Statistical analysis – Page 6

Improvement season-to-season

Posted on 2021-11-28 | by

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

No	Family Name	Given Name	Nation	Races	Ski Speed Score	Hit Rate Score	Range Time Score	Total Performance Score	Change
No	Family Name	Given Name	Nation	Races	Ski Speed Score	Hit Rate Score	Range Time Score	Total Performance Score	Change
1	Todev	Blagoy	BUL	2	0.84	-0.53	-0.94	0.23	-1.06
2	Gow	Scott	CAN	2	-0.25	-1.56	-1.74	-0.81	-1.00
3	Dudchenko	Anton	UKR	2	-0.76	-0.53	-1.04	-0.73	-0.72
4	Brown	Jake	USA	2	-1.05	-0.53	1.02	-0.65	-0.54
5	Schommer	Paul	USA	2	-0.11	-1.21	-0.15	-0.44	-0.50
6	Desthieux	Simon	FRA	2	-1.53	-1.21	-0.72	-1.34	-0.49
7	Stvrtecky	Jakub	CZE	2	-0.78	-0.18	0.95	-0.40	-0.44
8	Kobonoki	Tsukasa	JPN	2	0.24	-1.21	0.33	-0.17	-0.41
9	Dovzan	Miha	SLO	2	0.17	-1.21	-1.40	-0.42	-0.40
10	Zahkna	Rene	EST	2	0.45	-0.87	0.43	0.07	-0.37
11	Strolia	Vytautas	LTU	2	-0.90	-0.53	1.30	-0.53	-0.36
12	Tsymbal	Bogdan	UKR	2	0.11	-0.53	-1.50	-0.27	-0.31
13	Stefansson	Malte	SWE	2	-0.21	1.19	0.86	0.32	-0.29
14	Claude	Fabien	FRA	2	-1.73	-0.18	-1.50	-1.26	-0.28
15	Gow	Christian	CAN	2	-0.47	-1.21	-1.33	-0.79	-0.27
16	Leitner	Felix	AUT	2	-1.08	-0.18	-0.55	-0.76	-0.27
17	Pidruchnyi	Dmytro	UKR	2	-0.54	-0.87	-0.82	-0.67	-0.24
18	Stalder	Sebastian	SUI	2	-0.04	-0.18	-0.97	-0.19	-0.22
19	Magazeev	Pavel	MDA	2	0.24	-0.53	-1.34	-0.17	-0.21
20	Latypov	Eduard	RUS	2	-1.00	-1.21	-0.01	-0.95	-0.15
21	Siimer	Kristo	EST	2	1.03	0.50	0.31	0.79	-0.10
22	Dombrovski	Karol	LTU	2	-0.35	-0.18	0.21	-0.23	-0.09
23	Claude	Florent	BEL	2	-0.22	-0.53	0.28	-0.25	-0.08
24	Nelin	Jesper	SWE	2	-1.32	-0.18	0.52	-0.77	-0.04
25	Femling	Peppe	SWE	2	-0.47	0.16	-1.29	-0.38	-0.02
26	Smolski	Anton	BLR	2	-1.28	-0.18	0.23	-0.78	-0.02
27	Lazouski	Dzmitry	BLR	2	-0.20	-0.18	1.04	-0.05	+0.01
28	Horn	Philipp	GER	2	-0.86	0.16	-0.90	-0.57	+0.05
29	Christiansen	Vetle Sjaastad	NOR	2	-1.50	-0.87	0.64	-1.06	+0.10
30	Boe	Tarjei	NOR	2	-1.38	-0.87	-0.59	-1.14	+0.10
31	Bormolini	Thomas	ITA	2	-0.31	-0.53	-0.93	-0.45	+0.10
32	Bauer	Klemen	SLO	2	-0.04	0.50	-1.09	-0.01	+0.11
33	Szczurek	Lukasz	POL	2	1.13	1.19	0.55	1.08	+0.11
34	Guigonnat	Antonin	FRA	2	-1.21	0.16	-0.39	-0.71	+0.11
