International Society of Performance Analysis of Sport (UK)ISPAS: http://ispas.org/

8TH INTERNATIONAL WORKSHOP AND CONFERENCE OF THE INTERNATIONAL SOCIETY OF PERFORMANCE ANALYSIS OF SPORT

11th-13th of September 2019 (Budapest, Hungary)„Technology meets Practice and Science”

Programme Abstracts:-

in the order theyappear in

the PROGRAMME

11th of September (Wednesday)

11.45Delivery of performance analysis in elite, underage rugby union: how to optimise player development?

Vinny Hammond1,2, Aleisha Barton1, Matthew Coyne1, Joy Earls1, Anna Walsh1, Chiamaka

Okigbo1, Denise McGrath1

1School of Public Health, Physiotherapy and Sports Science, University College Dublin, Ireland2Irish Rugby Football Union, Ireland

AbstractWhile coaches and performance analysts understand the importance of player engagement in learning, the delivery of performance analysis (PA) feedback can often be ad hoc, coach- driven and results focused (Middlemas et. Al., 2017). This study sought to understand how PA feedback is delivered to an U20 international squad to optimise player development. Eight players from the 2019 Irish International U20 Rugby Union squad provided informed consent to participate in semi-structured interviews where questions were posed about their personal experience with PA and how it impacts their development and performance. The transcribed data were analysed using thematic analysis. Performance data is consumed optimally by players when: 1) the messaging is accurate, clear and simple; 2) when it is constructively delivered; 3) when they can map personal performance data to other higher-level performances; 4) when they are provided with augmented feedback that they could not otherwise access; 5) when availability of resources is not time restricted. Learning occurs best in a player-driven, one-on-one coach/player dynamic; through players’ discussion of data within positional groups and through interactive player/coach delivery in team review sessions. These findings can be interpreted in line with a recent study in Rugby League (Rothwell et al., 2019) that discusses player development through the lens of the complexity sciences model. In this framework, players develop within the micro-structure of practice (i.e. the daily, weekly activities in training environments) by harnessing the spontaneous self-organising tendencies of a learner in an adaptive setting. These environments should expose athletes to learning landscapes rich in pertinent, multi-modal information so that they can self-solve technical, tactical and physical “problems” within the dynamically evolving ecological constraints of training and competition.

References

Middlemas, S. G., Croft, H. G., & Watson, F. (2017). International Journal of Sports Science & Coaching, 13(2), 201–212.

Rothwell, M., Stone, J., & Davids, K. (2019). Journal of Motor Learning and Development, 1–19.

12th of September (Thursday)

11.55Predicting cycling power using linear regression.

Femke Ongenae1, Gilles Vandewiele1, Lorenz van Herwaarden1 and Filip De Turck1

1IDLab, Ghent University – imec

AbstractRecreational athletes turn towards coaches and mobile applications (e.g. strava) to exercise healthy and follow up their progress in a systematic way. To optimize training, an accurate and objective view on the athlete’s performance is required. Therefore, sensors are increasingly used during training. An important metric to gain insight into the performance of cyclists is power. As power meters are too expensive for recreational athletes, a power prediction model based on: (i) data of cheaper sensors, e.g. heart rate, (ii) profile and context data, offers a cheap, albeit less accurate, solution. A global Linear Regression (LR) model is trained on data from all athletes. Its coefficients are used to predict the power output during training of a new athlete. An individualized LR model is trained on a particular athlete’s historical data. The models were designed using anonymized client data from EnergyLab, a coaching company. The global model achieves a RMSE (65.4 vs. 87.1) and MAE (49.2 vs. 67.9) that are significantly lower than the Martin (1998) formula. For 9 out of the 10 evaluated athletes, the individualized model achieves significantly lower RMSE and MAE than the Martin formula and global model (one sided Wilcoxon test p = 0.005). By using exercise context, athlete profile and inexpensive sensor data, LR models are achieved that predict the power more accurately than mathematical approximations [1]. The individualized model obtains better accuracy than the global one, but suffers from the cold-start-problem, i.e., data from trainings during which the athlete used a power meter is required.

References

Martin, J.C. et al. (1998). Validation of a mathematical model for road cycling power. Journal of Applied Biomechanics, 14(3), 276-91.

12.05In it to win it: Measuring stress responses in horse and riders during eventing competition

Cameron-Whytock.H124., Sinclair,J²., Taylor,P³., Brigden.C4. and Hobbs,S.J².¹School of Animal, Rural and Environmental Sciences, Nottingham Trent University, NG25 0QF²School of Sport and Wellbeing, University of Central Lancashire, PR1 2HE³School of Psychology, University of Central Lancashire, PR1 2HE4Myerscough University Centre, Myerscough College, P33 0RY

AbstractEquestrian sport is a unique Olympic discipline as human and animal athletes work in unison to navigate various challenges in competition. Stress during competition can affect both horse and rider, with a possible impact on health, welfare and performance. The cross-country (CC) phase of eventing competition poses the highest risk of injury and fatality to horse and rider, however the stress that this phase invokes in both horse and rider is scarcely understood. Heart rate variability (HRV) was analysed in horses and their riders (n=16) resting at home, resting at competition, CC warm up and waiting at the CC start box during British Eventing competitions in 2017. A reduction of HRV parameters such as SDRR and RMSSD have often been associated to stressful situations in humans and horses. The Exercise Induced Feeling Inventory (EIFI) was used to profile the rider’s mood before and after competition. Rider HRV was significantly lower at the CC start box than resting at home (SDRR: p=0.03; RMSSD: p=0.01) or the CC warm up (SDRR: p=0.01; RMSSD: p=0.01). Horse HRV was significantly lower at the CC start box than at the CC warm up (SDRR: p=0.02). Horse HRV was significantly lower at the CC start box than rest at home (RMSSD: p=0.02) or rest at competition (RMSSD: p=0.05). There was a strong positive correlation between rider SDRR and revitalisation score before competition (R2 =0.65, p=0.03).e Results indicate that horses and riders experience the highest levels of stress at the CC start box, compared to rest at home, rest at competition or CC warm-up. Neither the valence nor the implications of this anticipatory stress are currently known. Higher rider revitalisation before competition is associated with lower stress levels at the CC start box, highlighting the importance of competition stress management in riders.

12.15

Clustering women’s world sevens rugby by temporal attack-defence performance

Koh Sasaki1, Ichiro Watanabe2, Takumi Yamamoto3, Jun Murakami4, Hironobu Shimozono4, Yu Iwai5 and Kensuke Iwabuchi5

1Res. Ctr. Health, Physical Fitness and Sport, Nagoya University, Nagoya, Japan2Tokyo City University, Tokyo, Japan3National Defence Academy, Yokosuka, Japan4Fukuoka University, Fukuoka, Japan5Japanese Rugby football Union, Tokyo, Japan

AbstractThere is little study concerned game structure of women’s sevens rugby. Because the game time is only 14 minutes (7 minutes half), the temporal performance would be a decisive factor. It might suggest the characteristics of current world women’s sevens rugby and each union. This study clarified the temporal structure of “try scoring rate” (frequency of tries in own possession (secs)), and “try conceding rate” (frequency of tries in oppose possession (secs)). With adding two manipulated factors from “opposition 22m entry try success (attack)” and “own 22m entry try success (defence)”, total four factors were investigated for the world ranking clusters. Data were picked up from opened homepage of World Rugby game analysis 2016-2017 women’s sevens series. Two-dimensional space showed the relationship of “try scoring rate” and “try conceding rate” (avg. = 79 secs) with mapping the world fifteen union’s performances. It suggested world ranking structure. Non-hierarchical cluster analysis was attempted in order to explore the possibility of grouping. Interesting differences were observed among the number of iterations. The 5-iteration process setting showed top group by top 7 unions. The 1000-iteration process setting showed top group by top 3 unions. (explained 96% of point variability) Clustering the world women’s sevens rugby was tried from the temporal structure analysis of some attack-defence performances. In non-hierarchical cluster analysis, the number of clusters needs to be determined by the analyst, and there is no established method to calculate the optimal number of clusters automatically. The number of women’s sevens games is also limited. Development of the optimal algorithm under this condition would be desired.

13.30 Invasion team and net games:

13.30 – 14.00 Performance Analysis in invasion-games and net games – Workshop SessionsInvited speakers: G. Csataljay (Sopron, Basketball, Hungary, T. Sterbenz- Vice-rector of University of PE, Hungary), C. White (British Tennis, UK)

Chair: N. James

14.00Optimization techniques for basketball players under the convex risk measures

Lazaros Ntasis,Department of Economics, School of Economics and Management, University of Peloponnese, Tripoli, Greece.

AbstractThe aim of the Athletes-Return-Correction (ARC) program is to optimize performance of the basketball players. The ARC program is a research-based on optimization problem techniques under the convex risk measures introduced by Artzner et al. (1999) approach that attempts to improve the optimal coaches’ decision in real time. The core problems are how coaches select the optimal player during the game. We investigate model to calculate the return of players over the following linear equation:

r ( x )=w1assist +w2twopoint+w3 threepoint+w4 freethrows+w5 points+¿w6 minutesongame …………..(1.1)

Where w1 is the sum of correct and wrong passes, two point shoot is the percentage of correct shoots, w3 is the sum of three points shoots, w4 is the percentage of free throws, w5 is the sum of points and w6 is the minutes on the game. Furthermore, we optimize the following quadratic problem:

minx , q

ρπc (r (x)) (1.2)

E [r (x )]≥u (1.3)

∑i=⊥

N

x i+ xN +1+∑i=1

N

qi=W (1.4)

q i=bi (x i−x i0 )+ ¿+ si( xi

0− xi )+¿ , i=1 , ....,N ¿ ¿ (1.5)

x i≥ 0 , ⅈ=1 ,.... , N+1 (1.6)

Were r(x) is the return calculated in equation (1.1) and ρπc is the convex risk measures. Furthermore equation (1.3) take into consideration only returns with is better than the player who play currently. All the equations are linear except (1.5) where we use Canakgoz and Beasley theorem for transformation. The ARC program is an action-based framework and a practical program to identify optimal athletes’ submission and to correct random performance errors in top-level athletes. From the applied perspective, the ARC program was used to improve the quality of coaching process and to enhance systematic work on sport technique. Our findings suggest that: under the convex risk measures coaches can optimize players returns during the game. The support performance analyst team can run the following program to find the best player selection into different circumstances. Concluding, this research idea the following optimisation problem run to R programming with Markovitz codes and investigate that the previews theorem have a perfect fit and over the basketball game.

