RGP_Posters_long_final by biathlonworld

RESEARCH GRANT PROGRAMME

AGENDA 2025/26 – 4 Projects...............................03-11 2024/25 – 3 Projects...............................12-19 2023/24 – 6 Projects...............................20-33 2022/23 – 5 Projects...............................34-45 2021/22 – 4 Projects...............................46-55

RGP 2025/26

RESEARCH GRANT PROGRAMME

2025/26

RGP 2025/26

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AGENDA 25/26 PROJECT 1 – Academy of Physical Education Katowice.........05-07

PROJECT 2 – KIHU Finland...................................................08-09

PROJECT 3 – University of Salzburg.....................................10-11

RGP 2025/26

WHY DO YOUNG BIATHLETES STAY OR QUIT? EXAMINING MOTIVATION, DROPOUT, AND SOCIOECONOMIC INFLUENCES Anna Akbaş1, Zbigniew Waśkiewicz1, Amelie Heinrich2, Suvi Heikkinen3, Veerle De Bosscher4

KEY FACTS SAMPLE 101 former & 367 active youth biathletes, surveyed in 23 languages DESIGN International survey of dropout reasons and motivational profiles METHODOLOGY ADQ & SMS-II; factor, cluster (k-means) & regression analysis CORE FINDINGS Environment - family support, injuries, coach support outweighs performance and socioeconomic factors

WHAT MAKES YOUNG BIATHLETES QUIT? Dropout Reasons and Predictors of Athlete Disengagement in International Youth Biathlon Waśkiewicz Z.1, Heinrich A.2, Heikkinen S.3, Mukhambet Z.4, De Bosscher V.5,, Akbaş A.1 1Institute of Sport Sciences, Academy of Physical Education, Katowice, Poland 2Department of Sports Sciences, Social and Health Sciences, University of Konstanz, Germany 3School of Business and Economics, University of Jyväskylä, Finland 4Academy of Physical Education and Mass Sport, Astana, Kazakhstan 5Department of Movement and Sport Sciences, Vrije Universiteit Brussel, Brussels, Belgium

RESULTS

BACKGROUND Youth athlete dropout remains one of the greatest challenges in competitive sport. Despite its importance, little international evidence exists on why young biathletes discontinue their careers.

Family support, injuries and external pressures outweigh performancerelated reasons.

AIM: To identify the main reasons for dropout and examine the key dimensions and predictors of athlete disengagement

ATHLETE DROPOUT IS DRIVEN BY THE ENVIRONMENT, NOT BY PERFORMANCE METHODS

Five distinct disengagement dimensions explained 66% of variance

101

21 ± 4.5

countries

former biathletes (44.6% female)

mean age at drop-out No single intervention will fix dropout — each dimension has a distinct driver

Open-ended responses provided qualitative support for the quantitative findings.

MEASURES • • •

Perceived dropout reasons Autonomy in sport participation Athlete disengagement dimensions

STATISTICAL ANALYSIS

INSTRUMENTS

ADQ

•

Athlete Disengagement Questionnaire

• •

online survey in 23 languages

Exploratory factor analysis Regression analysis Thematic analysis

FUNDING This study was funded by the IBU Research Grant Programme (Grant No. S002157, €12,500). Principal Investigator: Dr Anna Akbaş

📧 a.akbas@awf.katowice.pl | ORCID 🔗 0000-0002-1244-1853 This poster presents results from the final stage of the project.

WHAT KEEPS YOUNG BIATHLETES MOTIVATED? Motivational Profiles and Predictors of Self-Determined Motivation in International Youth Biathlon Akbaş A.1, Heinrich A.2, Heikkinen S.3, Mukhambet Z.4, De Bosscher V.5, Waśkiewicz Z.1 1Institute of Sport Sciences, Academy of Physical Education, Katowice, Poland 2Department of Sports Sciences, Social and Health Sciences, University of Konstanz, Germany 3School of Business and Economics, University of Jyväskylä, Finland 4Academy of Physical Education and Mass Sport, Astana, Kazakhstan 5Department of Movement and Sport Sciences, Vrije Universiteit Brussel, Brussels, Belgium

RESULTS

BACKGROUND Self-determined motivation is a key predictor of longterm sport participation, yet little is known about motivational profiles of young biathletes.

Most athletes are autonomously motivated, but females report higher external pressure

AIM: To identify motivational profiles and predictors of self-determined motivation in young biathletes.

THE TRAINING ENVIRONMENT — NOT BACKGROUND — IS THE STRONGEST PREDICTOR OF SELF-DETERMINED MOTIVATION Coach support and perceived progress matter more than socioeconomic factors

METHODS

41 countries

367 active biathletes (49.3% female)

16-23 years old

1 in 4 athletes shows an at-risk motivational profile

Coach support and perceived progress matter more than socioeconomic factors

• • •

STATISTICAL ANALYSIS

MEASURES

INSTRUMENTS

Intrinsic & extrinsic motivation Amotivation Self-Determination Index (SDI)

SMS-II

• •

online survey in 23 languages

•

Descriptive statistics Cluster analysis (kmeans) Hierarchical regression

FUNDING This study was funded by the IBU Research Grant Programme (Grant No. S002157, €12,500). Principal Investigator: Dr Anna Akbaş

📧 a.akbas@awf.katowice.pl | ORCID 🔗 0000-0002-1244-1853 This poster presents results from the final stage of the project.

RGP 2025/26

PERFORMANCE-DETERMINING FACTORS IN ELITE PRONE SHOOTING AT REST AND AFTER EXERCISE OF VARYING INTENSITY Esa Hynynen1, Miika Köykkä1,2, Keijo Ruotsalainen2, Vesa Linnamo2

KEY FACTS SAMPLE N = 20 elite biathletes (National Teams of Finland & USA) DESIGN Laboratory simulation comparing prone shooting across 3 loads METHODOLOGY Optical tracking (Noptel ST 2000), PCA & multiple regression CORE FINDINGS Under-stress variance drops from 93% (rest) to 84% (race intensity)

Performance-Determining Factors in Elite Biathlon Prone Shooting at Rest and After Exercise of Varying Intensity

IBU

Isaac Burgess, Esa Hynynen, Keijo Ruotsalainen, Vesa Linnamo, James Becker, Miika Köykkä

IBU

Project Overview • Ski speed during competition accounts for about 50% of performance differences between biathletes, but a single missed target often separating medalists from non-medalists. • Biathlon shooting is performed under high physiological stress; however little research has investigated technical determinants of performance at rest and after intense exercise. Purpose: Determine the technical factors most strongly associated with biathlon prone shooting performance at rest and following exercise at different intensities in elite biathletes.