35	Hiidensalo	Olli	FIN	2	-0.21	0.16	0.80	0.02	+0.12
36	Banys	Linas	LTU	2	0.95	0.50	-0.41	0.66	+0.12
37	Eder	Simon	AUT	2	-0.41	-1.21	-1.55	-0.78	+0.15
38	Slotins	Roberts	LAT	2	0.42	0.85	1.49	0.67	+0.15
39	Samuelsson	Sebastian	SWE	2	-2.00	0.16	0.44	-1.08	+0.15
40	Rees	Roman	GER	2	-0.90	0.16	-0.15	-0.50	+0.18
41	Mukhin	Alexandr	KAZ	2	0.28	0.85	0.45	0.46	+0.18
42	Varabei	Maksim	BLR	2	-0.95	1.19	1.39	-0.05	+0.20
43	Boe	Johannes Thingnes	NOR	2	-1.61	-1.21	0.02	-1.30	+0.20
44	Iliev	Vladimir	BUL	2	-0.46	0.50	0.38	-0.08	+0.22
45	Jacquelin	Emilien	FRA	2	-1.99	0.50	-0.63	-1.10	+0.23
46	Ozaki	Kosuke	JPN	2	-0.18	0.85	1.97	0.38	+0.26
47	Baloga	Matej	SVK	2	1.35	0.50	-0.14	0.92	+0.27
48	Trsan	Rok	SLO	2	1.20	-1.56	-0.68	0.18	+0.27
49	Windisch	Dominik	ITA	2	-0.42	1.19	-1.09	-0.03	+0.28
50	Loginov	Alexander	RUS	2	-1.21	0.16	-0.48	-0.73	+0.29
51	Langer	Thierry	BEL	2	-0.10	0.50	-0.08	0.08	+0.30
52	Rastic	Damir	SRB	2	0.66	0.50	3.22	0.92	+0.33
53	Bocharnikov	Sergey	BLR	2	-0.82	0.85	-0.79	-0.33	+0.34
54	Laegreid	Sturla Holm	NOR	2	-0.71	-1.56	-0.91	-0.98	+0.34
55	Fillon Maillet	Quentin	FRA	2	-1.36	-0.18	-0.71	-0.94	+0.39
56	Doll	Benedikt	GER	2	-0.98	-0.18	-0.28	-0.67	+0.39
57	Krcmar	Michal	CZE	2	-0.74	0.16	0.08	-0.38	+0.40
58	Fak	Jakov	SLO	2	-0.37	-1.21	-0.85	-0.67	+0.42
59	Harjula	Tuomas	FIN	2	0.62	0.16	-1.65	0.21	+0.43
60	Yaliotnau	Raman	BLR	2	-0.51	1.53	1.18	0.28	+0.43
61	Weger	Benjamin	SUI	2	-0.37	-0.87	0.17	-0.45	+0.43
62	Komatz	David	AUT	2	0.16	-0.53	0.54	0.01	+0.45
63	Guzik	Grzegorz	POL	2	0.14	1.19	0.71	0.51	+0.46
64	Bionaz	Didier	ITA	2	0.11	-0.18	0.61	0.09	+0.47
65	Doherty	Sean	USA	2	0.02	0.85	-0.24	0.23	+0.48
66	Sima	Michal	SVK	2	0.55	0.85	0.08	0.58	+0.54
67	Dale	Johannes	NOR	2	-1.24	0.16	0.88	-0.58	+0.64
68	Tachizaki	Mikito	JPN	2	1.03	-0.87	0.68	0.44	+0.65
69	Eberhard	Julian	AUT	2	0.06	0.16	-0.27	0.05	+0.72
70	Sinapov	Anton	BUL	2	0.42	1.53	0.76	0.78	+0.72
71	Eliseev	Matvey	RUS	2	0.71	-1.21	-0.26	0.04	+0.85
72	Vaclavik	Adam	CZE	2	0.03	1.88	1.19	0.70	+0.88
73	Ponsiluoma	Martin	SWE	2	-1.53	2.56	-1.12	-0.29	+0.91
74	Gerdzhikov	Dimitar	BUL	2	0.45	2.56	0.15	1.03	+0.99
75	Hofer	Lukas	ITA	2	0.14	-0.53	0.93	0.04	+1.00
76	Garanichev	Evgeniy	RUS	2	0.59	0.85	-0.80	0.50	+1.21