14.10Design and validation of an observational system in Beach Volleyball

Duarte Sousa1, Rodrigo Casanova1, João Prudente1,2

1Department of Physical Education and Sport, Faculty of Social Sciences, University of Madeira, Portugal2C.I.D.E.S.D., Portugal

AbstractThe analysis of Team Games has been the object of a growing interest on the part of researchers and coaches, and there has been a great deal of research carried out in this field and Beach Volleyball (BVB) is not an exception.The need to evaluate, get more knowledge about the game and to verify if the introduction of new rules brings the desired changes in the durations and actions used, became necessary to create an adequate observational system to observe Beach Volleyball. We used Observational Methodology. To validate the ad hoc observational system, the validation of the construct was done by expertise through the application of an survey to 9 Volleyball experts, using a cohort value of 65%. For data analysis it was used descriptive statistics and prospective and retrospective sequential analysis technique. After the validation of the construct, an experimental study was carried out with a sample of 4 matches of the BVB 2015 Men´s World Championship in the Netherlands Intra- and inter-observer reliability was tested by Kappa Coefficient (results 0.87). The G test was used, in order to test the generalizability. The value of 99.84% showed that the variance was associated to the facet categories, and G index (relative and absolute) obtained of 0.99, proved a high level of reliability and precision. The results obtained in the experimental study on reliability and generalization allow us to affirm that the built instrument was adequate to evaluate the impact that the introduction of the new rules in the BVB bring to this sport.

14.20Differential vs conventional resistance training effects in youth basketball players

Sogand Poureghali1, Jorge Arede2, Pedro Esteves13, Wolfgang I. Schöllhorn4, Nuno Leite1

1 Otto-von-Guericke-Universität Magdeburg, Magdeburg, Germany2 Research Centre in Sports Sciences, Health Sciences and Human Development, CIDESD, Vila Real, Portugal3 Polytechnic Institute of Guarda, UDI: Research Unit for Inland Development, Guarda, Portugal4 Institute of Sport Science, Training and Movement Science, University of Mainz, Mainz, Germany

AbstractThe differential learning approach, which takes advantage of fluctuations that occur, without movement repetitions and without corrections has been growing in skill acquisition field (Schöllhorn, 2012). However, in strength training this approach has been mostly neglected (Hegen Polywka, Schöllhorn, 2015), and more research is needed to better understand training effects, particularly in youth athletes. The aim of this study was to examine the effect of conventional and differential learning resistance training on the motor performance. Twelve U12 regional level basketball players were grouped in differential (n=6) and conventional (n=6), according their resistance training program. All subjects accomplished a 7-week resistance training program, which included own-body weight Squat, Lunge, and Lateral Squat (twice/week, 3 sets x 10 repetitions + 2’ passive recovery between sets). Differential group performed different fluctuations in a random and unexpected order in each repetition. Prior and after training period, sprinting (0-10 split time), jumping (countermovement jump [CMJ], and agility (Pro Agility T-test, T-test and L-Drill test) were assessed. Specifically designed spreadsheets were used to analyze within- and between-group changes using magnitude-based inferences. Within-group analysis showed small improvements in T-test for differential and conventional groups (ES = -0.37 > -0.11). The differential group also showed small improvements in CMJ (ES = 0.25 > -0.14), and Pro Agility test (ES = -0.07 > 0.53). Increasing fluctuations during resistance training program seems beneficial for change-of-direction speed and maneuverability (i.e. T-test) over conventional training approach. These results stimulate for further research towards more movement variations in strength training, especially in youth athletes.

References

Hegen, P., Polywka, G. Schöllhorn, W. I. (2015). The Differential Learning Approach in Strength Training (Squat). In Book of Abstract of 20th annual Congress of the European College of Sport Science, 24th - 27th June 2015, Malmö (p. 590). Malmö: University of Malmö.

Schöllhorn, W. (2012). The Nonlinear Nature of Learning-A Differential LearningApproach.The Open Sports …, 100–112. Retrieved from http://benthamsciencepublisher.com/open/tossj/articles/V005/SI0007TOSSJ/100TOSSJ.pdf

14.30Contribution to methodology of efficiency evaluation of handball goalkeepers.

Josip Cvenić,Faculty of education, J.J. Strossmayer University of Osijek, Osijek, Croatia.

AbstractGoalkeepers have a very important role in handball, especially in maintaining team morale. In coaching communities, it is well recognized that goalkeepers’ performances can predict team ranking in major tournaments. There are different systems for assessing players, goalkeepers and teams in handball. Therefore, the purpose of this study was to analyse goalkeepers’ save performance during the 47 matches of the 2018 men’s European Handball Championship tournament. The top 20 goalkeepers from 12 national teams were analysed using a standard method of save percentage and compared with new method. The goal of this research was to compared two methods for assessment goalkeeper’s efficiency, standard method with save percentage for each goalkeeper and the new method based on saves classified according to the distance and specific position and different significance (6m,7m,9m, wing shots, fast breaks, breakthroughs). In 47 games 16 teams from 4322 attempts scored 2562 goals, with a mean save percentage of 31% (1146 saves). Intergroup differences between goalkeeper’s rankings in two assessment methods were determined with Mann–Whitney U analysis.The aim of present study was to analyse save performance of the goalkeepers during the 2018 European Championships comparing one existing and one new methods. The results of this study confirm differences in this two methods.

14.40How playing basketball with distinct body height and biological maturation affects physical performance and tactical behavior?

Jorge Arede1, Sogand Poureghali2, Pedro Esteves 13, Wolfgang I. Schöllhorn4, Nuno Leite1

1 Research Centre in Sports Sciences, Health Sciences and Human Development, CIDESD, Vila Real, Portugal2 Otto-von-Guericke-Universität Magdeburg, Magdeburg, Germany3 Polytechnic Institute of Guarda, UDI: Research Unit for Inland Development, Guarda, Portugal4 Institute of Sport Science, Training and Movement Science, University of Mainz, Mainz, Germany

AbstractJuvenile basketball athletes show individual variation in maturation that results in interindividual differences at anthropometrical, physical, and technical level (Arede, Ferreira, Gonzalo-Skok, & Leite, 2019). This study aims to compare physical and tactical performance of young basketball players with distinct anthropometrical and maturation distribution. Ten young U-16 male basketball players played 5x5 half court situations (2 sets of 8 minutes, with 5 minutes of rest between sets). The players were allocated to two teams according to maturity offset (MO) and body height (Z-score across the squad). MO was estimated using a non-invasive method (Mirwald, Baxter-Jones, Bailey, & Beunen, 2002). Two distinct games were prescribed: i) more mature and taller vs less mature and smaller (Game 1); and ii) more mature and smaller vs less mature and taller (Game 2). Physical workload data was collected via WIMU PRO Local Positioning System, and included variables previously analysed in basketball scrimmage (Vazquez-Guerrero, Reche, Cos, Casamichana, & Sampaio, 2018). Also, maximum and average heart rate (HR) were recorded with individual HR monitors. Spatial exploration index was also calculated (Gonçalves et al., 2017). We found higher external and internal demands in Game 2. Less mature and smaller players explored more available space in Game 1 (ES = 0.79), and very largely more than their counterparts (ES = -1.34). Games 2 induces higher between-groups differences. More mature and taller athletes covered less distance in stationary per walking (ES = -1.27), in running (ES = -3.23), high-intensity decelerations (> -2 m s∙ -2; ES = -0.82), peak acceleration (ES = -1.09), and body impacts (> 5 g; ES = -0.81). Height and maturity levels provided evidence for high impact on physical and tactical dimensions of young players during basketball scrimmage. With this regard, manipulating anthropometrical and maturation during training may stand as a valuable strategy to promote specific training adaptations in youth basketball players.

Funding: Foundation for Science and Technology (Portugal), through a Doctoral grant endorsed to the first author [SFRH/BD/122259/2016] and under project UID/DTP/04045/2019.

References

Arede, J., Ferreira, A. P., Gonzalo-Skok, O., & Leite, N. (2019). Maturational development as key aspect in physiological performance and national team selection in elite male basketball players. International Journal of Sports Physiology and Performance, 14, 1–9.

Gonçalves, B., Esteves, P., Folgado, H., Ric, A., Torrents, C., & Sampaio, J. (2017). Effects of pitch area-restrictions during soccer large-sided game. Journal of Strength and Conditioning Research, 31(9), 2398–2408.

Mirwald, R. L., Baxter-Jones, A. D. G., Bailey, D. A., & Beunen, G. P. (2002). An assessment of maturity from anthropometric measurements. Medicine and Science in Sports and Exercise, 34(4), 689–694.

Vazquez-Guerrero, J., Reche, X., Cos, F., Casamichana, D., & Sampaio, J. (2018). Changes in External Load When Modifying Rules of 5-on-5 Scrimmage Situations in Elite Basketball. Journal of Strength & Conditioning Research, 00(00), 1–8.

15.20 – 16.30 Performance Analysis in Elite Soccer - Workshop SessionsInvited speakers: A.Fuller (Hudl),P. Aleixander (F.C Valencia), R. Long (FA, UK)

Chair: M. T. Hughes

16.00The process performance analysts follow when using video feedback in professional Semi EliteEnglish Soccer.

Mulvenna . C.1 Thomson. E. 1 Twist. C. 1 Bloyce. D. 1

1Department of Sport and Exercise Science, University of Chester, Chester, UK.

AbstractPerformance Analysis (PA) is an integral feature of coaching in soccer though the processes underpinning such practice are often described as simple, linear procedures. This perspective however, fails to recognise the dynamic nature of PA provision and given the increased investment and reliance on for a multitude of reasons, scrutiny of the current processes and duties commensurate with the role would seem timely. Accordingly, this study sought to scrutinise the process of PA and how analysts attempt to create a comprehensive, structured process to PA. Eight full-time performance analysts (age: 23 – 29 yrs; experience: 2 – 8.5 yrs) in the English Football League and English National League participated in semi-structured interviews. Two core components of PA were identified: opposition analysis and performance review with less attention given to player recruitment, season long statistical tracking and the development PA tools. Where the process was concerned, analysis revealed there was no consistent approach adopted, instead a highly personalised process was developed between the interdisciplinary teams. A persistent finding however was that performance analysts are reliant on the development of a close personal bond with the manager to ensure PA holds a fully immersed place within the coaching process. Beyond a simple framework regarding the process of PA for opposition analysis and performance review, a coordinated approach to PA is lacking. The two key sections of PA align with previous literature (Groom, 2012) though this study recognises the highly individualised approaches from one club to another, which are context specific and reliant on strong relationships. Despite this, the results confirmed the widespread application of PA in elite sports (Drust, 2010; Groom, Cushion & Nelson, 2011) and therefore future descriptions of PA ought to convey this feature of PA to better prepare analysts for the demands of the role.