Methodology • 20 elite biathletes from the national teams of Finland and the United States participated in the study. • Aiming point trajectories during each labsimulated competition shooting bout (5shot series) were captured using a Noptel ST 2000 optical tracking device (67 Hz) on a single target.

Shooting performance evaluated under three conditions: 1. Rest 2. Immediately after skiing at threshold intensity 3. And race intensity

• Principal component analyses (PCA) with varimax rotation were used to extract factors from the aimpoint trajectory variables, based on prior research. • Surrogate scores were calculated for each extracted factor by standardizing and averaging the aimpoint variables that loaded onto them. • Surrogates entered multiple regression models to evaluate predictive ability of mean shooting performance at each condition.

Main Findings Four technical factors consistently described prone shooting across all physiological states: Stability of Hold (SoH), Aiming Accuracy (AA), Cleanness of Triggering (CoT), and Timing of Triggering (ToT). • These factors described most of the variance in prone

shooting whether the athlete was at rest (83.7%), threshold (81.6%), or race (80.3%).

• The importance of each factor in the model shifted

substantially from rest, where AA, CoT, and ToT were all significant predictors, to race intensity, where only AA was a significant predictor in the model.

Surrogate scores predicted mean shooting performance very well at rest but decreased by 11% at threshold, and 9% race intensities

• Mean shooting performance at rest was strongly

correlated with performance at threshold (ρ = 0.60, p = 0.006) and at race (ρ = 0.63, p = 0.003).

Recommendations and Applications • Prioritize aiming accuracy under high load. Since AA is the dominant predictor of performance at race

intensity, training should focus on the ability to center the target with physiological stressors such as high heart rate and heavy breathing.

• Use surrogate scores for precision coaching. Instead of just looking at hits and misses, coaches may be able

to use the four-factor model to identify why an athlete is missing. Is it a loss of stability (SoH) or a failure in accuracy (AA)? This may allow for individualized technical corrections and tracking training over time.

This project was funded by the International Biathlon Union Research Grant Program. Thank you to the athletes and coaches from Finnish and United States National teams for participating and cooperating in this study.

RGP 2025/26

REALISTIC RECOIL SIMULATION FOR ROUNDFREE RIFLE TRAINING Christoph Thorwartl1, Thomas Grah1, Alexander Kösters2

KEY FACTS SAMPLE Anschütz LaserPower rifle platform with pneumatic recoil simulation DESIGN Proof-of-concept for round-free, recoil-simulating dry-fire training METHODOLOGY Rifle-mounted IMU; acceleration, angular velocity & signal consistency across settings CORE FINDINGS Generated measurable, repeatable and adjustable recoil-like rifle motion

DEVELOPMENT OF A PNEUMATIC RECOIL DEMONSTRATOR FOR BIATHLON Christoph Thorwartl1, Thomas Grah1, Mathias Schmoigl-Tonis1, Michael Buchecker2 and Alexander Kösteres2 Salzburg Research Forschungsgesellschaft m.b.H., Austria1 Department of Sport and Exercise Science, University of Salzburg, Austria 2

Abstract:

Dry-fire training is widely used in biathlon, but conventional systems do not reproduce the

mechanical recoil of live .22 LR shooting. The reCoil project developed an adjustable, sensor-integrated pneumatic recoil demonstrator and quantitatively compared its response with live-fire shooting. The prototype generated measurable, repeatable, and technically tunable recoil-like rifle motion. At 8 bar, peak recoil acceleration remained 61.3% below the live-fire reference, identifying recoil magnitude as the main technical limitation. In parallel, a Body and Sports-Equipment Sensor Network (BSSN) and the reCoil reView tool were established for integrated shot-related sensing, mobile control, and synchronized data analysis.

INTRODUCTION

RESULTS

Biathlon shooting performance depends on rifle stability, aiming behaviour, trigger control,

The pneumatic demonstrator generated clearly detectable, repeatable, and adjustable recoil-

and effective follow-through, particularly under physiological and psychological strain

like rifle motion. Both cylinder configuration and operating pressure systematically influenced

(Laaksonen et al., 2018; Sattlecker et al., 2017). Dry-fire and laser-based systems enable

translational and rotational responses. Live .22 LR shooting produced a mean negative Acc X

safe, repeatable, and resource-efficient training but largely omit the mechanical recoil event

peak of −94.7 m/s², compared with −36.6 m/s² at 8 bar for the simulator. The simulated peak

of live .22 LR shooting. As a result, relevant aspects of post-shot rifle motion, athlete–rifle

therefore remained 61.3% below the live-fire reference. Linear extrapolation suggested

interaction, force transmission, and sensory feedback remain unrepresented. The reCoil

approximately 22 bar to reach the measured live-fire peak acceleration (Figure 2). The

project addresses this gap by combining controllable recoil generation with sensor-based

implemented BSSN enabled bidirectional communication, shot-related sensor integration,

measurement and mobile interaction in a round-free biathlon training platform.

mobile recoil control, and synchronized data review (Figure 3a and 3b). 60

AIM

Acc X recoil: simulated pressure levels vs real shooting -20

Negative Acc X peak vs pressure: extrapolation to real shooting target Required 21.58 bar 6 bar shots 7 bar shots 8 bar shots Simulated mean +/- SD Real shooting target Linear fit/extrapolation Required pressure

-30

20 -40 0

To establish the technical basis for a realistic, adjustable, and sensor-integrated recoil

-20

simulator for biathlon by:

-40

-50 -60

 developing a functional recoil demonstrator,

-60

 characterizing and tuning its recoil response,

-80

 benchmarking it against live .22 LR shooting, and

-100

 establishing an integrated Body and Sports-Equipment Sensor Network (BSSN).

-120 -0.01

-70 -80 Real shooting Simulated 6 bar Simulated 7 bar Simulated 8 bar

-0.005

0.005

0.01

0.015

0.02

Time relative to detected recoil event [s]

0.025

-90

0.03

-100

Mean real-shooting negative Acc X peak

Pressure setting [bar]

Figure 2: Live versus simulated recoil at 6, 7, and 8 bar, with linear pressure extrapolation to the mean live-fire peak acceleration.

METHOD Mechanical, electromagnetic, and pneumatic recoil-generation concepts were evaluated regarding compactness, adjustability, integration potential, and development feasibility. A pneumatic concept was selected and integrated into an Anschütz LaserPower rifle platform with electronic trigger detection, microcontroller-based valve control, smartphone interaction, and a modular 3D-printed stock. Rifle motion was quantified using an IMU while cylinder configuration and operating pressure were systematically varied. The selected configuration was subsequently compared with live .22 LR shooting. In parallel, a BLE-based BSSN and the reCoil reView tool were developed to integrate rifle motion, trigger and buttstock signals, mobile control, and synchronized shotevent analysis.