Women

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

No	Family Name	Given Name	Nation	Races	Ski Speed Score	Hit Rate Score	Range Time Score	Total Performance Score	Change
No	Family Name	Given Name	Nation	Races	Ski Speed Score	Hit Rate Score	Range Time Score	Total Performance Score	Change
1	Bendika	Baiba	LAT	2	-0.74	-0.87	-0.34	-0.73	-0.83
2	Lie	Lotte	BEL	2	-0.31	-1.28	-0.67	-0.63	-0.61
3	Sola	Hanna	BLR	2	-1.29	-0.05	-1.47	-0.95	-0.55
4	Nigmatullina	Uliana	RUS	2	-0.60	-1.68	-0.33	-0.88	-0.43
5	Magnusson	Anna	SWE	2	-0.72	-0.46	-0.13	-0.57	-0.37
6	Davidova	Marketa	CZE	2	-1.24	-1.68	-0.15	-1.24	-0.37
7	Klimina	Darya	KAZ	2	0.16	-0.05	2.04	0.33	-0.35
8	Jislova	Jessica	CZE	2	-0.37	-0.46	-0.51	-0.41	-0.30
9	Fialkova	Ivona	SVK	2	-0.48	1.18	0.35	0.10	-0.25
10	Alimbekava	Dzinara	BLR	2	-1.46	-1.28	-0.44	-1.29	-0.23
11	Weidel	Anna	GER	2	-0.09	-2.09	-0.74	-0.75	-0.23
12	Avvakumova	Ekaterina	KOR	2	0.27	-0.46	-0.06	0.02	-0.22
13	Lescinskaite	Gabriele	LTU	2	0.88	-1.68	0.76	0.12	-0.21
14	Charvatova	Lucie	CZE	2	-0.88	0.77	-1.04	-0.42	-0.19
15	Brorsson	Mona	SWE	2	-1.09	-0.46	-0.84	-0.88	-0.18
16	Bescond	Anais	FRA	2	-1.32	-0.05	-0.29	-0.83	-0.17
17	Puskarcikova	Eva	CZE	2	-0.44	-0.46	-0.11	-0.40	-0.16
18	Vittozzi	Lisa	ITA	2	-0.92	0.36	-1.99	-0.68	-0.15
19	Eder	Mari	FIN	2	-1.05	-0.05	1.45	-0.46	-0.14
20	Hauser	Lisa Theresa	AUT	2	-0.95	-0.87	-1.97	-1.05	-0.14
21	Kondratyeva	Anastassiya	KAZ	2	1.80	-0.87	3.00	1.17	-0.13
22	Chevalier-Bouchet	Anais	FRA	2	-1.21	-0.05	-1.16	-0.87	-0.10
23	Lien	Ida	NOR	2	-0.92	-0.05	1.01	-0.43	-0.07
24	Irwin	Deedra	USA	2	0.30	0.36	0.19	0.31	-0.05
25	Braisaz-Bouchet	Justine	FRA	2	-1.65	0.36	-0.40	-0.91	-0.05
26	Todorova	Milena	BUL	2	-0.65	0.77	-0.26	-0.19	-0.03
27	Kalkenberg	Emilie Aagheim	NOR	2	-0.25	-0.05	-0.71	-0.25	-0.01
28	Oeberg	Elvira	SWE	2	-2.15	0.77	-0.91	-1.15	+0.00
29	Dzhima	Yuliia	UKR	2	-0.74	-0.05	-0.23	-0.48	+0.03
30	Roeiseland	Marte Olsbu	NOR	2	-1.63	-0.46	-1.32	-1.25	+0.05
31	Herrmann	Denise	GER	2	-1.23	-0.87	0.41	-0.93	+0.06
32	Preuss	Franziska	GER	2	-1.51	-0.05	-0.83	-1.00	+0.06
33	Kruchinkina	Elena	BLR	2	-0.35	-0.05	-0.35	-0.26	+0.07
34	Mironova	Svetlana	RUS	2	-0.82	0.36	-0.44	-0.43	+0.11