References

Drust (2010). Performance analysis research: Meeting the challenge. Journal of Sports Sciences, 28 (9), 921-922.

Groom, R., Cushion, C. J. & Nelson, L. J. (2011) The delivery of video-based performance analysis by England youth soccer coaches: towards a grounded theory, Journal of Applied Sport Psychology, 23, 16, 32.

Groom (2012) Towards an understanding of the use of video-based performance analysis in the coaching process. PhD Thesis. Loughborough University.

16.10The influence of situational variables on attacking process in football

Jongwon Kim1, Nic James1, Nimai Parmar1, Besim Ali2 & Goran Vučković3

1London Sport Institute, Faculty of Science & Technology, Middlesex University, London, UK2Fulham Football Club, Motspur park, Surrey, UK3Faculty of Sport, University of Ljubljana, Ljubljana, Slovenia

AbstractThe tactical analysis in football was traditionally based on average statistics of which approaches ignored most situational variables (Rein & Memmert, 2016). Whilst some studies have identified the influence of situational variables to technical parameters, they have not analysed attacking process. This paper presented a framework of meaningful metrics to objectively describe the attacking process and identify the influence of situational variables. The attacking process was categorised into three phase- stable, advantage, and unstable situations. The four independent variables (match location, opposition quality, match status and key player) was analysed from Crystal Palace Football Club matches (n=38) played by in the 2017/2018. Crystal Palace FC created a median of 53.5 advantage situations (IQR=16.8), 23 unstable situations (IQR=8.8) per match. They frequently utilised wide areas (Median=21.5, IQR=9.8) to progress attack, however only 26.6% resulted in unstable situations (Median=6.0, IQR=3.8), which was the lowest rate compared to the other advantage situations. Multiple linear regression analysis showed attacking process was influenced when they were losing and their key player did not play. A novel methodology for attacking process was presented with valid approach. These finding will help coaches and players to understand their and opposition’s attacking patterns, which will enable them to plan appropriate training sessions and create a game model for the pre-match analysis.

References

Rein, R., & Memmert, D. (2016). Big data and tactical analysis in elite soccer: future challenges and opportunities for sports science. Springerplus, 5:1410. DOI 10.1186/s40064-016-3108-2.

16.20Spatial-temporal metrics to assess collective behaviour in football: a systematic review. Martin Corsie, Neil Buchanan, Thomas Craig and Paul Swinton,School of Health Sciences, Robert Gordon University, Garthdee Road, Aberdeen, UK.

AbstractWithin performance analysis of soccer there is growing interest in the measurement of players’ collective behaviour using novel metrics. The present study comprised a systematic review of research investigating spatial-temporal metrics in soccer. Five electronic databases were searched for studies published between 2008 and 2019. Included studies were required to investigate metrics that tracked at least two positional references across time to infer players’ collective behaviour in either training sessions or matches. The search identified 1100 studies, 77 were retrieved in full text and 69 were included in the review. Author quotes regarding metric: 1) description; 2) validity/reliability; and 3) practical applications, were extracted and analysed. Additionally, an adapted 12 item critical appraisal tool was used to assess study quality. A total of 123 individual metrics were reported across the 69 studies. A thematic analysis of metric descriptions identified 6 primary categories: 1) dispersion [n=101]; 2) centroid [n=62]; 3) synchrony; [n=39]; 4) dyad [n=34]; 5) entropy [n=27]; and 6) technical-tactical [n=5]. Thirty five studies were conducted with adult participants and the remaining 34 studies with youth teams. The majority of studies investigated spatial-temporal metrics during training [n=46], and all studies achieved at least a moderate classification for research quality. Descriptions and formulas of metrics were generally consistent across studies. However, in the majority of cases metric descriptions did not clearly integrate with principles of play in soccer or common coaching philosophies. Metric validity was identified on only 17 occasions, and less than half the studies [n=31] clearly discussed practical applications or made recommendations for performance analysts. Collectively, the review identifies that a range of innovative metrics can be used to quantify players’ collective behaviour in soccer, however, future research should link metrics to underpinning principles of play and make clear recommendations to increase transfer to practice.

17.30- 17.50 Coffee Break

17.50 Improving elite sports performance in a data driven worldMichael T. Hughes (Insight, UK)

18.20 Performance Profiling in Sport: Bridging the theory-practice gapN. James (Chair of ISPAS - University of Middlesex, UK)

18.50 Sport Analytics as a tool for effective decision-makingT. Sterbenz (Vice -rector of University of Physical Education, Hungary)

19.20 Future of Performance Analysis in Sport” and „Role of the Performance Analyst in the coaching Team” – Chat Panel Discussion Moderator: M. T. Hughes C. White (Lawn Tennis Association, UK), D. Lock, A. Ackerman (Insight, UK)

20.30- 22.00 Dinner for invited speakers and sponsors, exhibitors

Chair: N. Parmar

9.00Cycling performance in comparison with cycling test in the laboratory and uphill cycling test.

Rauter Samo1and Milić Radoje2,1Faculty of sport, University of Ljubljana, Ljubljana, Slovenia.

AbstractMonitoring several aspects of training load and physiological characteristics of the cyclists can be a very important factor for success in the cycling world (Faria et al., 2005). Power output measures recorded within laboratories and field settings allow a cyclist’s physical work capacities to be quantified. Taken together, the integration of these measures provides blended data that relate to performance, training adaptation and talent identification potential across various cycling disciplines.(Novak & Dascombe, 2014). The aim of the study was to find correlations between cyclist’s overall yearly results, cycling uphill field test and physiological parameters obtained on the cycling test in the laboratory. The study involved 19 cyclists, (age 15,9 ± 1,3 years, BM = 67,7 ± 6,5 kg, BH = 178,1 ± 4,0 cm) who performed uphill cycling test (1,7km - 4,1%), incremental cycle exercise test (60W + 15W/min). We used their results in the Slovenian cycling cup and compared them to their result in cycling field test (VAM) and cycling test in the laboratory (VO2max, peak power, peak power per kg). Results showed that there were significant correlations between cyclists overall yearly results and physiological parameters obtained on the cycling tests in the laboratory (PPO/kg: r=0.598, p=0.009; VO2max: r=0.554, p=0.017) and cycling uphill test (VAM: r=0.469, p=0.05). The correlation of the results between cyclist’s uphill test and cycling test in laboratory were also significant (PPO: r=0.712, p=0.001). The present study showed that there are many physiological parameters obtained in cycling laboratory and field tests correlating to cycling performance. This kind of approach can be useful tool in predicting cycling performance.

References

Faria, E. W., Parker, D. L., & Faria, I. E. (2005). The science of cycling: physiology and training - part 1. Sports Medicine (Auckland, N.Z.), 35(4), 285–312.

Novak, A. R., & Dascombe, B. J. (2014). Physiological and performance characteristics of road , mountain bike and BMX cyclists. 3(3), 9–16.

13th of September (Friday)

Chair: N. Parmar

9.10Video based notational analysis of the game structure in collegiate men’s lacrosse

Richard Hauer & Harald Tschan,1Department of Training Science, Centre for Sport Science and University Sports, University of Vienna, Vienna, Austria.

AbstractAlthough rising numbers in recent lacrosse specific research exists, there is still little scientific understanding of the structure and relevant performance indicators in the sport of lacrosse. Therefore, the aim of this study is (a) to give information about the game structure, and (b) define performance indicators in lacrosse competition. Data of ten NCAA-Division I-Men’s-Lacrosse games were collected and verified (1) using a self-created observation system with the NacSport software. Data analysis contained information about possessions, face-offs, passes, shots, goals, saves, and groundballs. Further, goal, pass, save and man-up efficiency was calculated. Additionally, differences between winning- and losing-teams were assessed to define relevant performance indicators. Results showed an average number of 113.50 ±7.47 possessions with a duration of 30.72 ±1.93 s. The total amount of detected passes was 672.40 ±71.80 of which 95% were complete. Further, 30% of the 82.30 ±9.02 shots where goals, 38% saved, and 32% missed. Overall 27.40 ±3.34 face-offs and 48.40 ±10.98 groundballs occurred. The comparison between winner and loser over the total course of play showed no differences, but medium ES in scored goals and goal efficiency (d= 0.75 ±0.87; d= 0.71 ±0.87). Further analysis with regard to quarters showed higher numbers for goals scored (p= 0.04; d= 0.89 ±0.86) and goal efficiency in the third (p= 0.01; d= 1.28 ±0.87), and possession duration in the fourth quarter (p= 0.05; d= 0.92 ±0.92) for winner. Overall, this study has shown that video based notational analysis seem to be a sufficient tool to create a better understanding of the game of lacrosse. Results indicate that winning teams score more goals through a higher shot efficiency in the third, followed by longer possession durations in the fourth quarter of play.

Keynote presentations;-

9.20 Key Performance Indicator in Elite Tennis.C. White (Law Tennis Association, UK)

10.00 Re: Thinking Analysis.R. Long (English FA, UK)

10.30 ISPAS – Accreditation.M. T. Hughes (Insight- ISPAS, UK)

11.00 Opposition intelligence strategies to support the success of the England teams- – Keynote presentationA. Fuller FA, UK (Hudl, UK)

11.30- 11.50 Coffee Break

11.50 Cooperation of Performance Analysts and Data Analysts and Tech companies” – Chat Panel DiscussionM. T. Hughes, A Fuller, N. James, I. Donelly (Insight, Hudl, ISPAS)

11.20 Using IT (video) technology at match analyses - – Keynote presentationP. Aleixandre (FC Valencia, Spain)

12.50 Company Keynote Presentation:

CATAPULTSPORTS

13.20 – 14.00 Coffee/ Snack Lunch

14.00 Company Keynote Presentation:

HUDL

14.30 ‘Atomic’ Handball: Facts & MythsI. Gruic (Faculty of Kineziology, Zagreb, Croatia)

14.40 Dinamo Football Academy - " Preparedness is the key to success and victory"- T. Despot (Dinamo Football Academy, Zagreb, Croatia)

14.50 Performance analysis and Sport Diagnostics in Football: The case study Luka Modric

V. Vučetić (Strenght coach of Luka Modric, Croatia)

15.10 Performance analysis of the first team of Dinamo ZagrebM. Minđek (Performance Analyst Dinamo Zagreb, Croatia)

15.30 Future of PA and Performance Diagnostic in FootballG. Sporis (Faculty of Kineziology, Zagreb, Croatia)

16.00- 16.20 Coffee Break

Chair: T. Sterbenz

17.15High-performance Canadian coaches attitudes and behaviours regarding technology implementation into their coaching practice

Jaswal, R.1, Stergiou, P.2, & Katz, L.1

1Kinesiology, University of Calgary, Calgary, Canada, 2 Canadian Sport Institute Calgary, Calgary, Canada.

