Nara Jang

Dr. Nara Jang


Research Focus & Metrics

Academic Career Length

2Years (2025-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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28 April 2025 in BMC Sports Science, Medicine and Rehabilitation
Verified
Journal Article
Open access
PDF file
HYHyo-Jun Yun
Hyo-Jun Yun
NJNara Jang
Nara Jang
MJMinsoo Jeon
Minsoo Jeon
This study aims to define and cluster tennis match types based on how they are played. The research data selected for this study were from the 100th round of 32 matches of the five finals of the 2023 International Tennis Open Tournament. Based on expert knowledge and sports expertise, 27 variables were included across seven areas. Three models were applied and the silhouette coefficient was calculated to identify the optimal number of clusters. A difference test was conducted on the game record variables based on the cluster results. Calculation of the silhouette coefficients for the three models showed that Model 3 (silhouette coefficient: 0.406) had the highest performance. The clustering results for the tennis match types are as follows. First, the NEt Rusher Defensive type, which is defensive and induces net play. Second, the ALl Courter Defensive type, which is either defensive or all-round. Third, the STroke Placement Offensive type, which is aggressive and has strengths in stroke. Fourth, the SErve Placement Offensive type, which is aggressive and has strengths in sub courses. This study’s findings are not only provide basic data to cluster game types in tennis matches but also to contribute to establishing game strategies for each game type, thereby further improving performance.

26 April 2025 in Life
Verified
Journal Article
Open access
PDF file
BMByeong Seok Min
Byeong Seok Min
NJNara Jang
Nara Jang
This study aims to identify the prevalence and patterns of sports injuries in recreational sports activities in South Korea. This study utilized data from the “survey of safety accidents” conducted by the Korea Sports Safety Foundation and finally, 3182 recreational sports participants who experienced injuries were selected for the study. For data processing, data related to recreational sports injuries were first collected and organized using Excel 2015, and frequency analysis was conducted using the SPSS 25.0 program. Furthermore, the association rule method was applied via Python 3.13.3 to analyze the patterns of injury sites and types. First, by investigating the prevalence of injuries in recreational sports, it was found that the injury frequency was highest in soccer, followed by cycling, hiking, and badminton. Second, in soccer, it was found that when ankle injuries, which have a high injury frequency, occur, knee, toe, and sprain injuries also occur together (Lift: 1.843). Additionally, in cycling, when knee injuries occur, toe, sprain, and strain (bruise) injuries also occur together (Lift: 2.420). In mountain biking, when ankle injuries, which have a high injury frequency, occur, cuts, sprains, stab wounds (cuts), sprains, and strains (bruises) also occur together (Lift: 1.808). The current survey on recreational sports injuries is expected to be used as basic data to prevent injuries in advance for participants in recreational sports, and it is expected that this will allow them to participate in sports by recognizing common injury sites before participating in sports.