Figure 3: CIMO AI Shot Analyzer for real-time IMU and force data monitoring and reCoil reView for synchronized playback and analysis of 10-s shot-centered sensor recordings.

DISCUSSION AND CONCLUSION A functional pneumatic recoil demonstrator was developed, systematically characterized, and quantitatively benchmarked against live .22 LR shooting. Together with the BSSN architecture and reCoil reView, the system provides a foundation for integrating recoil generation with sensor-based analysis and mobile interaction. The current system should be considered a technology demonstrator rather than a validated replacement for liveammunition recoil. Its main technical limitation is insufficient recoil magnitude: linear

(a)

(b)

Figure 1: 3D-printed ReCoil prototype integrated into the laser rifle platform. (a) Overview of the prototype showing the custom housing and integration of the recoil unit, electronics and wiring. (b) Detailed view of the rear assembly including actuator mounting, guide elements, control electronics and shoulder-contact interface.

REFERENCES

extrapolation indicated that approximately 22 bar would be required to reach the measured live-fire peak acceleration. A promising development route is a compact N₂O-based pneumatic supply, providing sufficient pressure reserve for a regulated and modular system. Future work should focus on increasing recoil fidelity, advancing sensor integration, and evaluating perceived realism and training transfer in athletes.

Laaksonen, M. S., Finkenzeller, T., Holmberg, H.-C., & Sattlecker, G. (2018). The influence of physiobiomechanical parameters, technical aspects of biathlon shooting, and psychophysiological factors on biathlon performance: A review. Journal of Sport and Health Science, 7, 394–404. Sattlecker, G., Buchecker, M., Gressenbauer, C., Müller, E., & Lindinger, S. (2017). Factors discriminating high from low score performance in biathlon shooting. International Journal of Sports Physiology and Performance, 12, 377–384.

RESEARCH GRANT PROGRAMME

2024/25

RGP 2024/25 Click here for More Infos & Downloads

AGENDA 24/25 PROJECT 1 – MidSweden University..............................................14-15 Monitoring and Managing Menstrual cycle symptoms in high performing female biathletes: A biopsychological approach PROJECT 2 – Østfold University College........................................16-17 Symptoms of REDs and mental health in young biathletes, and coaches’ knowledge of REDs and eating disorders PROJECT 3 – Montana State University..........................................18-19 Psychologic and biomechanical effects of manipulating rifle carriage position (high vs. low) and harness tightness (tight vs. loose)

RGP 2024/25

“MONITORING AND MANAGING MENSTRUAL CYCLE SYMPTOMS IN HIGH-PERFORMING FEMALE BIATHLETES: A BIOPSYCHOSOCIAL APPROACH” Kerry McGawley1, Nathalie Brown2, Guro Strøm Solli3, Madison Taylor1 , Heidi Kuuttinen1

KEY FACTS SAMPLE 2 female athletes (cross country & biathlon) DESIGN 3 studies across 4 menstrual cycles METHODOLOGY Symptom, blood-loss & hormone monitoring CORE FINDINGS High individual variability; inconsistent symptom management -> need for individualized support-

RGP 2024/25

SYMPTOMS OF REDs AND MENTAL HEALTH IN YOUNG BIATHLETES, AND COACHES’ KNOWLEDGE OF REDs AND EATING DISORDERS Therese Fostervold Mathisen1, Christine Sundgot-Borgen2, Anne Mette Rustaden3, Inger Johanne Løkkevik3, Lindsay Macnaughton4, Helge Einar Lundberg5 , Jorunn Sundgot-Borgen5 1 Faculty of Health, Welfare and Organisation, Østfold University College, Fredrikstad, Norway. 2 Department of Psychology, University of Oslo, Oslo, Norway. 3 Faculty of Social and Health Sciences, University of Inland Norway, Lillehammer, Norway 4 Department of Sport and Exercise Sciences, Durham University, Durham, Norway. 5 Institute of Sports Medicine, Norwegian School of Sport Sciences, Oslo, Norway

KEY FACTS SAMPLE N = 73 young biathletes (16-20) & 33 coaches DESIGN Cross-sectional study; 2 sub-studies METHODOLOGY Questionnaires, DXA, RMR & blood tests CORE FINDINGS REDs (Relative Energy Deficiency) & mental health issues prevalent, especially in females; coaches need improved REDS/ LEA knowledge

RGP 2024/25

PSYCHOLOGIC AND BIOMECHANICAL EFFECTS OF MANIPULATING RIFLE CARRIAGE POSITION (high vs. low) AND HARNESS TIGHTNESS (tight vs. loose) James Becker, Ethan Livingood, Isaac Burgess

KEY FACTS SAMPLE N = 16 well-trained biathletes DESIGN 5 rifle position & harness configurations during roller skiing METHODOLOGY Respiratory, heart rate, 3D kinematics & plantar forces

CORE FINDINGS High/tight configuration improved skiing economy by 4.8% & reduced oxygen consumption by 5.2%

RESEARCH GRANT PROGRAMME

2023/24

RGP 2023/24

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AGENDA 23/24 PROJECT 1 – AECC University...............................................22-23 Visual requirements of the Elite Biathlete

PROJECT 2 – University of Alberta.........................................24-25 “It’s something that needs to be heard”: National Team Athletes’ Experiences of the Menstrual Cycle PROJECT 3 – Technical University of Munich.........................26-27 Influence of caffeine on biathlon performance during a simulated competition PROJECT 4 – Northumbria University....................................28-29 Pacing behavior and athlete perceptions with and without shooting in highly trained biathletes PROJECT 5 – University of Salzburg......................................30-31 Assessing the impact of trigger control on shooting performance and the feasibility of recoil simulation for training in biathlon

PROJECT 6 – Texas A&M University......................................32-33 Scope 3 environmental impact: assessing fan modes of transportation

RGP 2023/24

VISUAL REQUIREMENTS OF THE ELITE BIATHLETE Dr. Zöe L. Wimshurst1, Miika Köykkä2,3, Professor Vesa Linnamo1

KEY FACTS SAMPLE 56 survey responses; 27 national-level biathletes tested

DESIGN Two-phase study comparing perceived vs. actual visual skills in biathlon prone shooting METHODOLOGY Likert Survey followed by 8 visual tests paired with optoelectronic shooting metrics. Sensor shooting metrics CORE FINDINGS Saccadic eye movements strongly predict shooting performance

RGP 2023/24

“IT’S SOMETHING THAT NEEDS TO BE HEARD”: NATIONAL TEAM ATHLETES’ EXPERIENCES OF THE MENSTRUAL CYCLE Helene Jørgensen1, Margie H. Davenport1, Nick L. Holt2, Tara-Leigh McHugh2