AbstractPrevious literature and models have proposed that successful technology adoption measures involve positive attitudes towards technology, high levels of technological self-efficacy beliefs, low levels of perceived complexity, and high levels of perceived relative advantage These antecedents need to be investigated among national team coaches. The purpose of this study is to investigate the antecedents of technology adoption in the high-performance Canadian coaching space. Sixty-one current and previous Canadian national team coaches were contacted and asked to participate in this investigation. Coaches were tasked to complete: a general background information form, the Affinity for Technology Interaction (ATI) scale, the Computer Self-Efficacy Measure (CSEM), and the Perceived Relative Advantage/Complexity scales (PRA/PCo). Of these 61 coaches asked to participate, 25 completed the forms. CSEM scores and ATI scores were significantly correlated (r=0.433), however the correlation accounts for only 18.75% of the explained variance. Based on the scoring of the questionnaires coaches who responded showed a moderate affinity for technology when engaging with said technology in their coaching practice. They were also shown to have very high self-efficacy when it comes to using technology and a concomitant moderately high conviction in their ability to use technology. Finally, those Canadian national team coaches who responded generally viewed technology as giving them a high relative advantage over not using technology and also see technology as not very complex to operate. It would appear that those Canadian national team coaches who replied had generally favourable views of technology and had confidence in their ability to use technology including being capable of overcoming challenges in using technology. Perhaps coaches with less favourable attitudes did not respond which would skew the results. Future investigations should focus on encouraging national team programs to examine sport specific challenges in adopting and/or implementing technology.

Chair: N.James

17.25Parabolic running path of elite sprinters on curve of 400 metres track and independent angles of lanes : a referenced based cause-effect relationship.

Dr. K. K. Debnath, Degree College of Physical Education( Autonomous College) Shri. H.V.P. Mandal, Amravati, Maharashtra, India.

AbstractSports feats are multifaceted and vibrant state of affairs that offer a potentially huge magnitude of quantitative and qualitative information. The job of performance analysis within the coaching course of action generates quantitative information entailing awareness areas, be promptly acknowledged. Hence the biomechanical, mathematical & psychological studies of sprinting on a curve, is an interesting and attractive theory-practical investigation tasks for sports performers.

Descriptive & co relational statistics were used. Reference based studies pertaining to motion analysis, competitive psychology & mathematical models were surveyed, studied with deep introspection, had given appropriate weight-age for both qualitative & quantitative(core) information, compiled on master chart, critically analyzed & interpreted to identify the trends for sports performance

Results were overall consistent & significant in terms of investigating parameters of undertaken study. There is positive co-relation between higher sports performance & varied angles of lanes

Parabolic path is due to force of gravity acting on the runner between foot strikes with the ground. The runner pushes off the ground serves as an initial launch force, causes his center of mass to follow a parabolic arch. Greater the vertical force, bigger the horizontal running velocity, and longer the arch length, faster the runner. Degrees of angle of lanes vary from 5.78 -37.73(degrees). Centrifugal force, is additionally the force essential to thrust performer tangentially alongside track. Ultimately rely on “feel”, a combination of psychological factors based upon their positioning relative to other runners, and how their body feels as they settle into the race.

17.35Predictive Performance Analysis of Players Against Training Plan

S. P. Deshpande, D. P. Vaidya and N.V. Wankhade.1,2,3P. G. Department of Computer Science and Technology, Degree College of Physical Education, Autonomous College, Amravati, Maharashtra, India.

AbstractPerformance of any player in competitive sports is collective result of skill, physical and mental fitness, diet, training etc. Every human being is different and therefore personalization is required in every aspect. A System developed for predictive performance analysis of a player and assist coaches to extend personalized coaching to the player. Data mining method ‘Clustering’ is use for assigning the training plan to the player and another method ‘Time Series Analysis’ is use for analysis of performance and prediction of performance during the competition. Real time data capturing by using sensors devised to capture performance in every attempt during the training session. For better visualization and understanding, system generates graphical output. The result gives performance analysis of player against the applied training plan. System also suggests the best suitable training plan for the player based on anthropometric parameters. Time series analysis (linear regression) gives prediction of performance on the day of competition. Every player based on his physical, mental, social and economic status need to treat independently. A common approach during training/coaching badly affects performance of player. Personalized training/coaching/monitoring is difficult without tools for performance analysis. This system assists the coaches in administering and monitoring the training/coaching activity.

17.45Knowledge, Attitudes and Usage regarding doping drugs among national level athletes in Sri Lanka

Nilaweera, A.I., Nadishani, K.E.M.U.,, Nipunya A.G. and Wijekoon, N.,Faculty of Medicine, University of Colombo, Colombo, Sri Lanka.

AbstractDoping incidence has been increased in sports at all levels. Therefore a need for alternative approaches to address the doping concerns has arisen because doping not only threatens the health of pathlete but also the true spirit of sport. This was a cross sectional descriptive study of 347 Sri Lankan athletes of 20 national teams/pools for the years 2018/2019 who were recruited through stratified and random sampling. A self-administered questionnaire was used to assess knowledge and usage of doping drugs. A modified version of Performance Enhance Attitude Scale was used to assess attitudes. Majority of athletes (66.6%) couldn’t define the term WADA. Not more than 38% of athletes were aware about any given drug. Though attitudes regarding doping were positive in general, 8.3% of athletes admitted they would dope if they got a chance while athletes of individual sports had negative attitudes. According to Randomized Response Technique used, 8.4% of athletes had admitted usage of doping drugs. Doping was highest among athletes in individual sports (18.2%). Lack of knowledge, lack of self confidence and pressure to win were the main reasons for doping. Younger age, less experience, professionally being only an athlete, negative attitudes and knowing fellow athletes who used doping drugs were significantly associated(p<0.05) with doping. Younger inexperienced athletes and athletes of individual sports were more prone to doping and authorities should take special care of them. Actions should be taken to fill the knowledge gaps regarding doping. Special attention should be paid to improve positive attitudes regarding doping because negative attitudes were associated with doping than poor knowledge.

References

The World Anti Doping Code (2018).

18.05 Acute Weight Training-induced Testosterone Responses of Trained Males Across Age Groups and Diets: A Pilot Study.

Ciara Angeli and G. Juan,Department of Exercise Science, College of Human Kinetics, University of the Philippines, Diliman, Quezon City, Philippines.

AbstractTestosterone has been associated with health and athletic performance. However, it is also known to decrease with age in a condition called hypogonadism. The rise of these age-related, non-communicable diseases affect economic growth. In order to come up with safe and sustainable fitness and nutrition programs to keep the aging population healthy and fully functional, the present study explored weight training and diet as possible factors affecting hormonal levels and responses among men. Twelve recreationally trained men from different age groups (20s to 70s) and diets (vegans and meat eaters) completed a 30-minute weight training protocol. Blood samples were taken before and after exercise to determine exercise-induced changes in total testosterone (TT) levels. Additional hormonal tests for cortisol (C) and testosterone-cortisol ratio (T/C) were conducted for outliers to guide future research. Pretest-posttest analysis showed a statistically significant increase in TT within subjects; t(11)=-3.842, p=0.003. Younger men (35 years old and below) had a significantly greater increase in TT compared to older men (40 years old and above); X²(1)=4.121, p=0.042. Age group was negatively correlated with TT increase (r=-0.622, p=0.031). Compared to meat eaters, vegans showed a consistently higher and almost significantly different TT in both pretest and posttest. A single session of 30-minute, moderate intensity, high-volume leg exercise can significantly increase blood serum TT in men across age groups and diets. Younger men tend to show greater increases in TT compared to older men. Further studies are needed to explore veganism as a healthier and more environmentally sustainable diet.

with 2 minutes summary presentations

18.15 E-Posters

Chair: G. Sporis

Descriptors and definitions for the rugby league tackle

Hopkinson, M1., Bissas, A1., Nicholson, G1., Beggs, C1., Scantlebury, S1., Hendricks, S1,2 and Jones, B1,2,.1 Carnegie Applied Rugby Research (CARR) centre, Institute for Sport, Physical Activity and Leisure, Leeds Beckett University, UK2 Division of Exercise Science and Sports Medicine, Department of Human Biology, Faculty of Health Sciences, the University of Cape Town and the Sports Science Institute of South Africa, Cape Town, South Africa AbstractVideo analysis has been adopted within many sports as a tool to quantify performance and identify mechanisms of injuries (Burger et al., 2017; Krosshaug et al., 2007). Despite the continued use of video analysis in RU attempting to determine mechanisms of injury (Davidow et al., 2018; Hendricks et al., 2016), the association between specific RL tackle variables and injury risk in rugby league has yet be investigated. This is likely due to the lack of a RL tackle specific variable list which would be required. The aim of this study was to develop an ecologically valid and reliable variable list to be used in rugby league research. A 5 stage process was undertaken based upon recommendation by ODonoghue, (2014). This comprised of (1) a synthesis of literature and variable list draft, (2) an initial expert panel meeting, (3) a refinement of the draft variable list, (4) an expert panel agreement and (5) an intra and inter reliability testing of the variables. To evaluate intra and inter reliability Kappa statistics (κ) were calculated using 30 randomly selected rugby league tackles, with an external coder coding the same 30 tackles at least 7 days apart from the first coder (McHugh, 2012). The agreed variable list comprised of 66 variables within match event, defensive start point, pre-contact, initial contact, post-contact and play the ball phases. Descriptions of each phase and variable were created. The intra and inter-reliability testing resulted in at least moderate agreement (>0.6) with all phases. Due to the overall depth of the list, it is recommended that the variables within the list are used selectively, meaning researchers choose variables which are appropriate to the specific research question. In addition, it is important that the variable lists are to be used consistently between research as studies adopting video analysis depends on accurate and consistent interpretation of complicated scenarios, the researchers understanding of the variable is vital and therefore the descriptors and supplementary images should be used throughout analysis to optimise research output. References