35	Klemencic	Polona	SLO	2	0.02	1.18	0.13	0.37	+0.11
36	Tachizaki	Fuyuko	JPN	2	0.06	-0.87	0.93	-0.11	+0.12
37	Chevalier	Chloe	FRA	2	-1.02	1.18	-0.30	-0.29	+0.12
38	Lunder	Emma	CAN	2	-0.04	-1.28	-2.13	-0.65	+0.16
39	Egan	Clare	USA	2	-0.51	-0.46	0.51	-0.37	+0.17
40	Tomingas	Tuuli	EST	2	-0.31	-0.46	-0.01	-0.32	+0.18
41	Kuklina	Larisa	RUS	2	-0.58	-0.05	-0.61	-0.43	+0.19
42	Gasparin	Selina	SUI	2	-0.20	-0.05	-0.59	-0.20	+0.20
43	Persson	Linn	SWE	2	-1.21	0.77	-0.99	-0.61	+0.21
44	Hinz	Vanessa	GER	2	-0.31	-0.46	-0.13	-0.33	+0.21
45	Kocergina	Natalja	LTU	2	0.41	0.36	1.16	0.49	+0.24
46	Hettich	Janina	GER	2	-0.51	-0.05	-0.61	-0.39	+0.25
47	Lehtla	Kadri	EST	2	1.76	-1.28	-0.41	0.62	+0.32
48	Tandrevold	Ingrid Landmark	NOR	2	-1.19	-0.05	0.46	-0.66	+0.33
49	Eckhoff	Tiril	NOR	2	-1.63	1.18	-0.82	-0.71	+0.34
50	Oeberg	Hanna	SWE	2	-1.67	0.77	-1.40	-0.93	+0.34
51	Hojnisz-Starega	Monika	POL	2	-0.33	0.36	-0.20	-0.11	+0.35
52	Kadeva	Daniela	BUL	2	0.61	0.77	-0.06	0.58	+0.38
53	Janka	Erika	FIN	2	1.50	0.36	-0.19	0.97	+0.38
54	Beaudry	Sarah	CAN	2	1.26	-1.28	-0.90	0.27	+0.41
55	Haecki	Lena	SUI	2	-0.23	0.36	-1.25	-0.18	+0.41
56	Knotten	Karoline Offigstad	NOR	2	0.23	-1.68	-1.25	-0.50	+0.42
57	Maeda	Sari	JPN	2	-1.01	3.23	-0.57	0.27	+0.42
58	Zdouc	Dunja	AUT	2	0.51	-1.28	-0.40	-0.11	+0.42
59	Gasparin	Elisa	SUI	2	-0.12	0.36	-0.12	0.02	+0.49
60	Gasparin	Aita	SUI	2	0.04	0.36	-0.80	0.03	+0.49
61	Schwaiger	Julia	AUT	2	0.07	-0.46	0.32	-0.05	+0.49
62	Zuk	Kamila	POL	2	-0.33	1.59	0.75	0.36	+0.58
63	Simon	Julia	FRA	2	-1.12	1.59	-1.38	-0.36	+0.58
64	Wierer	Dorothea	ITA	2	-1.16	-0.05	1.65	-0.50	+0.59
65	Minkkinen	Suvi	FIN	2	0.51	-0.05	0.55	0.36	+0.60
66	Horvatova	Henrieta	SVK	2	2.24	-0.46	-0.11	1.18	+0.61
67	Rieder	Christina	AUT	2	0.61	-0.46	0.31	0.27	+0.61
68	Semerenko	Valentina	UKR	2	0.14	-0.05	-0.86	-0.03	+0.62
69	Bekh	Ekaterina	UKR	2	0.39	1.59	-0.95	0.58	+0.66
70	Leshchanka	Iryna	BLR	2	-0.11	0.36	0.56	0.11	+0.79
71	Reid	Joanne	USA	2	-0.15	1.59	1.37	0.53	+0.81
72	Talihaerm	Johanna	EST	2	0.88	1.18	1.12	1.00	+0.83
73	Hachisuka	Asuka	JPN	2	1.71	1.59	1.89	1.70	+1.08
74	Sabule	Annija	LAT	2	2.91	0.77	-0.01	1.94	+1.20
75	Kazakevich	Irina	RUS	2	-0.69	3.64	0.53	0.71	+1.31