1 Faculty of Kinesiology, Sport, and Reaction, University of Alberta, Edmonton, Canada 2 Faculty of Kinesiology, University of Calgary, Canada

KEY FACTS SAMPLE N = 17 female biathletes (17-25) competing at international levels DESIGN Qualitative description (QD) study examining athletes’ lived experiences

METHODOLOGY Individual Semi-structured interviews CORE FINDINGS MC impacts vary widely, reaching from abdominal pain to psychological symptoms (drops in confidence and motivation)

RGP 2023/24

INFLUENCE OF CAFFEINE ON BIATHLON PERFORMANCE DURING A SIMULATED COMPETITION Koehler, K.1, Engel, H.1, Yilmaz, C.1, Appelhans, D.1, Mathieu, J.2, Kock, H.2, Staunton C.3

KEY FACTS SAMPLE N = 9 national and international biathletes (male) DESIGN Randomized, double-blind, cross-over study in Oberhof METHODOLOGY Ingested 3mg/kg caffeine or placebo before a simulated race

CORE FINDINGS Caffeine boosted early skiing speed but dropped standing shooting accuracy by ~10%

RGP 2023/24

PACING BEHAVIOR AND ATHLETE PERCEPTIONS WITH AND WITHOUT SHOOTING IN HIGHLY TRAINED BIATHLETES Florentina Johanna Hettinga1, Thomas Johansen Losnegard2, Jan Kocbach2, Kandianos Emmanouil Sakalidis1

1 Northumbria University, UK 2 Norwegian School of Sports Sciences, Norway

KEY FACTS SAMPLE N = 20 senior biathletes (11 female, 9 male)

DESIGN Randomized trial comparing a biathlon sprint vs. cross-country sprint METHODOLOGY Measuring physiological and pacing data during 7.5/ 10 km skiing with vs. without shooting

CORE FINDINGS Athletes skied 1.5% faster without shooting – slowing down ~300𝑚 before the range to preserve accuracy

Pacing behavior and athlete perceptions with and without shooting in highly trained biathletes Thomas Johansen Losnegard; Erland Stubbe; Kandianos Emmanouil Sakalidis; Florentina Johanna Hettinga

Introduction

Methodology

Biathlon involves pacing, a critical self-regulatory factor in sport performance that encompasses goal-setting, monitoring, and self-reﬂecting. However, the impact of shooting on pacing remains unexplored. This study aims to enhance our understanding of pacing behavior and shooting in biathlon by investigating differences in performance, physical and biopsychological stress, and decision-making during races with and without shooting.

Participants • Eleven women (age 21 ± 2 yrs) • 9 men (age 22 ± 3 yrs) Procedure • Two time-trials—cross-country skiing and biathlon—separated by 72 hours. • Female completed 7.5 km (3 x 2.5 km) course; male completed 10 km (3 x 3.3 km) course. • Location: Birkebeiner ski area, Lillehammer, Norway.

Methodology

Results

Measurements • Kinematic data --> integrated IMU and GNSS unit. • Heart rate (HR) --> Polar M40 heart rate monitors. • Rate of Perceived Exertion (RPE) --> 6-20 scale. • Questionnaire (experience, applied pacing strategy, shooting related questions).

• A signiﬁcant difference was observed in the overall competition time between biathlon and cross-country skiing (26:39 ± 1:44 vs 25:02 ± 1:47 min; mean ± 95% CI; -6.5% ± 1.2%, P<0.05). • HR: No signiﬁcant differences.

Statistical Analysis • Paired sample t-tests/ unpaired sample t-tests Wilcoxon signed-rank tests - Median (Mdn) and Interquartile Range (IQR) • P-value ≤ 0.05 (Microsoft Office Excel 2013 and SPSS)

Figure 1: Time differences between cross country skiing and biathlon trials. Men to right and women left.

Results

Discussion

• RPE: Signiﬁcant difference between biathlon (145.8 ± 7.8) and cross-country skiing (150.0 ± 6.8), P < 0.01. • No difference in the use of perceptual information in both biathlon and cross-country skiing trials.

• Participants demonstrated a "J-shaped" lap-to-lap pacing profile during the biathlon trial. • The act of shooting significantly affects the pacing strategy in biathlon. • Participants decreased their intensity before both prone and standing shooting. • Participants adjusted their intensity based on various forms of feedback. • Coaches can use this information to understand how shooting influences athletes' pacing. • This research can help develop a pacing questionnaire as a tool for coaches.

Figure 2. Shooting/zeroing responses of athletes before and after the biathlon trial. Mnd = Median. Error bars: 95% CI.

References 1.Foster, C., De Koning, J. J., Hettinga, F., Lampen, J., La Clair, K. L., Dodge, C., et al. (2003). Pattern of energy expenditure during simulated competition. Medicine & Science in Sports & Exercise, 35(5), 826–831

3.Elferink-Gemser, M. T., & Hettinga, F. J. (2017). Pacing and self-regulation: Important skills for talent development in endurance sports. International Journal of Sports Physiology and Performance, 12(6), 831–835. https://doi.org/10.1123/ijspp.2017-0080

2.Smits, B. L., Pepping, G. J., & Hettinga, F. J. (2014). Pacing and decision making in sport and exercise: The roles of perception and action in the regulation of exercise intensity. Sports Medicine, 44(6), 763–775. https://doi.org/10.1007/s40279-014-0163-0

4.Luchsinger, H., Sandbakk, Ø., & Kocbach, J. (2023). Highly trained biathletes with a fast-start pacing pattern improve time-trial skiing performance by pacing more evenly. International Journal of Sports Physiology and Performance, 18(12), 1435–1441.

RGP 2023/24

ASSESSING THE IMPACT OF TRIGGER CONTROL ON SHOOTING PERFORMANCE AND THE FEASIBILITY OF RECOIL SIMULATION FOR TRAINING IN BIATHLON Alexander Kösters1, Hans-Peter Wiesinger2

1 University of Salzburg, AUT 2 Institute of General Practice, Family Medicine and Preventive Medicine, Center for Public Health and Healthcare Research, PMU Salzburg, AUT

KEY FACTS SAMPLE N = 22 elite Austrian biathletes and N = 18 novice biathletes DESIGN Mixed-methods study evaluating trigger/rifle dynamics at rest vs. during competition

METHODOLOGY Resting and race-simulated shooting, measuring biomechanical and physiological data CORE FINDINGS Trigger control showed minimal impact on performance, while elite athletes maintained far superior shooting stability under exercise load

Assessing the impact of trigger control and selective attention on shooting performance in biathlon.

2 Trigger control

Methods Elite and novice biathletes were analysed for trigger behavior, rifle motion, and shooting performance under various conditions.