Burger, N., Lambert, M. I., Viljoen, W., Brown, J. C., Readhead, C., Den Hollander, S., & Hendricks, S. (2017). Mechanisms and Factors Associated with Tackle-Related Injuries in South African Youth Rugby Union Players. American Journal of Sports Medicine, 45(2). https://doi.org/10.1177/0363546516677548

Davidow, D., Quarrie, K., Viljoen, W., Burger, N., Readhead, C., Lambert, M., Hendricks, S. (2018). Tackle technique of rugby union players during head impact tackles compared to injury free tackles. Journal of Science and Medicine in Sport. 21(10) https://doi.org/10.1016/j.jsams.2018.04.003

Hendricks, S., O’Connor, S., Lambert, M., Brown, J. C., Burger, N., Mc Fie, S., Viljoen, W. (2016). Video analysis of concussion injury mechanism in under-18 rugby. BMJ Open Sport & Exercise Medicine, 2(1). https://doi.org/10.1136/bmjsem-2015-000053

Krosshaug, T., Nakamae, A., Boden, B. P., Engebretsen, L., Smith, G., Slauterbeck, J. R., Bahr, R. (2007). Mechanisms of anterior cruciate ligament injury in basketball: Video analysis of 39

cases. American Journal of Sports Medicine. 32(4) https://doi.org/10.1177/0363546506293899

McHugh, M. L. (2012). Interrater reliability: the kappa statistic. Biochemia Medica. 22(3) https://doi.org/10.11613/BM.2012.031

ODonoghue, P. (2014). Research Methods for Sports Performance Analysis. International Journal of Performance Analysis in Sport. https://doi.org/10.4324/9780203878309

The relationship between the maximum isometric strength and the speed of the ball in the power serve in Beach Volleyball.

Pérez-Turpin, J.A.1, Terol-Sanchis, M.1, Gomis-Gomis, M.J.1, Elvira, C1.1General Didactics Department, Faculty of Education, University of Alicante, San Vicente del Raspeig, Spain

AbstractThe objectives of this study were to analyze the relationship between maximum isometric strength levels in different joints of upper and lower limbs and the serve speed in powers of competitive beach volleyball players, as well as to develop a prediction model based on this information. Eight male beach volleyball athletes performed the study (mean ± standard deviation, age: 21.6 ± 3.20 years, height: 1.87 ± 0.08 cm, body weight: 80.18 ± 7.11 kg). The participants are from a high competitive level nationally and internationally. They were tested using maximal isometric strength levels (wrist flexion, elbow and shoulder extension, leg and back extension, external and internal rotation of the shoulder). Serve speed was measured using a radar gun. Results showed a strong positive relationship between the serve speed and the internal rotation of the shoulder (r = 0.65, p <0.05). We also found low to moderate correlations between the potential serve speed and elbow flexion, extension of the elbow, external rotation of the shoulder, and extension of the leg and back (r = 0.41, r = 0, 14, r = 0.39, r = 0.28, p = 0.265). Bivariate and multivariate models were developed to predict serve speed, with shoulder flexion and internal rotation that explain 58% of the variance in serve speed (r = 0.79, p <0.001). The maximum level of isometric strength in internal rotation of the shoulder was strongly related to the serve speed, and a large part of the variability in the serve speed was explained by the maximum levels of isometric strength in internal rotation of the shoulder and the extension of leg and back.

References

Baiget, E., Corbi, F., Fuentes, J. P., y Fernández-Fernández, J. (2016). The Relationship Between Maximum Isometric Strength and Ball Velocity in the Tennis Serve. Journal of Human Kinetics, 53(1), 63–71.

Buscà, B., Moras, G., Peña, J., y Rodríguez-Jiménez, S. (2012). The influence of serve characteristics on performance in men’s and women’s high-standard beach volleyball. Journal of Sports Sciences, 30(3), 269–276. doi:10.1080/02640414.2011.635309.

Riggs, M. P., y Sheppard, J. M. (2009). The relative importance of strength and power qualities to vertical jump height of elite beach volleyball players during the counter-movement and squat jump. Journal of Human Sport and Exercise, 4, 221–236.

Everesting challenge attempt strategy: a case study.

L. Cesanelli1, G. Vici1, D. Camilletti1, R. Ceci1, L. Belli1, V. Polzonetti1

1School of Biosciences and Veterinary Medicine – University of Camerino

AbstractThe Everesting bike attempt (repeat any hill, anywhere in the world until you climb the altitude of 8848 m, the equivalent eight of M. Everest) is becoming an increasingly popular challenge. Physical and metabolic stress to which the body will be exposed during an effort like this are unusual. Parallelly athlete’s performance optimization represent also a singular challenge for coaches, trainers and sport nutritionists. One ex-élite cyclist, trained individual (male; 26 years; 181 cm; 71,7 kg; 21,9 BMI) followed a 10 weeks training and nutrition program to reach his peak performance and attempt the Everesting challenge. After selecting the climb to perform the challenge, body composition analysis (body weight, body circumferences, skinfold thickness and bioimpedance analysis) Conconi test, FTP (Functional Threshold Power) test and Blood lactate test were planned at week 1, 5 and 10. Additional Blood lactate tests were performed in order to find the right intensity (W) (Maximal Lactate Steady State MLSS) and consequently the right ascent time. Training program was structured to improve aerobic capacity and lactate threshold. Nutrition program was structured 1) to improve body composition 2) to improve and sustain performance. After 10 weeks FTP increased from 245 to 267 W and MLSS (4 mmol/L) from 252 W to 270 W. Body weight decreased from 71,7 kg to 68,3 kg and body fat from 10,7% to 6,8 % (Jackson-Pollock 7 sites). The individual was able to accomplish the Everesting challenge concluding his ride in 13h34m27s, average power 162 W, average heart rate 139 bpm, 7685 cal consumed. Ten weeks of strategically planned nutrition and training program may be sufficient to prepare an élite athlete or a well-trained individual to attempt an ultra-endurance challenge like the Everesting.

The Evaluation of the High Peak of Velocity in footballers. Survey of all category from an Amateur Youth Academy.

Bernardo Ricioppo1, Ciro Hosseini Varde’i1 and Riccardo Izzo1

1Department of Biomolecular Sciences, School of Sport Science, Exercise and Health, University of Urbino Carlo Bo, Urbino, Pesaro e Urbino 61029, Italy

Performed by ARGS, Advanced Research Group in Sport, School of Health and Sport Science with K-Sport Universal, Italy

AbstractThe players performance model (PPM) consists of numerous components that go to compete to create the sport performance itself. The analysis of performance of youth football, could offer different insights to be able to select the talent or differentiate the training sessions (Unnithan et al., 2012). The aim of this study is to investigate the high peak velocity in youth football category and to determinate, how much times, footballers reach this during matches. Other studies worked in sprint and high peak velocity, but no one of this were investigate differences between all categories (Brownstein et al, 2018). The ability of repeat sprints during matches is of certain importance, and is possible to increase with specific trainings (Vitale et al., 2018). As we know from literature maturity status affects performance, high peak velocity evolve during maturation. Were analysed 120 athletes belonging to an amateur academy, 30 for each category U-12, U-14, U-16 and U-18. The objective through a sprint test on 20 meters was to assess the average high peak velocity, for each category, and then go to analyse how many times it is achieved during the championship rounds. The sprint tests were performed using GPS 10Hz (K-Sport Universal, Montelabbate, Italy), each athletes repeats the test 3 times, and only the best performance was selected. Were analysed and was settled a High Peak velocity (HPV) Value for every category, based on average data. After for every category was analysed one match with the use of GPS in order to discover if and how much times the HPV was reached. Data were processed with proprietary software (K-Fitness, K-Sport Universal, Montelabbate, PU, Italy) and then analysed with using spreadsheets (Excel, Microsoft, USA). The S.D and the Max and Min values were calculated in order to analays better the output data. The S.D shows the deviation of the group analaysed and was higher in the U-14 and lower in the U-18, this results could be connected with the state of maturation of atlethes, that are more equalized more the age grow, as showed from our output data. The Max and Min data helps to understand the difference between the top value from the bottom, no particular differenc were detected between the Max value between U-16 and U-18 (respectively 29,7 and 29,8) in the other and the average of HPV is different, opposide happen for the Min value detected that are higher more the age grow and lower in U-12 and U-14. All the results lets us to assume that the maturation ratio in the group influence the results. The analysis of youth football performance can help and increase the selection of talent and help coaches to work better during training, this can be possible with a multifactorial analysis of footballers.

References

Unnithan V., White J., Georgiou A., Iga J. and Drust B. (2012). Talent identification in youth soccer. J Sports Sci., 30(15), 1719-26.

Brownstein C.G., Ball D., Micklewright D. and Gibson N.V. (20180. The Effect of Maturation on Performance During Repeated Sprints With Self-Selected Versus Standardized Recovery Intervals in Youth Footballers. Pediatr Exerc Sci. Jul 22:1-6. 2017-0240.

Vitale J.A., Povìa V., Vitale N.D., Bassani T., Lombardi G., Giacomelli L., Banfi G. and La Torre A. (2018). The effect of two different speed endurance training protocols on a multiple shuttle run performance in young elite male soccer players. Res Sports Med.: 1-14.

Analysis of the Physical efficiency index of football Teams and correlation with goal events. An Survey of the Italian Serie A Championship.

Lorenzo Canapini1, Ciro Hosseini Varde’i1 and Riccardo Izzo1

1Department of Biomolecular Sciences, School of Sport Science, Exercise and Health, University of Urbino Carlo Bo, Urbino, Pesaro e Urbino 61029, Italy

Performed by ARGS, Advanced Research Group in Sport, School of Health and Sport Science with K-Sport Universal, Italy

AbstractThe aim of this paper is centred on the Match Analysis (MA) of football that nowadays is a fundamental tool in the elite level (Barnes et at., 2014). The MA is the objectively analysis of matches using hardware and software that help the coaching staff to evaluate the physical-technical-tactical performance of the single athlete and the entire team in order to define the Performance Model (PM) (Barreria et al., 2014). The aspects to consider in a football competition are physical, technical, tactical and psychologica (Belling et al., 2015)]. The team average physical efficiency index (TA-PEI) evaluate in percentage the capacity of a team to handle every single event during a football match, the index range, move from 0 (worst efficiency) to 100 (best efficiency). It is calculated from various physical parameters derived from video tracking such as distance travelled, speed, acceleration, deceleration and metabolic power, all integrated in a single parameter showed in percentage. The TA-PEI is the average of values get registered from all the players during matches, it’s can be calculated for various time laps: for all the match, for the first half, for the second half, for every quarters (15 minutes), for every minutes or it can be selected in different technical scenarios (goal actions, defensive actions etc..). In our study, we take in consideration the TA-PEI during goal actions in order to objectively define if the physical performance is correlated with goals actions. Where examined using video-tracking 38 games of the 2015/2016 Italian Serie A, and calculated the TA-PEI during goal events for both teams. During this survey, 92 goals were scored, and 184 TA-PEI were collected. For each realization, the TA-PEI was examined, both by the finalizing team and by the team that suffered the goal. In the 67% of the cases, the TA-PEI was greater for the formations that scored, in the 20%, the TA-PEI was identical among the challenging teams and in the 13% cases, and the TA-PEI was greater for the clubs that have suffered the goal. The TA-PEI is absolutely an original and singular Index, and therefore not present in literature, it is not possible to have a state of the art concerning it. The objective of the research, were to identify the performance model in the specific goal situations, the TA-PEI parameter can help staff to receive more specific information during crucial moments of matches.

