Search Results - Big data
-
1
A generative approach to frame-level multi-competitor races
Stokes, T., Bagga, G., Kroetch, K., Kumagai, B., Welsh, L.Published in Journal of Quantitative Analysis in Sports (2024)“…We apply this methodology to one-mile horse races using frame-level tracking data provided by the New York Racing Association (NYRA) and the New York Thoroughbred Horsemen`s Association (NYTHA) for the Big Data Derby 2022 Kaggle Competition. …”
-
2
Reliability of joint angle calculation in running movements using an inertial measurement unit
Hamada, K., Okazaki, S., Nakagawa, K.Published in 28th Annual Congress of the European College of Sport Science, 4-7 July 2023, Paris, France (2023)“…During the calibration, the subjects were instructed to face forward and align both upper limbs with the trunk so that the joint angle reference points would not shift, and the feet were grounded parallel to the ground and the distance between the big toes was standardized at 10 cm. To assess the reliability of same-day measurement data, running measurements were taken twice daily on a treadmill (BIODEX, PRO WWT-600) at 10.0 km/h for 30 s. …”
-
3
Predicting future stars: Probability and performance corridors for elite swimmers
Born, D.-P., Stöggl, T., Lorentzen, J., Romann, M., Björklund, G.Published in Journal of Science and Medicine in Sport (2024)“…Objectives To evaluate the new age groups of the World Junior Championships in swimming from a scientific perspective, establish benchmarks and performance corridors that predict success at peak performance age and compare performance corridors between men and women and short-, middle-, and long-distance freestyle races. Design Longitudinal big data analysis. Methods In total, 347,186 annual best times of male (n = 3360, 561 ± 177 Swimming Points) and female freestyle swimmers (n = 2570, 553 ± 183 Swimming Points) were collected across all race distances at peak performance age and retrospectively analyzed throughout adolescence. …”
-
4
Match running performance characterizing the most elite soccer match-play
Modric, T., Versic, S., Morgans, R., Sekulic, D.Published in Biology of Sport (2023)“…In order to identify match running performance (MRP) characterizing the most elite soccer matchplay, this study aimed to examine position-specific differences in the MRP of players competing in "big five" (BFLTs) and "non-big five" league teams (N-BFLTs). …”
-
5
Running endurance in women compared to men: retrospective analysis of matched real-world big data
Le Mat, F., Gery, M., Besson, T., Ferdynus, C., Bouscaren, N., Millet, G. Y.Published in Sports Medicine (2023)“…Laufausdauer von Frauen im Vergleich zu Männern: retrospektive Analyse von abgeglichenen Big Data aus der realen Welt…”
-
6
Olympic coaching excellence: A quantitative study of Olympic swimmers` perceptions of their coaches
Cook, G. M., Fletcher, D., Peyrebrun, M.Published in Journal of Sports Sciences (2022)“…The questionnaires assessed perceptions of 12 variables within the Big Five personality traits, the dark triad, and emotional intelligence, and the data was analyzed using three one-way multivariate analysis of variance and follow-up univariate F-tests. …”
-
7
Pain processing in elite and high-level athletes compared to non-athletes
Pettersen, S. D., Aslaksen, P. M., Pettersen, S. A.Published in Frontiers in Psychology (2020)“…Background: Previous studies shows that elite and high-level athletes possess consistently higher pain tolerance to ischemic and cold pain stimulation compared to recreationally active. However, the data previously obtained within this field is sparse and with low consistency. …”
-
8
Olympic coaching excellence: A quantitative study of psychological aspects of Olympic swimming coaches
Cook, G. M., Fletcher, D., Peyrebrune, M.Published in Psychology of Sport and Exercise (2021)“…The questionnaires assessed 12 variables within the Big Five personality traits, the dark triad, and emotional intelligence, and the data was analyzed using three one-way multivariate analysis of variance and follow-up univariate F-tests. …”
-
9
Zukunftsperspektive von Sportinformatik & Sporttechnologie im Leistungs- und Breitensport (Future prosepcts of sport informatics and sport technology im elite and grassroot sport)
U. Fehr, V. WernerPublished 2021“…Sports Innovation: Smart Equipment and Wearable Technology " Session Informations- und Feedbacksysteme " Sport-Informationssysteme - Review verschiedener Produkte basierend auf einem sportinformatischen Architekturkonzept " Effiziente Suche und Bewertung von Szenen in Spielsportarten " Überprüfung zeitlicher und räumlicher Genauigkeit im Trampolinturnen Validierung einer Web-Applikation zum Fern-Monitoring von Belastungs- und Erholungsparametern " Einsatzmöglichkeiten und Transfer von Künstlicher Intelligenz im internationalen Spitzensport - zwischen Small und Big Data " Einsatz von Künstlicher Intelligenz im internationalen Spitzensport - Eine Erhebung des Status Quo " Darstellung von Informationen im Bereich des Peripheren Sehens bei Sportlern/innen " Session Messtechnik und Datenanalyse 1 " Eignet sich OpenPose zur 3-D-Analyse im Leistungssport? …”
-
10
Human running performance from real-world big data
Emig, T., Peltonen, J.Published in Nature Communications (2021)“…Menschliche Laufleistung aus Big Data der tatsächlichen Welt…”
-
11
Comparisons of performances for determining the relative importance in the modern pentahlon
Lee, S.-H., Park, J.-C., Kim, K.-B., Kim, S.-J., Ko, B.-G.Published in Korean Journal of Sport Science (2020)“…The fencing event plays a major role in passing the qualifiers and is a big variable for good performance in the finals. …”
-
12
Study on optimization and innovation of swimming technique
Xin, Z. W.Published 2018“…With the correction action in technical movements and new system training programs to increase the speed of the swim, the study has a big breakthrough in the future of the swim team.This study has carried out data analysis of the swimming team of a primary school in Guangzhou and national team of China, so as to study the training program of the most suitable members to improve the performance of the team members of the swimming team. …”
-
13
-
14
-
15
Innovations and pitfalls in the use of wearable devices in the prevention and rehabilitation of running related injuries
Willy, R. W.Published in Physical Therapy in Sport (2018)“…What makes a wearable device valuable? 5. Wearables and big data: predicting running performance and the epidemiology of running injuries 6. …”
-
16
-
17
Development of a worldwide network for the purpose of hypothesis-driven research through data mining
Ferber, R.Published in International Calgary Running Symposium, August 14-17, 2014 (2014)“…We also know that this goal of extracting and analysing big data via high-performance computing is only possible through a collaborative and international community: one we continue to build.…”
-
18
Understanding and analyzing a large collection of archived swimming videos
Sha, L., Lucey, P., Morgan, S., Sridharan, S., Pease, D.Published in IEEE Workshop on Applications of Computer Vision (2014)“…Big Data…”
-
19
Relationship between isokinetic muscle strength and 100 meters finswimming time
Kunitson, V., Port, K., Pedak, K.Published in Journal of Human Sport & Exercise (2015)“…Finswimming is a sport where athlete uses one big monofin to produce propulsion. The purpose of this study was to describe relationship between isokinetic strength of different muscle groups and 100 meters finswimming time. …”
-
20