1 Background Athletes and coaches believe that poorly coordinated trigger control results in uncoordinated rifle motion and poor shooting performance, but evidence for this in biathlon is lacking.

Three clips of 5 shots Simulation race: Elite: 12.5 km; Novice 6.0 km

Trigger control was not correlated with riffle motion and shooting performance in elite and novice biathletes.

There was no difference in performance between shot number 1 to 5 Frequency

Outcome There was no difference between elite biathletes and novice biathletes.

Score

2 3 4 Shot number (Novice) 0

2 3 4 Shot number (Experts)

4 Practical applications Trigger control seems overestimated for shooting performance. This holds for the first and last shot, as well as the shot 2 to 4. Athletes should spend less training time and potentially less concentration on trigger control. Reference: alexander.koesters@plus.ac.at; hans-peter.wiesinger@pmu.ac.at

RGP 2023/24

SCOPE 3 ENVIRONMENTAL IMPACT: ASSESSING FAN MODES OF TRANSPORTATION Brian McCullough1, Gidon Jakar2 1 Texas A&M University 2 University of Florida

KEY FACTS SAMPLE 201 surveyed travel parties at the IBU World Cup in Soldier Hollow DESIGN GIS-based spatial accessibility analysis combined with an online spectator travel survey METHODOLOGY Mapped local hotel/transit infrastructure via ArcGIS Pro and calculated air and road travel distances to estimate Scope 3 CO2 emissions

CORE FINDINGS Attendance generated 197,089 kg of CO2 emissions – driven largely by air travel and a high reliance on private cars

RGP 2023/24

RGP 2022/23

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AGENDA 22/23 PROJECT 1 – AECC University..............................................36-37 Psychophysiological Interventions in Biathlon

PROJECT 2 – Swiss Federal Institute of Sport.......................38-39 Resting metabolic rate and exercise energy expenditure in Swiss elite biathletes PROJECT 3 – Mid Sweden University....................................40-41 The application and utility of wearable sensors for athlete monitoring in biathlon PROJECT 4 – Northumbria University....................................42-43 High level biathletes with a fast start pacing pattern improve time trial skiing, without changes in shooting performance, by using a more even pacing strategy PROJECT 5 – Nord University Bodø.......................................44-45 The long term development of performance physiological, and training characteristics in a world-class female biathlete

RGP 2022/23

PSYCHOPHYSIOLOGICAL INTERVENTIONS IN BIATHLON Dr. Zöe L. Wimshurst1 , Dr. Emma Mosley2 , Dr. Stephanie Tibbert1 , Phill Heritage1 , Dr. Greg Neil3 1 School of Rehabilitation, Sport and Psychology, AECC University College 2 Department of Rehabilitation and Sports Science, Bournemouth University 3 Psychology Department, Solent University

KEY FACTS SAMPLE N = 9 biathletes from the British development squad (15-25 years)

DESIGN Counterbalanced crossover study with a post-testing focus group METHODOLOGY Evaluated Quiet Eye and Slow-Paced Breathing workshops via laser shooting, HRV, eye tracking, and workbooks

CORE FINDINGS Interventions significantly improved shooting performance (p = 0.02) and participant technique knowledge (p < 0.05)

RGP 2022/23

RESTING METABOLIC RATE AND EXERCISE ENERGY EXPENDITURE IN SWISS ELITE BIATHLETES Thomas Steiner1 , Elias Bucher1 , Eva Hofmann2 , Maria Gräfnings2 , Hanspeter Betschart2, John. Wehrlin1 1 Selection of Elite Sport, Swiss Federal Institute of Sport, Magglingen, Switzerland 2 Swiss-Ski, Muri b. Bern, Switzerland

KEY FACTS SAMPLE N = 13 elite Swiss biathletes (7 female, 6 male; mean age ~ 26-27) DESIGN Cross-sectional study combining resting and submaximal exercise tests METHODOLOGY Measured resting metabolic rate and exercise energy expenditure via indirect calorimetry during roller-skiing

CORE FINDINGS ~30% showed suppressed RMR indicating Low Energy Availability, while energy expenditure strongly correlated with heart rate

Resting metabolic rate and exercise energy expenditure in Swiss elite biathletes Thomas Steiner1, Elias Bucher1*, Eva Hofmann1, Maria Gräfnings2, Hanspeter Betschart2, Jon P. Wehrlin1 1Section for Elite Sport, Swiss Federal Institute of Sport, Magglingen, Switzerland 2Swiss-Ski, Muri b. Bern, Switzerland

Correspondence: thomas.steiner@baspo.admin.ch

Introduction

Results

Low Energy Availability (LEA) and Relative Energy Deficiency in Sport (REDs) are common among endurance athletes, negatively impacting long-term health and performance 1. The diagnosis of LEA and REDs are multifactorial and include the analysis of energy balance, body composition, validated questionnaires, and performance. In an attempt to establish preventative measures and appropriate care, Swiss-Ski has launched the «FUEL» project, that involves three main components: counseling and education, diagnostics, and energy balance measurements (see Figure 1)

mRMR varied from 1186 - 2062 kcal·24h-1 and RMRratio values ranged from 0.79 – 1.04, with inter-individual differences of up to 500 kcal·24h-1 observed among male and female athletes. Four out of thirteen athletes (~30%) demonstrated suppressed RMR with RMRratio < 0.9. Very large associations were found between EEErel and relative power output (R2 = 0.88). Large correlations were observed between EEErel and HR (R2 = 0.64) and RPE (R2 = 0.58). Individual regressions demonstrated nearly perfect relationships between EEErel and HR (R2 = 0.94 – 0.99). Large inter-individual differences were observed in gross efficiency (GE) across athletes ranging from 15 – 20%, with differences also observed between sub-techniques at around ~15.5% (G4), ~16.5% (G3), and 18% (G2).

Scientific Support Project Design

Data Analysis & Reporting

Planning of Intervention and Measurements

Analysis of pre- and post-test & intervention data

B 2500

Tracking Dietary Intake

RMR (kcal·24h -1)

Video-based Nutrition Education

4-day tracking of food intake over 3 different training phases

Nutritional counseling embedded in Swiss-Ski

2000

1500

mRMR females pRMR females mRMR males

1000

pRMR males

500

Nutritional Counseling

Energy Expenditure

One-on-one sessions & team workshops embedded in Swiss-Ski

Females

Males

Resting metabolic rate (RMR), Exercise Energy Expenditure (EEE), Energy expenditure during daily activity

Diagnostics

RMR (kcal·24h -1·kg-1ffm)

Energy Balance

Counseling & Education

6 7 8 Participant

Figure 3 Measured (dark) and predicted (light) resting metabolic rates (A) and normalized for fat free mass (B) in female and male biathletes. mRMR = measured metabolic rate, pRMR = predicted metabolic rate, ffm = fat free mass.