References

Barnes C., Archer D. T., Hogg B., Bush M. and Bradley P. S. (2014). “The evolution of physical and technical performance parameters in the English premier league”, International Journal of Sports Medicine, ISSN 0172-4622.

Barreria D., Garganta J., Castellano J., Prudente J. and Anguera M. T. (2014). “Evolución del ataque en fútbol de élite entre 1982 y 2010: Aplicación del análisis secuencial de retardos”. Revista de Psicología del Deporte, 23, . ISSN 1132-239X.

Belling P. K., Suss J. and Ward P. (2015). Advancing theory and application of cognitive research in sport: Using representative tasks to explain and predict skilled anticipation, decision-making, and option-generation behaviour. Psychology of Sport and Exercise, .16, ISSN 1469-0292.

Differences in technical-tactical indicators of karate kumite between the world championship in Tokyo 2008 and Madrid 2018.

Tihomir Vidranski, Petar Otkovic and Daria Zupan Tadijanov,Department of Kinesiology, Faculty of Education, University of Josip Juraj Strossmayer, Osijek, Croatia

AbstractThe Karate, for a decade now, has undergone the adaptation of their rules with a tendency for greater attractiveness and media enthusiasm to the best impression on the audience and media at its first appearance at the Olympics (Tokyo 2020). Therefore, the aim of this paper is to establish the trend of differences in the technical-tactical indicators of karate kumite between Karate World Championships in Tokyo 2008 and Madrid 2018. There were 274 contestants in Tokyo, seniors aged 18 and over in 137 combat, and 24 contestants in 12 combat in Madrid consisted 48 variables of techniques and tactics. The data was based on the 149 DVD videos. The karate fighting parameters were compared using Mann-Whitney U test. Analyses were performed using MedCalc statistical software 10.4 (MedCalc software, Ostend, Belgium) and P value < 0.05 were considered statistically significant. The results indicate that there is no statistically significant difference in 45 of 48 variables of technical tactical indicators between two championships. Three variables showed a statistically significant difference: Kizame Tsuki-not-scored in attack, Gyako Tsuki Jodan-not-scored in counteratteck and Gyako Tsuki Chudan-not-scored in attack. The results between the technical-tactical indicators of the karate fighting in the two world championships indicates that generally there are no significant differences, particularly in the score-based techniques. Hand-not-scored techniques, performed in Madrid showed lower level of frequency. Reasons for such results were in karate rules changes and in the increase of the fight length from 3 to 4 minutes that most probably led to energy rationalisation of movement structure.In this way, it can be concluded that today's karate fighters are less active from the aspect of non-scored techniques, compared to karate fighters ten years ago. Non-scored techniques within the combining technical structures of karate combat are likely to contribute that kind of differences.

References

World Karate Federation (2019). WKF Rules. Retrieved from: https://www.wkf.net/pdf/rules/wkf-competition-rules-2019_en-pdf-en-764.pdf.

Differences in biological age of the best U11 and U13 teams in Croatia

Ajman Hrvoje1 and Tomac Zvonimir2,1Faculty of Education, University Josip Juraj Strossmayer, Osijek, Croatia.

AbstractIt is known that among the individuals who are chronologically at the same age there are individuals who develop below the average as well as those above the average (Malina et al., 2004). The data on the level of biological development, are very important for the young athletes in sports (Rowlands, 2009). The aim of this research was to determine differences in biological age between male soccer players in the category U11 and U13 of the two best Croatian teams in the year 2011. The estimate for biological age was conducted by a validated questionnaire developed by the authors from the United Kingdom (?Taylor, 2001). Gender-specific, pubertal development self-assessment questionnaires were used photographs of the Tanner standards (Tanner, 1962). For all participants anthropometrical characteristics (height, weight and BMI) were determined. For all samples descriptive parameters were calculated and Mann- Whitney U test was used to determine differences. Statistically significant differences were not determined in morphological variables. Statistically significant differences were determined only in U11 category in Tanner 1. side standards (U=27,50; p=0.00), and in 2. side (U=41,50; p=0,01) but not in the U13 category (p=0.40). Statistically significant differences were determined in U11 category and maybe at this age that was a factor who had a significant impact on the final result of the championship.

References

Malina, R.M., C. Bouchard, O. Bar-Or. Growth, maturation and physical activity. (2nd edition). Champaign, IL, USA: Human Kinetics, 2004.

Rowlands, A. V. Methodological Approaches for Investigating the Biological Basis for Physical Activity in Children. Pediatr. Exerc. Sci. 21:273–278, 2009.

Taylor, S.J.C., P.H. Whincup, P.C. Hindmarsh, F. Lampe, K. Odoki, and D.G. Cook. Performance of a new pubertal self-assessment questionnaire: a preliminary study. Paediatr. Perinat. Ep. 15:88-94, 2001.

Tanner, J.M. Growth at Adolescence. Oxford: Blackwell Scientific Publications, 1962.

Impact of 24 weeks of strength training coupled to endurance training on endurance performance (HERO Dolomites 2019)

L. Cesanelli1, G. Vici1, D. Camilletti1, R. Ceci1, L. Belli1, V. Polzonetti1

1School of Biosciences and Veterinary Medicine – University of Camerino

AbstractDespite reports are still equivocal, in recent years different studies reported how strength training can impact positively on long-term endurance performance. Strength training can both induce positive adaption related to neuro-muscular-mechanical aspects (e.g. increased proportion of type IIA muscle fibres, increased maximal muscle strength and rapid force capacity, economy of movement, increased tendon stiffness) and metabolic adaptations (e.g. stimulation of anabolic pathways) and consequently body composition and physical condition of athletes. 14 trained amateurs’ cyclists (males; 27,03 ± 3,75 years; 177,15 ± 5,69 cm; 69,67 ± 8,53 kg; 22,2 ± 1,67 BMI) that completed the Hero Dolomites 2018 competition and signed to the 2019 edition (86 km, 4500 m), after giving informed consent, voluntary accepted to participate to the study. 7 of them (treated) followed a 24 weeks strength training coupled to endurance training program to increase performance, the other (untreated) followed their endurance training routines without any specific resistance training protocol. FTP (Functional Threshold Power) test and 1RM (One Repetition Maximum) test (barbell squat and leg press 45°) were planned at week 1, week 8, week 16 and week 24. 2019 race times were compared to 2018 once. Treated individuals showed increased strength (barbell squat: +29,7 ± 7,8 kg; leg press 45°: +53,5 ± 13,1 kg) and FTP (+23,2 ± 9,3 W) from week 1 to week 24. Both treated and untreated individuals improved their race time from 2018 to 2019 (treated: -51,4 ± 24,6 m; untreated: -11,8 ± 14,4 m). Treated individuals improved significantly race time from 2018 compared to untreated individuals (p<0,05). Structured and periodized strength sessions can be incorporated and maintained for the entire duration of a 24 weeks training program to improve endurance performance. Strength training coupled to endurance training may improve more endurance performance compared to endurance alone.

Electrical activity of the brain during fine motor activity – case study.

Damir Bavcevic1, Tonci Bavcevic1 and Bojan Masanovic2

1University of Split, Faculty of Kinesiology, Split, Croatia2University of Montenegro, Faculty for Sport and Physical Education, Niksic, Montenegro

AbstractAn important segment of researching ontogenetic development represents an area of visual-motor integration (Bavčević, 2015). In order to understand this process it is necessary to analyse its neurobiological fundaments, in the first place related to brain activities. The aim of was to analyse electrical activity of the brain during the performance of fine motor activities. The research was conducted as a case study of a seven year old male subject. Measuring electrical activity of the brain included an electroencephalographic recording of subjects during graphomotor activities by the use of a 14-channel EEG. The Test of Visual-Motor Integration (VMI) was applied to evaluate visual-motor integration of graphomotor type (T. Bavčević & D. Bavčević, 2015). The recording procedure consisted of three consecutive phases: 1) open eyes phase – 1 minute; 2) closed eyes phase– 1 minute; 3) solving the VMI test phase. The spectrum analyses in the first phase (open eyes) and also in the second phase (closed eyes) registered topologically symmetrical beta rhythm predominantly positioned in the left and the right temporal lobe. Electroencephalographic recording in the third phase (while solving the VMI test) resulted in an increase of the beta rhythm. The highest amplitudes were registered at the frequencies of 20 Hz, 23 Hz, 26 Hz and 29 Hz predominantly in the area of the right occipital lobe with irradiation toward the right parietal and temporal lobe. Obtained results confirmed an increased brain activity in subjects while performing graphomotor activities. The increase is dominant in the bandwidth of the beta rhythm, particularly in the upper part of the spectrum of 20 Hz and higher in the band of beta 3 waves. The findings imply that fine motor activities in children of the observed age require a high degree of concentration and sensorimotor control as well as a conscious control of thinking.

References

Bavčević, T. (2015). Research review of relation of visual-motor integration, motor abilities and ontogenetic development. In Z. Grgantov, J. Paušić, T. Bavčević, D. Čular, A. Kezić & A. Miletić (Eds.), Proceedings Book of the 5th International Scientific Conference "Contemporary Kinesiology", Split, 2015 (pp. 729-737). Split: Faculty of Kinesiology, University of Split.

Bavčević, T., & Bavčević, D. (2015). Construction and validation of the test for evaluation of visual-motor integration in children aged 7 to 10. Research in Physical Education, Sport & Health, 4 (2).

The analysis of 12-year old children's self-assessment of swimming ability.