Arnd Peiffer: Biathlon Legend?

Posted on 2021-07-16 | by

Brian Halligan | Leave a Comment

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.

Why the French weren’t more competitive

Posted on 2021-06-26 | by

biathlonanalytics | Leave a Comment

Introduction

After the 2019-2020 season, Martin Fourcade retired from biathlon, leaving a strong group of athletes on the French men’s team. They appeared ready to challenge the Norwegians, with Q Fillion Maillet and E Jacquelin the main contenders already having a good season and getting close in the 2019-2020 season. However, the 2020-2021 season turned out a little different, with still strong performances from all French team members, but it quickly felt they were not going to challenge for the yellow bib.

This analysis tries to find out where things stagnated for the French and prevented QFM and EJ from at least challenging for the crystal globe(s).

World Cup Points

First, I wanted to see how the World Cup Points compared to the eventual yellow bib winner, per season (which happened to be this fella called JT Boe all three seasons!). The charts below show Johannes Tingnes Boe in red, Quentin Fillon Maillet in dark blue and Emilien Jacquelin in light blue:

We can see that after closing the gap with JT Boe in the 2019-2020 season, it has widened again on the 2020-2021 season, mostly for QFM but to some degree for EJ as well. Now let’s look at the discipline level:

The Sprint and Pursuit events show the same story, being very close to Boe in 2019-2020 but losing ground in 2020-2021, especially in the sprint. In the Sprint, EJ is behind QFM in every season, but for the Pursuit EJ first follows, then equals and eventually surpasses QFM in the last season.

The Individual and Mass Starts were the events where most progress were made, as QFM actually does better than Boe in the last season and is very close in all three seasons in the Mass Start. EJ drops in the final season compared to the previous one.

Ski speed

Now let’s look at more detail, starting with ski speed compared to the field’s average. Note that the vertical axis is reversed, as -4 means 4% below the field average, which is a good thing, so it should be at the top.

It’s no surprise that JT Boe is the fastest of the three but where in 2019-2020 the Frenchmen were seemingly getting closer, the gap widened again in last season:

This was due to JT Boe being even faster, but both Frenchmen losing speed compared to the field average. They are still quite a bit faster than the field average, but clearly need to rely on shooting time and quality if they want to catch up. Let’s look at that next.

Range Time

Looking at the time on the range we can see this is where the French athletes gain time on Boe, not in the least due to Boe getting slower, but QFM and EJ are also getting faster from one season to the next. We noticed Boe having some shooting struggles, and I also clearly remember the super fast shooting by EJ at the World Championships. He also proved later in the season the fast shooting doesn’t always work out, but generally I would say the French are stronger here.

Of course a fast range time only works well when you hit most targets, so that the next thing we’ll look at.

Shooting Time and Percentage

The chart below shows combined Shooting Percentage from left to right and Shooting Time compared to Field Average from bottom to top. It then plots the three seasons per athlete to show the change and development from season to season. Generally EJ is in the top left corner, meaning he shoots fast but not most accurately. QFM has started shooting faster but lost some shooting quality. Boe is clearly the slower shooter of the three, and although his percentage was up in the 2019-2020 season, last season he dropped back to around 85%, the lowest of the three.

Conclusions

Since Boe is still by far the fastest skier, the Frenchmen needed to keep the distance in ski speed as small as possible, which they failed to do in the last season as the gap widened. They do perform better in the shooting range though and if Boe continues to struggle this would be an area where the Frenchmen can gain the most ground. Even if the existing difference in shooting speed and quality stays the same as last season, closing the gap a little on the skis will allow them to be more competitive again for the upcoming season. According to the guys at Sport in Depth (I wrote about them in my previous article), they will still end up behind Boe (and Laegreid). I can’t wait for the new season to get started so we can actually find out for ourselves!

Predicting race results

Posted on 2021-06-18 | by

biathlonanalytics | Leave a Comment

In February I wrote about a Tableau report that didn’t necessarily predict race outcomes for the World Championships but helped inform people to make better predictions or guesses. I still believe it helps to know who’s hot and not (recent race results), previous race results at the venue and discipline, and current standing in the World Cup, but I ran into a website that has built a model to predict race and season outcomes, and their results are interesting, to say the least.

When you consider how unpredictable biathlon can be, any decent results from a model are impressive if you ask me. In this article they describe how their model did against reality, and the results were good in many cases. In addition they have more articles evaluating their performance, and I would agree that they did well.

But models remain exactly that, models. And I am sure if the IBU held 150,000 races the reality would be closer to the models. But that’s the beauty of sport and biathlon: we don’t run the races that many time, so we have to consider the form of the day, athletes feeling sick but still participating, harder and softer snow conditions during the race, a loud crowd at the shooting range (remember those days?!?), etc. we can go and on about external qualitative factors that can, and will, impact race results. If a model predicts Laegreid to challenge for the yellow bib, and Hauser to win a specific race, I think they are on to something worth checking out.

