75-0.05
29GasparinAitaSUI
13-0.39-0.58-1.09-0.53-0.05
30EganClareUSA
18-0.63-0.350.11-0.46-0.05
31GasparinElisaSUI
13-0.48-0.20-1.00-0.46-0.04
32DavidovaMarketaCZE
25-1.41-0.46-0.20-0.99-0.03
33PerssonLinnSWE
22-1.23-0.30-0.57-0.89-0.03
34MironovaSvetlanaRUS
15-1.07-0.19-0.21-0.72-0.02
35KazakevichIrinaRUS
18-1.020.170.49-0.49-0.00
36HauserLisa TheresaAUT
26-1.10-0.81-1.53-1.06+0.00
37CharvatovaLucieCZE
20-0.930.77-0.23-0.36+0.01
38VittozziLisaITA
20-1.050.96-1.40-0.51+0.04
39HaeckiLenaSUI
22-0.88-0.09-1.24-0.69+0.04
40AvvakumovaEkaterinaKOR
13-0.34-0.150.86-0.14+0.05
41ReidJoanneUSA
16-0.520.420.12-0.17+0.09
42PreussFranziskaGER
17-1.35-0.58-0.76-1.06+0.09
43KruchinkinaElenaBLR
13-0.700.190.26-0.33+0.09
44ZukKamilaPOL
14-0.790.680.42-0.22+0.10
45KnottenKaroline O.NOR
18-0.41-0.60-1.80-0.63+0.10
46LeshchankaIrynaBLR
14-0.79-0.070.77-0.40+0.10
47EckhoffTirilNOR
21-1.70-0.22-0.77-1.16+0.11
48HinzVanessaGER
21-0.80-0.53-0.02-0.63+0.11
49PuskarcikovaEvaCZE
160.00-0.31-0.65-0.17+0.12
50WiererDorotheaITA
25-1.08-0.46-1.46-0.95+0.15
51Hojnisz-StaregaMonikaPOL
19-0.74-0.58-0.09-0.61+0.19
52ZdoucDunjaAUT
13-0.04-0.95-1.27-0.45+0.20
53BendikaBaibaLAT
19-0.820.33-0.39-0.44+0.22
54LienIdaNOR
19-1.240.710.22-0.50+0.24
55LunderEmmaCAN
17-0.26-0.21-1.46-0.39+0.29
56DzhimaYuliiaUKR
19-0.990.14-0.10-0.55+0.30
57DunkleeSusanUSA
150.03-0.020.290.04+0.38
58SchwaigerJuliaAUT
14-0.37-0.280.60-0.23+0.38
59GasparinSelinaSUI
15-0.690.73-0.07-0.20+0.48
60TalihaermJohannaEST
140.29-0.240.540.17+0.49
Posted in Statistical analysis

Individual Olympic gold medals in biathlon (1960 – 2022)

Posted on 2022-02-19 | by real biathlon | Leave a Comment on Individual Olympic gold medals in biathlon (1960 – 2022)

Individual/non-team Olympic titles in biathlon – updated (1960 – 2022)
Complete record list:
https://www.realbiathlon.com/record

Posted in Biathlon Media, Long-term trends, Statistical analysis | Tagged 2022 Winter Olympics

Olympic Mixed Relay Projection

Posted on 2022-02-04 | by real biathlon | Leave a Comment on Olympic Mixed Relay Projection

Who are the favorites for the opening biathlon event at 2022 Winter Olympics? Here are the overall relay performances scores for the top 10 nations in the Mixed Nations Cup score (team performances this season).


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.


Norway – Average Performance Score: -1.16

NoFamily NameGiven NameNationRacesRank
(avg)
Points
(avg)
Ski Speed
Score
Hit Rate
Score
Range Time
Score
Total
Performance
Score
1RoeiselandMarte OlsbuNOR
34.046.3-1.35-1.24-1.86-1.53
1EckhoffTirilNOR
34.046.3-1.520.050.57-0.54
1BoeTarjeiNOR
41.060.0-1.06-1.06-0.77-0.95
1BoeJohannes T.NOR
41.060.0-1.93-1.59-1.17-1.60

France – Average Performance Score: -1.06

NoFamily NameGiven NameNationRacesRank
(avg)
Points
(avg)
Ski Speed
Score
Hit Rate
Score
Range Time
Score
Total
Performance
Score
NoFamily NameGiven NameNationRacesRank
(avg)
Points
(avg)
Ski Speed
Score
Hit Rate
Score
Range Time
Score
Total
Performance
Score
2Chevalier-BouchetAnaisFRA
44.049.5-1.280.44-1.66-1.22
2SimonJuliaFRA
31.756.0-1.26-0.37-1.07-1.08
2JacquelinEmilienFRA
33.049.3-1.20-0.410.27-0.55
2Fillon MailletQuentinFRA
33.049.3-1.49-1.47-1.24-1.39

Belarus – Average Performance Score: -0.95

NoFamily NameGiven NameNationRacesRank
(avg)
Points
(avg)
Ski Speed
Score
Hit Rate
Score
Range Time
Score
Total
Performance
Score
3AlimbekavaDzinaraBLR
45.544.0-1.23-1.24-1.71-1.41
3SolaHannaBLR
56.241.6-1.460.420.50-0.49
3LabastauMikitaBLR
45.842.3-0.88-0.74-1.15-0.96
3SmolskiAntonBLR
55.841.4-1.09-0.96-0.72-0.94