Rastovski, D.1, Lovrinčević, J.1 and Ajman, H.1

1Faculty of Education, J.J. Strossmayer University of Osijek, Croatia

AbstractReport of the World Health Organisation (WHO, 2014) states that over 370,000 people drown every year. Over 50 % of these victims are younger of 25 years of age, which makes drowning the 3rdleading cause of death for children aged up to 15 years. One of the possible causes of drowning is bad self-assessment of swimming ability. In order to detect the real number of non-swimmers and the reliability of swimming self-assessment questionnaire, we have carried out a swimming ability test on a sample of 3670 children aged 12 years in Osijek County, Croatia. Self-assessment of swimming ability for children aged 12-year was conducted by a questionnaire which contained yes/no statements about swimming ability. Afterwards, the children who stated positively about their swimming ability were tested by standard swimming test atthe swimming pool. The results are presented in percentages. The analysis of results indicates a great number of children who statednegatively about their swimming ability(33.9%). After the swimming test at the pool, it was established that 41.73% of respondents could not swim, which makes a significant difference of 7.74%. A great number of children (520) had a wrong perception about their swimming ability, which can be attributed to their negative emotions – fear (anxiety, nervousness, worry, caution, tension, fright) and shame (discomfort, guilt, humiliation, sorrow). Another crucial factor of children’s misjudgment is not being familiar with the criteria for swimming ability.

References

Goleman, D. (1997). Emocionalna inteligencija –zašto je važnija od kvocijenta inteligencije? Mozaik knjiga, Zagreb.

Ižaković, D., RajleBrođanac, M., Grgurić, M. (2015) Praćenjeivrednovanjerada u područjuobukeneplivača u Osječko–baranjskojžupaniji.

World Health Organization. (2014). Global report on drowning: preventing a leadingkiller. World Health Organization.

Biomechanics of the Clean And Jerk in Weight Lifting National Jordanian Team.

Amer I. Al-Khleifat1 Maher Al-Kilani2 and Hashem A. Kilani3

School of Physical Education, University of Jordan, Amman, Jordan1,3

Hashemite University, Zarqa, Jordan2

AbstractSeven elite national Jordanian weightlifters were videoed at 50 fields per second from the sagittal plane during the execution of the clean and jerk (C&J) on an AMTI force platform with 3 weights of submaximal lifts; low medium and high weights (35%, 65%, 85%) of their maximum. Linear and angular kinematics of the barbell with the ground reaction forces histories of the lower body were analyzed using Kinova & APAS. A significant decrease was found in the maximum vertical velocity of the barbell during the second pull of the heaviest lift (p < 0.05). Maximum extension velocity of the hip joint significantly increased during the first pull of the heaviest lift (p < 0.05). Vertical velocity and maximum bar height decreased during the second pull, especially at 85%. Angle-angle diagrams of the knee and hip profile showed major differences among participants, especially at the 85% lift of their maximum.

Keywords: Kinematics, Barbell, Olympic Lifts .

sUptake and influence on time penalties of competitor worn stopwatches during a trial period in grassroots level Eventing.

Lauren Birkbeck1 and Georgina Ridal2,1 Animal Behaviour, Performance and Welfare Group, School of Animal, Rural and Environmental Sciences, Nottingham Trent University, United Kingdom.2 National Horseracing College, Doncaster, United Kingdom

AbstractBritish Eventing (BE) attracts more than 76,000 competitors each season, the majority of these at grassroots level. Each cross-country course has an optimum time for completion, with time penalties accrued for completing too fast or too slow. Rider worn stopwatches were permitted on a trial basis in 2016; previously, stopwatches were not permitted at grassroots level to discourage inexperienced competitors from altering speed dependent on the clock. Jumping fences at an inappropriate speed is considered to be a risk factor for falls in an already high risk sport. Penalties are cumulative, results deciding, and published, incentivising competitors to reduce. Aim: to observe uptake of stopwatch use and penalties accrued by grassroot competitors in the trial season. Natural observation of four days of grassroots competition (approved institutionally and by British Eventing Risk Management Committee). Mid-way and completion time, presence of visible stopwatch, and observed stopwatch viewing were recorded live, time and cross-country jumping penalty data added retrospectively; only clear jumping rounds were used (n=616). A stopwatch was observed on 32% of all competitors, with uptake increasing as competition difficulty increased (23% at BE80, 36% at BE90, 50% at BE100). Fewer time penalties were accrued by those wearing a visible stopwatch at BE80 (1.20 ± 4.05 seconds compared to 3.6 ± 8.53 seconds without, U = 4141, p < 0.001) and BE90 (0.4 ± 4.35s compared to 5.2 ± 9.07s, U = 50600.5, p < 0.01), no difference was seen at BE100 (0.00 ± 2.21s compared to 0.00 ± 3.01s). The use of a visible stopwatch resulted in fewer time penalties accrued during clear competitive cross country at BE80 and BE90. At BE100, no difference in time penalties was seen, however uptake of stopwatch use was greater. This may reflect more experienced riders being able to judge an appropriate pace from feel rather than measurement.

Teaching the service to novice athletes.

Dante Forte1 , and Gaetano Altavilla2 , 1University of Salerno, Salerno, Italy.2University of Split, Spit, Croatia.

AbstractVolleyball service is the fundamental element with which the game begins; it can be carried out from below, from a floating top, or from above in a jump. This article discusses the changes in speed and accuracy of service as a result of different training methods. A sample of 33 participants with no experience in volleyball was divided into three groups. Two groups carried out three weeks of training, the first following the ecological approach, in complete freedom, the second group following the mixed method (global-analytical-global) while the third group formed the control group. The participants were evaluated in advance and on two successive occasions. In each test, accuracy and speed of service were recorded. The results highlight the improvement in the accuracy and speed of the practice groups. In addition, the mixed training group presented greater consistency in accuracy, decreasing the variable error of their attempts. The main conclusion of the study is that the mixed training methodology can be a very effective method for learning the service in volleyball with inexperienced populations.

The analysis of endurance variables among young soccer players.

Ádám Gusztafik,Illés Academy, Szombathely, Hungary. adam.gusztafik@gmail.com<mailto:adam.gusztafik@gmail.com>

AbstractIn the field of soccer we talk about a wide range of endurance. Yo-Yo IRTL1 standardized test is a basic test protocol even in the case of young players. The progressive rise of the workload during the test shows how fit players are. We have used Polar Team2 control to monitor players' heart rate. Our target is to compare the young players performance in a Hungarian and a Serbian football academy. We carried out measurements involving different teams of different age groups of young players in Illés Academy, Szombathely, Hungary and in Topola Sports Club, Subotica, Serbia. N=138 players. In both clubs we tried to involve all the young players. While processing the data we used IBM SPSS Statistics25 program, which made it possible for us to analyze standard analysis, normality control, linear regression and correlation matrix analysis. (p<0.05) The difference between the results of the Yo-Yo test carried out in the two football academies is significant (2643.42m and 1551.29m). However, there is moderate correlation between the results of the endurance tests until the players reached the red zone (90-100%) (r=0.571; p<0.000). The time the players spent in the maximum intensity zone reveals high motivation. The most successful players managed to tolerate the highest workload. (r=0.541; p<0.000). We did not find any correlation between the Heart Rate Variability and the distances covered by the players. Therefore we suggest carrying out Polar Team2 control to monitor heart rate among young soccer players to create personal training programs for them.

Keywords: soccer, young soccer players, endurance, Yo-Yo test, polar

Examination of agility factors of junior football players in Topola, Serbia

Miklós Koltai,Eötvös Loránd University (ELTE), Faculty of Education and Psychology (PPK), the Institute of Sport Sciences, SzombathelyE-mail: koltai.miklos@ppk.elte.hu<mailto:koltai.miklos@ppk.elte.hu>

AbstractThe Institute of Sport Sciences in the Faculty of Education and Psychology (PPK) at the Eötvös Loránd University (ELTE) accepted the invitation from the University of Novi Sad, Teachers' Training Faculty in Hungarian, Department for Physical Education to collaborate – within the framework of an international program, involving students – in data collection for scientific research. The project was designed to collect data about junior football players using complex instrumental measurements. Agility is the ability to move easily and quickly; it infers rapid onset, sudden stops and changes in direction. In modern football, this factor is considered the most important one in terms of efficiency. U14, U16, U18 junior soccer teams of Topola Sport Club; N=66. Internationally standardized and recommended agility tests (Dribbling test, Illinois test, T-test). The movement structures of these tests perfectly model the solutions applied in the actual game. We used the Inbody 720 instrument measuring the body composition and Oxa Starter infrared timing gate instrument to measure speed agility tests; and the participants’ speed on 5, 10, 20, and 30 meters. The data have been processed with the IBM SPSS Statistics25 program (p<0.05). There is a moderate correlation between agility with a ball and without a ball (0.595). There is a moderate correlation between agility and body composition parameters: SMM, IWM, PM, MM (-0.453, -0.454, -0.453, -0.417) while the correlation between agility and Height, Weight, BMI,RLLM, LLLM, EWM is less than moderate (-0.318, -0.329, -0.276, -0.332, -0.330, -0.374). A slight correlation can be found between agility with a ball and body composition parameters. However, agility parameters and Body Fat Mass do not show any correlation. The merged agility skills' weak correlation (or from time to time the lack of correlation) with the most the selection of an ideal body build, nor the regular starting speed training have an indirect effect on agility. In modern soccer, agility is an extremely complex skill, and the exact structure of itsperformance components is hard to define. The factors influencing players’ agility should be emphasized and methodically developed in youth training in the light of future efficiency.

Key words: agility, junior, football

How playing basketball with distinct body height and biological maturation affects physical performance and tactical behavior?