I’m no betting person so I don’t see myself using it for that purpose ever, although I did participate in a fun fantasy game that relies on race predictions to determine the “most knowledgable biathlon person”. But in line with the dashboard I created myself, I think the model does a good job providing additional information that can help inform predictions, and also give more insight into biathlon and its athletes. And in the end, I’m happy it doesn’t predict race results with 95% certainty, as that would quickly end my interest in biathlon altogether!

The Story Of Tiril Eckhoff

Posted on 2021-06-18 | by

Brian Halligan | Leave a Comment

This victory in Oestersund marked Tiril Eckhoffs record breaking 13th victory in a single season. Breaking Magdelena Forsberg’s record of 12 victories in the 2000-2001 season. While biathlon fans today are familiar with the bubbly and exciting personality that Tiril is known for, this impressive accomplishment didn’t come easy. In today’s video, we will dive deep into the career of Tiril Eckhoff and see how the record that captivated fans during the 2021 season was an accomplishment of hard work and breaking through personal barriers.

Hopes were high for the young Norwegian athlete. At only 21 years old, Eckhoff had earned some impressive results at the IBU Junior World Championships only weeks prior to her W.C. debut: All of Norway could see the young athlete had a lot of promise and hopes for the future were high. Eckhoff continued to improve on the skis and established herself as one of the fastest skiers on the circuit by the 2013-2014 season and consistently earned in the top 20 results. Eckhoff earned a place on the Norwegian Olympic team and helped the women’s team capture a gold medal in the Sochi relay.

Tiril started off the 2014/15 season with a bang: earning her first world cup win by shooting 90% in the Oestersund Sprint. Despite Eckhoff consistently placing in the top 10 in ski speed and skiing 4.2% faster than the average biathlete, Tiril had a hole in her performance that would hold her back and actually make her finish lower in the standings than the previous season: a 79.4% shooting percentage. And specifically, a 74.1% standing percentage. Six times Tiril would clean her prone stage only to spoil the race with standing misses. In fact, Tiril only cleaned her standing twice during this season, and both times she did that she earned podium finishes. So what was Tirils plan to combat this weakness in her game: Ski faster! This plateau continued for several seasons: It was the same old story of fast skiing, good prone shooting and meltdowns in the standing stages.

Despite her plateau Eckhoff would occasionally excite the norwegian fan base with stellar performances. Most notably, her performance at the 2016 IBU World Championships at her home stadium of Oslo Holmenkollen. In front of the King of Norway, Eckhoff performed at her best winning the Sprint competition with clean shooting and helping the Norwegian Women’s relay team claim victory by bringing the team from 9th to 1st without missing a shot on the third leg.

In 2017 rumors began circulating that Tiril was having some issues with her vision and was focusing on rehabilitating her eyes. She told IBU TV she had “double vision” and spent a lot of time in the summer focusing on what she sees when she looks through the sights.

The results of her hard work began paying off in the 2019/2020 season where she bumped her shooting percentage up to 83% and skied 5.3% faster than the average athlete. This jump in the shooting percentages helped Tiril break through the ceiling and get back into the top 10 overall. Winning 7 races during the season and battled Italy’s Dorothea Wierer for the overall globe through the entire season which was cut due to the Covid-19 pandemic.

As mentioned in the beginning of the video, Tiril would go on to win 13 races this season and set a Women’s World Cup record. But the interesting thing about this accomplishment is when you look at her stats on the season, she actually under performed in the key areas that propped her up in previous seasons.

The area that gave Tiril her edge was the one piece that plagued her in the past: her standing shooting. Up a full 10% from the season before, Tiril had honed in the standing targets and was able to close the door on great victories. We see this all too often in biathlon where an athlete ruins a good race with poor standing shooting. And we also see examples of athletes coming back from poor starts to finish strong with good shooting in the later stages.

When you look at the numbers, this concept makes sense. In a typical 12.5k Women’s mass start each lap it takes the fastest skiers approximately 6:20 to ski the 2.5k course, this means at the completion of the last shooting an athlete only has 17.5% of the race remaining to make a comeback if needed. Whereas after the prone shooting 60% of the race remains.

Tiril Eckhoff’s dedication to focusing on her performance weaknesses and ability to break through her results plateau is a lesson for athletes around the world. Sticking with the training, and continuing to work hard can help you achieve new heights. It will be interesting to see if Tiril can continue her success this upcoming season. And it would be exciting to see what she could do if she could combine her new found standing ability with her highest prone percentages of years past.