# Sport Performance Analysis with a Focus on Racket Sports: A Review
## 3 Results
### SR2: A Systematic Review of Publications on Racket Sports
#### 3.2.1 Classification by Racket Sport and Methodology
To characterize the data collected from the tournament platform, the published analysis employs average, median, standard deviation, quartiles, minimum, and maximum values. The Shapiro Wilk statistical test was used to confirm the data's normality. The Mann-Whitney test was used to compare the maximum difference in points established by the game's winners and losers. In (2013), the Crosstabs-Command and binomial logistic regression methods were used to determine the interactive effects of each contextual variable on challenge success (gender, requester player, next point winner, score-line, game, game interval, games in favor, challenges left per game, match-outcome, and player's international experience). The main findings revealed that the request affects the success of a challenge with less efficiency when the player requests the hawk-eye (odds ratio [OR] = 0.65) and when the player who requests the hawk-eye is the loser of the match (OR = 0.21). The identified trends enable players to improve strategic plans that include determining the best time to request a Line Review. [PERSON] et al. (2017) found statistical differences in a set of badminton competition matches in five different modalities in terms of competition level (Group Phase vs. Eliminatory Phase). Non-parametric data were subjected to a descriptive analysis and a univariate test (Mann-Whitney U). The findings of the analysis presented here could assist players and coaches in planning and implementing various types of workouts or, more specifically, competition schedules tailored to the characteristics of badminton. Combine Approach  
[PERSON] et al. (2013) combined observational approach (10 expert coaches) with a random forest algorithm. The publication emphasized the benefits of performance analysis from the juxtaposition of subjective and objective data to design training plans based on the participants' level of expertise. Neural Networks  
The recent work of [PERSON] et al. (2019) on bipartite networks for modeling racket sport performance. Non-linear and ecological approaches are associated with bipartite networks. Badminton stroke networks (BSN) were created by analyzing a player's and their opponents' match activities. The model was able to recognize various playing patterns. The identification of each player's network and its association with point outcomes, in particular, provided a better understanding of stroke performance and individual characteristics of world-class badminton players. [PERSON] et al. [97] focused on creating an automated system that used Faster Region Convolutional Neural Network (Faster R-CNN) to track the position of the badminton player from the sport broadcast video. Several different trained Faster R-CNN detectors were generated from the dataset before being tested on a variety of videos to assess detector performance. The study found that when the detector is fed a more generalised dataset, it successfully detects the player. [PERSON] et al. [99] used a pretrained Convolutional Neural Network (CNN) method to create an automated system for badminton smash recognition on widely available broadcasted videos. The CNN models were built using smash and other badminton actions from the video, such as clear, drop, lift, and net. Tennis is primarily depicted as a racket sport in the literature that has been reviewed. Considering that it is famous worldwide, as opposed to badminton, which is the most popular at the competitive level in Asia, this is not a surprising outcome. Four broad groupings of performance analysis categories have been identified across 65 publications reviewed. Although tennis is the most researched sport, only one paper addressed tracking software as a tool for performance evaluation. The publications for badminton, padel tennis, and table tennis feature all four groups, followed by tennis publications with three groups, and finally squash publications with only two ways.