Jorge Arede1, Sogand Poureghali2, Pedro Esteves 13, Wolfgang I. Schöllhorn4, Nuno Leite1

1 Research Centre in Sports Sciences, Health Sciences and Human Development, CIDESD, Vila Real, Portugal2 Otto-von-Guericke-Universität Magdeburg, Magdeburg, Germany3 Polytechnic Institute of Guarda, UDI: Research Unit for Inland Development, Guarda, Portugal4 Institute of Sport Science, Training and Movement Science, University of Mainz, Mainz, Germany

AbstractJuvenile basketball athletes show individual variation in maturation that results in interindividual differences at anthropometrical, physical, and technical level (Arede, Ferreira, Gonzalo-Skok, & Leite, 2019). This study aims to compare physical and tactical performance of young basketball players with distinct anthropometrical and maturation distribution. Ten young U-16 male basketball players played 5x5 half court situations (2 sets of 8 minutes, with 5 minutes of rest between sets). The players were allocated to two teams according to maturity offset (MO) and body height (Z-score across the squad). MO was estimated using a non-invasive method (Mirwald, Baxter-Jones, Bailey, & Beunen, 2002). Two distinct games were prescribed: i) more mature and taller vs less mature and smaller (Game 1); and ii) more mature and smaller vs less mature and taller (Game 2). Physical workload data was collected via WIMU PRO Local Positioning System, and included variables previously analysed in basketball scrimmage (Vazquez-Guerrero, Reche, Cos, Casamichana, & Sampaio, 2018). Also, maximum and average heart rate (HR) were recorded with individual HR monitors. Spatial exploration index was also calculated (Gonçalves et al., 2017). We found higher external and internal demands in Game 2. Less mature and smaller players explored more available space in Game 1 (ES = 0.79), and very largely more than their counterparts (ES = -1.34). Games 2 induces higher between-groups differences. More mature and taller athletes covered less distance in stationary per walking (ES = -1.27), in running (ES = -3.23), high-intensity decelerations (> -2 m s∙ -2; ES = -0.82), peak acceleration (ES = -1.09), and body impacts (> 5 g; ES = -0.81). Height and maturity levels provided evidence for high impact on physical and tactical dimensions of young players during basketball scrimmage. With this regard, manipulating anthropometrical and maturation during training may stand as a valuable strategy to promote specific training adaptations in youth basketball players.

Funding: Foundation for Science and Technology (Portugal), through a Doctoral grant endorsed to the first author [SFRH/BD/122259/2016] and under project UID/DTP/04045/2019.

References

Arede, J., Ferreira, A. P., Gonzalo-Skok, O., & Leite, N. (2019). Maturational development as key aspect in physiological performance and national team selection in elite male basketball players. International Journal of Sports Physiology and Performance, 14, 1–9.

Gonçalves, B., Esteves, P., Folgado, H., Ric, A., Torrents, C., & Sampaio, J. (2017). Effects of pitch area-restrictions during soccer large-sided game. Journal of Strength and Conditioning Research, 31(9), 2398–2408.

Mirwald, R. L., Baxter-Jones, A. D. G., Bailey, D. A., & Beunen, G. P. (2002). An assessment of maturity from anthropometric measurements. Medicine and Science in Sports and Exercise, 34(4), 689–694.

Vazquez-Guerrero, J., Reche, X., Cos, F., Casamichana, D., & Sampaio, J. (2018). Changes in External Load When Modifying Rules of 5-on-5 Scrimmage Situations in Elite Basketball. Journal of Strength & Conditioning Research, 00(00), 1–8.

Spatial-temporal metrics to assess collective behaviour in football: a systematic review. Martin Corsie, Neil Buchanan, Thomas Craig and Paul Swinton,School of Health Sciences, Robert Gordon University, Garthdee Road, Aberdeen, UK.

AbstractWithin performance analysis of soccer there is growing interest in the measurement of players’ collective behaviour using novel metrics. The present study comprised a systematic review of research investigating spatial-temporal metrics in soccer. Five electronic databases were searched for studies published between 2008 and 2019. Included studies were required to investigate metrics that tracked at least two positional references across time to infer players’ collective behaviour in either training sessions or matches. The search identified 1100 studies, 77 were retrieved in full text and 69 were included in the review. Author quotes regarding metric: 1) description; 2) validity/reliability; and 3) practical applications, were extracted and analysed. Additionally, an adapted 12 item critical appraisal tool was used to assess study quality. A total of 123 individual metrics were reported across the 69 studies. A thematic analysis of metric descriptions identified 6 primary categories: 1) dispersion [n=101]; 2) centroid [n=62]; 3) synchrony; [n=39]; 4) dyad [n=34]; 5) entropy [n=27]; and 6) technical-tactical [n=5]. Thirty five studies were conducted with adult participants and the remaining 34 studies with youth teams. The majority of studies investigated spatial-temporal metrics during training [n=46], and all studies achieved at least a moderate classification for research quality. Descriptions and formulas of metrics were generally consistent across studies. However, in the majority of cases metric descriptions did not clearly integrate with principles of play in soccer or common coaching philosophies. Metric validity was identified on only 17 occasions, and less than half the studies [n=31] clearly discussed practical applications or made recommendations for performance analysts. Collectively, the review identifies that a range of innovative metrics can be used to quantify players’ collective behaviour in soccer, however, future research should link metrics to underpinning principles of play and make clear recommendations to increase transfer to practice.

Design and validation of an observational system in Beach Volleyball.

Duarte Sousa1, Rodrigo Casanova1, João Prudente1,2

1Department of Physical Education and Sport, Faculty of Social Sciences, University of Madeira, Portugal2C.I.D.E.S.D., Portugal

AbstractThe analysis of Team Games has been the object of a growing interest on the part of researchers and coaches, and there has been a great deal of research carried out in this field and Beach Volleyball (BVB) is not an exception.The need to evaluate, get more knowledge about the game and to verify if the introduction of new rules brings the desired changes in the durations and actions used, became necessary to create an adequate observational system to observe Beach Volleyball. We used Observational Methodology. To validate the ad hoc observational system, the validation of the construct was done by expertise through the application of an survey to 9 Volleyball experts, using a cohort value of 65%. For data analysis it was used descriptive statistics and prospective and retrospective sequential analysis technique. After the validation of the construct, an experimental study was carried out with a sample of 4 matches of the BVB 2015 Men´s World Championship in the Netherlands Intra- and inter-observer reliability was tested by Kappa Coefficient (results 0.87). The G test was used, in order to test the generalizability. The value of 99.84% showed that the variance was associated to the facet categories, and G index (relative and absolute) obtained of 0.99, proved a high level of reliability and precision. The results obtained in the experimental study on reliability and generalization allow us to affirm that the built instrument was adequate to evaluate the impact that the introduction of the new rules in the BVB bring to this sport.

Training load effect on hamstring passive stiffness.

D. Satkunskiene 1, T.M. Silva 2, S. Kamandulis 1, N.M.C. Leite 3, A. Domeika 4, M. Mickevicius1, A. Snieckus 1

1 Institute of Sports Science and Innovation, Lithuanian Sports University, Kaunas, Lithuania;2 University of Trás-os-Montes and Alto Douro, Vila Real, Portugal;3 Research Center in Sports Sciences, Health Sciences and Human Development, CIDESD, University of Trásos-Montes and Alto Douro, Vila Real, Portugal;4 Kaunas University of Technology, Kaunas, Lithuania.

AbstractBiomechanical adaptation may be slower than physiological adaptation leading to the overloading of the musculoskeletal system capacity and increased risk of injury (Vanrenterghem et al., 2017). The purpose of this study was to identify changes in hamstring passive stiffness during the pre-season and in-season periods, and to evaluate the associations between the external and internal training loads and changes in hamstring strength and passive stiffness changes. Hamstring strength and passive stiffness were measured in professional male soccer players before and after the pre-season (4 weeks), and after the in-season (6 weeks) periods using an isokinetic dynamometer. Muscle passive stiffness was determined from the slope of the passive torque–angle relationship. External loads (acceleration and jumps) were monitored by GPS and internal loads by questionnaire. Hamstring passive stiffness increased after 10 weeks of training and matches, without changes in passive peak torque and range of motion. The mean value of the external load accumulated during the last four weeks in-season period was 9088.87 ± 973.40 A.U. The average internal load was 7057.59 ± 795.25 A.U. The hamstring passive stiffness modifications were associated with the volume of the external load. The individual data analysis also provided some support for the suppression of the biomechanical adaptation in the subjects with relatively large external load. The different levels of the applied loading conditions and general exercise conditions may considerably affect connective tissue adaptive responses (Bohm et al., 2015). Adding exercise repetitions did not increase collagen synthesis further, but potentially increased the degradation and further amplified the negative net balance of collagen (Magnusson et al., 2010). We found that regular training and match workouts increase hamstring passive stiffness in professional soccer players but the adaptation of muscle-tendon unit passive elements could slow down or might not occur if players experience excessive mechanical stress.

References

Bohm, S., Mersmann, F., & Arampatzis, A. (2015). Human tendon adaptation in response to mechanical loading: A systematic review and meta-analysis of exercise intervention studies on healthy adults. Sports Medicine-Open, 1(1), 7.

Magnusson, S. P., Langberg, H., & Kjaer, M. (2010). The pathogenesis of tendinopathy: Balancing the response to loading. Nature Reviews Rheumatology, 6(5), 262.

Vanrenterghem, J., Nedergaard, N. J., Robinson, M. A., & Drust, B. (2017). Training load monitoring in team sports: A novel framework separating physiological and biomechanical load-adaptation pathways. Sports Medicine, 47(11), 2135–2142.

Practical application of Big Data - Multidimensional analytical methods in sports.

Mátyás Tamás Sonkoly, József Csicsman (foreign consultant)Department of Computational Optimization, University of Szeged, Szeged, HungaryÚj Calculus Számítógép-alkalmazási Bt., Budapest, Hungary

Abstract

It was a real request to predict the result of a football matches by using professional sportmen’s training data from CATAPULT system. I got the result of the football matches in same period and we had to accept a definition for performance of the players and ’good’ and ’bad’ matches to start the data mining process and make predicting model with minimum 80% accuracy. The database needed a great amount of reconfiguration. Some deep learning methods don’t tolerates missing, unfitting and false informations. I had to explore the possibility of connection between the match results and the training performances. K-means clustering method help me and proved my presumption. In data mining phase, neural network, decision tree and logistic regression methods were applied and competed. I used the SAS Base for data manipulation; and the SAS Enterprise Miner easy to use application for data mining. Methods provided the next variables as the most influential variables of the result of a match:

Players’ time spent in given zones Inertial Movement Analysis datas, intensity of acceleration, deceleration, and direction change The time spent in the acceleration categories The count of high jumps (headings)

Models were trained in a part of the database and validated in an independent other part of it. The next accuracies of methods were received at validation – when the model predicts the result correctly:

Decision tree: 85% Logistic regression: 75% Neural network: 66% Combination of the first three: 82%

As the result shows we found method above 80%. We agreed to get a useable method for predict the result of the match if we know the players’ performance of the previous trainings. I worked only one year data of a team which means a few amount of football matches. To achieve a functional system and calculate a wide and legitimate spectrum of result for games, I would need more data . I could bring new and different variants in the procedure if I know the team’s all opponent list, matches played home and foreign countries, all players in matches and their positions etc.If these requirements were met we could provide a more precise understanding of those true factors which determines the games.