Germany – Average Performance Score: -0.87

NoFamily NameGiven NameNationRacesRank
(avg)
Points
(avg)
Ski Speed
Score
Hit Rate
Score
Range Time
Score
Total
Performance
Score
4VoigtVanessaGER
44.841.0-0.71-1.04-0.69-0.74
4HerrmannDeniseGER
34.342.0-1.61-0.190.56-0.62
4DollBenediktGER
34.045.0-1.17-0.59-0.42-0.81
4NawrathPhilippGER
33.346.7-1.35-1.23-1.28-1.31

Sweden – Average Performance Score: -0.78

NoFamily NameGiven NameNationRacesRank
(avg)
Points
(avg)
Ski Speed
Score
Hit Rate
Score
Range Time
Score
Total
Performance
Score
NoFamily NameGiven NameNationRacesRank
(avg)
Points
(avg)
Ski Speed
Score
Hit Rate
Score
Range Time
Score
Total
Performance
Score
5OebergHannaSWE
32.750.3-1.260.750.20-0.47
5OebergElviraSWE
32.750.3-2.19-0.57-0.49-1.35
5PonsiluomaMartinSWE
46.038.3-1.37-0.74-0.43-0.94
5SamuelssonSebastianSWE
46.038.3-0.860.270.12-0.35

ROC – Average Performance Score: -0.74

NoFamily NameGiven NameNationRacesRank
(avg)
Points
(avg)
Ski Speed
Score
Hit Rate
Score
Range Time
Score
Total
Performance
Score
NoFamily NameGiven NameNationRacesRank
(avg)
Points
(avg)
Ski Speed
Score
Hit Rate
Score
Range Time
Score
Total
Performance
Score
6NigmatullinaUlianaRUS
34.047.3-0.63-0.370.08-0.33
6ReztsovaKristinaRUS
53.250.0-1.30-0.35-1.28-1.18
6LoginovAlexandrRUS
42.352.5-1.55-0.45-0.25-0.93
6LatypovEduardRUS
32.750.0-1.530.520.47-0.53

Italy – Average Performance Score: -0.64

NoFamily NameGiven NameNationRacesRank
(avg)
Points
(avg)
Ski Speed
Score
Hit Rate
Score
Range Time
Score
Total
Performance
Score
NoFamily NameGiven NameNationRacesRank
(avg)
Points
(avg)
Ski Speed
Score
Hit Rate
Score
Range Time
Score
Total
Performance
Score
7VittozziLisaITA
57.236.6-0.82-0.57-1.62-1.09
7WiererDorotheaITA
45.838.8-0.720.410.54-0.11
7BormoliniThomasITA
57.435.6-0.960.040.13-0.42
7HoferLukasITA
36.737.0-0.79-1.01-1.11-0.94

Ukraine – Average Performance Score: -0.53

NoFamily NameGiven NameNationRacesRank
(avg)
Points
(avg)
Ski Speed
Score
Hit Rate
Score
Range Time
Score
Total
Performance
Score
NoFamily NameGiven NameNationRacesRank
(avg)
Points
(avg)
Ski Speed
Score
Hit Rate
Score
Range Time
Score
Total
Performance
Score
8SemerenkoValentinaUKR
310.031.0-0.23-0.37-0.32-0.28
8DzhimaYuliiaUKR
48.533.5-0.740.360.13-0.28
8PrymaArtemUKR
56.836.6-0.30-0.48-0.75-0.50
8PidruchnyiDmytroUKR
56.836.6-0.91-0.96-1.29-1.06

Czech Republic – Average Performance Score: -0.43

NoFamily NameGiven NameNationRacesRank
(avg)
Points
(avg)
Ski Speed
Score
Hit Rate
Score
Range Time
Score
Total
Performance
Score
9JislovaJessicaCZE
59.033.2-0.46-0.96-0.88-0.68
9DavidovaMarketaCZE
59.033.2-1.13-0.220.50-0.40
9KarlikMikulasCZE
413.327.8-0.640.451.050.13
9KrcmarMichalCZE
411.829.3-0.80-0.59-0.78-0.77

Austria – Average Performance Score: -0.37

NoFamily NameGiven NameNationRacesRank
(avg)
Points
(avg)
Ski Speed
Score
Hit Rate
Score
Range Time
Score
Total
Performance
Score
NoFamily NameGiven NameNationRacesRank
(avg)
Points
(avg)
Ski Speed
Score
Hit Rate
Score
Range Time
Score
Total
Performance
Score
10SchwaigerJuliaAUT
412.529.3-0.16-0.280.440.06
10HauserLisa TheresaAUT
38.338.7-1.030.540.21-0.37
10EderSimonAUT
511.232.8-0.54-0.58-1.09-0.76
10LeitnerFelixAUT
413.327.8-0.59-0.42-0.15-0.40

Posted in Statistical analysis | Tagged 2022 Winter Olympics

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