1.50

Figure 1. Overview of the FUEL project components, including counseling and education, diagnostics, and energy balance. A team of scientific experts in the domains of LEA and REDs, sports medicine, and performance accompany the project.

Objectives within IBU Research Grant Programme: 1) Assess the resting metabolic rate (RMR) and to explore potential cases of RMR suppression 2) Establish the exercise energy expenditure (EEE) profiles and associations with power output and heart rate in elite biathletes.

1.25

1.00 Females Males

0.75

0.50

1.25

1.00 G4 G3

0.50

0.25

0.25 1

C 1.4

y = 0.127 + 0.306 x, R 2 = 0.88

2 min

2.9°

0.8

G3 G2

0.6

0.4 1.0

4.0

1.0

1.5

2.0

2.5

3.0

3.5

4.0

1.2

y = 0.119+ 0.322 x, R 2 = 0.94 y = 0.153 + 0.287 x, R 2 = 0.91 y = 0.176 + 0.275 x, R 2 = 0.89 y = 0.17 + 0.269 x, R 2 = 0.92 y = 0.164 + 0.286 x, R 2 = 0.89 y = 0.182 + 0.26 x, R 2 = 0.90 y = 0.17 + 0.282 x, R 2 = 0.89 y = 0.125 + 0.312 x, R 2 = 0.85 y = 0.202 + 0.292 x, R 2 = 0.88 y = 0.116+ 0.333 x, R 2 = 0.92 y = 0.15 + 0.288 x, R 2 = 0.89 y = 0.145 + 0.308 x, R 2 = 0.83 y = 0.158 + 0.293 x, R 2 = 0.88

1.0

0.8

0.6

0.4 1.0

1.5

Relative power (Watt·kg-1)

2.0

2.5

3.0

3.5

4.0

1.0

1.5

2.0

Relative power (Watt·kg-1)

2.5

3.0

3.5

4.0

Relative power (Watt·kg-1)

C 1.4

y = − 0.189 + 0.00683 x, R 2 = 0.64

D 1.4

y = − 0.185 + 0.00635 x, R 2 = 0.77

0.8

0.6

Relative energy expenditure (kJ·min-1·kg-1)

1.0

Females

0.8

Males

0.6

0.4 120

140

160

180

200

1.4

y = − 0.115 + 0.00641 x, R 2 = 0.59

y = − 0.435 + 0.00808 x, R 2 = 0.98 y = − 0.586 + 0.00841 x, R 2 = 0.99

y = − 0.179 + 0.00666 x, R 2 = 0.66

1.2

1.0

0.8

G3 G2

0.6

0.4

100

120

140

160

180

200

y = − 0.609 + 0.00872 x, R 2 = 0.94 y = − 0.463 + 0.00909 x, R 2 = 0.99

y = − 0.246 + 0.00721 x, R 2 = 0.66

1.2

y = − 0.897 + 0.0103 x, R 2 = 0.96 y = − 0.123 + 0.00596 x, R 2 = 0.99

1.2

y = − 0.262 + 0.00725 x, R 2 = 0.99 y = − 0.24 + 0.00761 x, R 2 = 0.99 y = − 0.72 + 0.0104 x, R 2 = 0.99 y = − 0.972 + 0.0118 x, R 2 = 0.94 y = − 0.241 + 0.00861 x, R 2 = 0.99 y = − 0.506 + 0.0095 x, R 2 = 0.97 y = − 0.712 + 0.0106 x, R 2 = 0.99

1.0

0.8

0.6

0.4 100

120

140

Heart rate (bpm)

160

180

200

100

120

140

160

180

200

Heart rate (bpm)

Figure 6. Association between relative exercise energy expenditure and heart rate across all intensities and sub-techniques (A), separated by sex (B), sub-technique (C), and individual athlete (D) in female and male biathletes. C B

C 22

y = 14 + 1.13 x, R 2 = 0.22

D 22

y = 13.1 + 1.66 x, R 2 = 0.39 y = 13.9 + 1.03 x, R 2 = 0.18

y = 17.2 + 0.344 x, R 2 = 0.05 y = 15.4 + 0.486 x, R 2 = 0.16 y = 15.2 + 0.0727 x, R 2 < 0.01

Gross efficiency (%)

16 G4

Females Males

1.0

1.5

2.0

2.5

3.0

3.5

4.0

Relative power (Watt·kg )

1.5

2.0

2.5

3.0 -1

Relative power (Watt·kg )

3.5

1.0

y = 13.4 + 1.12 x, R 2 = 0.34 y = 13.4 + 1.53 x, R 2 = 0.41 y = 12.8 + 1.8 x, R 2 = 0.47 y = 13.3 + 1.78 x, R 2 = 0.53 y = 13 + 1.62 x, R 2 = 0.40 y = 13.1 + 1.95 x, R 2 = 0.52 y = 13 + 1.65 x, R 2 = 0.42 y = 14.4 + 0.895 x, R 2 = 0.12 y = 12.7 + 1.35 x, R 2 = 0.36 y = 13.9 + 0.748 x, R 2 = 0.21 y = 14.3 + 1.15 x, R 2 = 0.29 y = 13.9 + 0.982 x, R 2 = 0.15 y = 13.9 + 1.17 x, R 2 = 0.26

4.0

12 1.0

1.5

2.0

2.5

3.0 -1

Relative power (Watt·kg )

3.5

4.0

1.0

1.5

2.0

2.5

3.0

3.5

4.0

Relative power (Watt·kg-1)

Figure 7. Association between gross efficiency and relative power output across all intensities and sub-techniques (A), separated by sex (B), sub-technique (C), and individual athlete (D) in female and male biathletes.

Conclusion •

•

1.1°

0.6

Heart rate (bpm)

2.9°

6.8°

Heart rate G3

3.5

1.2

100

~I.1

Males

y = − 0.000906 + 0.391 x, R 2 = 0.98

1.2

y = − 0.2 + 0.00743 x, R 2 = 0.81

~I.4

Females

0.8

B 1.4

2.9°

3.0

~I.2

2.5

0.4

~I.3

1.1°

2.0

-1

1.0

0.4

1.5

C A

6 26.3 ± 2.8 177 ± 3.8 70.7 ± 6.3 12.8 ± 1.0 47 ± 8 1779 ± 151 69.2 ± 3.7

Exercise Energy Expenditure

Technique

0.6

1.4

y = 0.0327 + 0.319 x, R 2 = 0.95 y = 0.0491 + 0.341 x, R 2 = 0.97

1.2

Relative power (Watt·kg-1)

Males

Figure 5. Association between relative exercise energy expenditure and relative power output across all intensities and subtechniques (A), separated by sex (B), sub-technique (C), and individual athlete (D) in female and male biathletes.

Data presented as mean ± standard deviation (SD). HRrest = resting heart rate, ̇ 2max = maximal oxygen consumption. VO

0.8

1.0

Table 1. Anthropometric and physiological characteristics of participants of the senior Swiss national team biathles.

4 min

1.0

0.4

Participants

Blood lactate

1.2

Relative energy expenditure (kJ·min-1·kg-1)

Thirteen elite biathletes from the Swiss National Team (see Table 1) underwent an RMR and EEE assessment in addition to their routine National team performance testing in June 2023. Measured (mRMR) and predicted (pRMR) RMR were used to determine RMRratio as a surrogate marker of LEA. Furthermore, athletes completed a submaximal graded exercise test protocol in the skating technique to determine EEE (see Figure 2).

Relative energy expenditure (kJ·min-1·kg-1)

Methods

27.5 ± 3.9 167 ± 6.5 64.7 ± 8.1 22.5 ± 1.8 52 ± 8 1468 ± 188 56.1 ± 3.6

D 1.4

y = 0.164 + 0.282 x, R 2 = 0.88 y = 0.147 + 0.305 x, R 2 = 0.85

Age (y) Body height (cm) Body mass (kg) Body fat (%) HRrest (bpm) RMR (kcal·24h-1) ̇ 2max (ml·kg-1·min-1) VO

3 Intensity level

Figure 4. Relative exercise energy expenditure across intensity level separated by sex (A) and skating sub-technique (B).

1.4

Intensity level

Females

0.75

Relative energy expenditure (kJ·min-1·kg-1)

Integration of the bi-annual ̇ 2max) performance tests (GXT & VO

Relative energy expenditure (kJ·min-1·kg-1)

Performance

LEAF-Q/LEAM-Q, EDE. and REDS

Gross efficiency (%)

Questionnaires

Body composition & bone mineral density (BMD)

Relative energy expenditure (kJ·min-1·kg-1)

DEXA

T3, T4, Cortisol, Estrogen, Testosteron

Relative energy expenditure (kJ·min-1·kg-1)

BLOOD SAMPLES

6.8°

•

6.8°

2.5 min

Figure 2. Roller ski skating test protocol to determine exercise energy expenditure across different intensities. G4, G3 and G2 refer to the incline-appropriate sub-techniques (gears). Order of sub-technique and corresponding treadmill velocity and incline were randomly assigned.

Significant inter-individual variability in RMR of up to 500 kcal·24h-1 underline the necessity for individual day-to-day fueling and support staff awareness of athletes' energy needs Individually calculated HR profiles may effectively estimate EEE during continual submaximal skiing exercise, allowing athletes and coaches to determine the energy requirements of steady-state endurance training sessions and hence optimize nutritional behavior Individual GE profiles across different exercise intensities, could further provide objective information for optimization of technique training

References 1 Mountjoy M, Sundgot-Borgen JK, Burke LM, et al. IOC consensus statement on relative energy deficiency in sport (RED-S): 2018 update. Br J Sports Med. Jun 2018;52(11):687-697.

RGP 2022/23

THE APPLICATION AND UTILITY OF WEARABLE SENSORS FOR ATHLETE MONITORING IN BIATHLON Craig Staunton, Glenn Björklund, Dr Mikael Swaren, Andreas Kårström, Marko Laaksonen Mid Sweden University, Östersund, Sweden

KEY FACTS SAMPLE N = 10 elite youth biathletes

DESIGN 5-week observational study on training compliance METHODOLOGY Tracked HR, GNSS speed, and PlayerLoad during training compared them to coaches‘ planned sessions

CORE FINDINGS High duration compliance (92–94%), significant low-speed movement, and strong PlayerLoad validity (p < 0.001)

RGP 2022/23

HIGH LEVEL BIATHLETES WITH A FAST START PACING PATTERN IMPROVE TIME TRIAL SKIING, WITHOUT CHANGES IN SHOOTING PERFORMANCE, BY USING A MORE EVEN PACING STRATEGY Thomas Losnegard1 , Magne Lund-Hansen1 , Erland Vedeler Stubbe1 , Harri Luchsinger2 , Even Dahlen Granrud1 , Øyvind Sandbakk2 , Jan Kocbach2 1 Northumbria University, UK 2 Norwegian School of Sports Sciences, Norway

KEY FACTS SAMPLE N = 38 high-level biathletes (~21 years)

DESIGN 2-day simulated sprint race study (fast-start vs. conservative control) METHODOLOGY Tracked GNSS/IMU speed, RPE, and shooting scores during roller-skiing time trials

CORE FINDINGS Slower starts improved skiing speed (p = 0.04) and lowered RPE without affecting shooting accuracy

RGP 2022/23

THE LONG TERM DEVELOPMENT OF PERFORMANCE, PHYSIOLOGICAL, AND TRAINING CHARACTERISTICS IN A WORLD-CLASS FEMALE BIATHLETE Guro Strøm Solli1 , Andrine Håstul Flom1 , Rune Kjøsen Talsnes1,2 1 Department of Sports Science and Physical Education, Nord University, Bodø, Norway 2 Centre of Elite Sports Research, Norwegian University of Science and Technology, Trondheim, Norway

KEY FACTS SAMPLE One world-class female athlete (22 international medals)

DESIGN Longitudinal case study analyzing performance, physiological tests, and training logs from age 17 to 33 METHODOLOGY Quantified annual physical training (LIT/MIT/HIT, mode) and shooting metrics across junior vs. senior seasons CORE FINDINGS Senior seasons featured 48% higher physical volume (more LIT/MIT, less HIT), 175% more shots fired, and a 10% increase in VO2max

The long-term development of performance, physiological, and training characteristics in a world-class female biathlete Guro Strøm Solli1*, Andrine Håstul Flom1, and Rune Kjøsen Talsnes1,2 1 Department of Sports Science and Physical Education, Nord University, Bodø, Norway 2 Centre for Elite Sports Research, Norwegian University of Science and Technology, Trondheim, Norway

Purpose: This project investigated the long-term development of performance, physiological, and training characteristics in a world-class female biathlete, with emphasis on differences between junior and senior athlete seasons.

Methods: Training data was recorded in training diaries designed by the Norwegian Ski Association and the Norwegian Olympic Federation and analysed in detail. Interviews with the participant were conducted to gather additional information.

Results:

Conclusions: This study provides unique insights into the long-term development of physical and shooting training from junior to senior in a world-class female biathlete. The major differences in training characteristics between junior and senior athlete seasons were higher sport-specific volumes of LIT and MIT, and less HIT. These differences were accompanied by more shooting training, particular at rest, and in connection with LIT.

RESEARCH GRANT PROGRAMME

2021/22

RGP 2021/22

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AGENDA 21/22 PROJECT 1 - Academy of Physical Education Katowice.............48-49 The influence of balance training and mindfulness training on shooting performance in young biathletes PROJECT 2 - Finnish Institute of High Performance Sport.........50-51 Validity of an automated GNSS-IMU system in temporal biathlon range work analysis PROJECT 3 - Montana State University.....................................52-53 Role of core stability and dynamic balance in standing shooting performance PROJECT 4 - University of Jyväskylä........................................54-55 Prevalence, consequences, and prevention of relative energy deficiency in sport in finnish elite male athletes (NoREDS-Study)

RGP 2021/22

THE INFLUENCE OF BALANCE TRAINING AND MINDFULNESS TRAINING ON SHOOTING PERFORMANCE IN YOUNG BIATHLETES Stomka, K., Watach-Biśtsa, Z.

KEY FACTS SAMPLE N = 26 youth biathletes

DESIGN Controlled experiment (balance vs. mindfulness vs. control) METHODOLOGY Tested functional balance, shooting metrics (rest and fatigue) and psychological questionnaires CORE FINDINGS Both body balance and mindfulness significantly contributed to shooting accuracy

RGP 2021/22

VALIDITY OF AN AUTOMATED GNSS-IMU SYSTEM IN TEMPORAL BIATHLON RANGE WORK ANALYSIS Köykkä, M.1,2 , Ruotsalainen, K.2, Vierola, S.1, Vänttinen, T.1, Heikkinen, T.2, Ohtonen, O.2, Linnamo, V.2

1 Finnish Institute of High Performance Sport, Jyväskylä, Finland 2 Neuromuscular Research Centre, Faculty of Sport and Health Sciences, University of Jyväskylä, Finland

KEY FACTS SAMPLE N = 12 biathletes DESIGN Validation study comparing wearable GNSS-IMU data to video footage

METHODOLOGY Recorded shooting range metrics across 12 laps and 6 shooting sets per athlete using sensors and synchronized video CORE FINDINGS The wearable system accurately measured all range timing metrics compared to video

Validity of an automated GNSS-IMU system in temporal biathlon range work analysis Köykkä, M.1,2, Ruotsalainen, K.2, Vierola, S.1, Vänttinen, T.1, Heikkinen, T.2, Ohtonen, O.2, Linnamo, V.2 Finnish Institute of High Performance Sport KIHU, Jyväskylä, Finland Neuromuscular Research Centre, Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland 1

STRONG RELATIONSHIPS BETWEEN METHODS WERE OBSERVED

INTRODUCTION The purpose of this study was to examine the validity of a commercial wearable wireless GNSSIMU system (Archinisis) in automated temporal biathlon range work analysis

METHODS ▪ 12 biathletes skied 12 laps around the shooting range and performed six times a 5-shot set of biathlon shooting from the prone and standing postures ▪ Temporal range work characteristics were simultaneously measured with ▪ a wearable GNSS-IMU sensor ▪ Naos sensor for biathlon by Archinisis ▪ a high-speed video camera Variable

Description

Approaching

Range entry to mat entry

Preparing

Mat entry to the 1st shot

Shot interval

Time between consecutive shots

Total shooting

Time between the 1st and last shot

Mat off

From the last shot to mat exit

Leaving

From mat exit to range exit

Range time

From range entry to range exit

Mat time

From mat entry to mat exit

PRONE rs = 0.92, p < 0.001

rs = 1.00, p < 0.001

rs = 0.98, p < 0.001

rs = 0.88, p < 0.001

rs = 1.00, p < 0.001

rs = 0.87, p < 0.001

rs = 1.00, p < 0.001

STANDING rs = 1.00, p < 0.001

rs = 1.00, p < 0.001

rs = 0.98, p < 0.001

rs = 0.87, p < 0.001

rs = 1.00, p < 0.001

rs = two-tailed Spearman’s rank correlation

RESULTS

CONCLUSION

Prone

Standing

MAE (s)

CV%RMS

MAE (s)

CV%RMS

Approaching

0.47 ± 0.31

4.1

0.27 ± 0.26

2.9

Preparing

0.19 ± 0.17

0.9

0.29 ± 0.19

1.4

Shot interval

0.006 ± 0.004

0.1

0.009 ± 0.010

0.3

Total shooting

0.02 ± 0.01

0.1

0.03 ± 0.04

0.2

Mat off

0.14 ± 0.13

2.5

0.15 ± 0.11

2.9

Leaving

0.46 ± 0.31

3.7

0.29 ± 0.18

2.4

Range time

0.17 ± 0.12

0.2

0.15 ± 0.11

0.2

Mat time

0.24 ± 0.20

0.5

0.28 ± 0.20

0.7

MAE = mean absolute error CV%RMS = root-mean-squared coefficient of variation percentage

Temporal biathlon range work characteristics can be measured with reasonable accuracy with the Archinisis GNSS-IMU system. The Archinisis system can be used to collect data on biathletes’ range work performance for coaching and research purposes.

RGP 2021/22

ROLE OF CORE STABILITY AND DYNAMIC BALANCE IN STANDING SHOOTING PERFORMANCE Becker, J.1, Jessen, D.2, Sorenson, A.2, Hubbard, S.2

KEY FACTS SAMPLE N = 22 biathletes across varying age and experience level DESIGN Observational study on physical prerequisites for standing shooting METHODOLOGY Tested core stability (YTB) and IMU postural/rifle stability during dryfire shooting

CORE FINDINGS Identified core stability as a key factor for standing shooting performance

RGP 2021/22

PREVALENCE, CONSEQUENCES, AND PREVENTION OF RELATIVE ENERGY DEFICIENCY IN SPORT IN FINNISH ELITE MALE ATHLETES (noREDS-STUDY) Ihalainen, J.1, Valtonen, M.2, Mjøsund, K.1,3 1 Faculty of Sport and Health Sciences, University of Jyväskylä, Finland 2 Finnish Institute of high-performance Sport KIHU, Jyväskylä, Finland 3 Urhea National Olympic Training Centre, Helsinki, Finland

KEY FACTS SAMPLE N = 50 highly trained Finnish male athletes (41 endurance)

DESIGN Cross-sectional screening study for LEA and RED-S symptoms METHODOLOGY Evaluated body composition (DXA), blood hormones, RMR, Vo2max, LEAM-Q-questionnaire and 4-day logs

CORE FINDINGS Emphasized routine RED-S screening and monitoring carbohydrate intake alongside lab testing