The complexity of the throwing motion, which involves high abduction angles and explosive movements

The gap

Evidence profile

Sourced from the stated challenges and stated research gap and limitations section of the source papers, classified as general, drawn from work published between 2025 and 2026, spanning 3 journals. Those papers have been cited 21 times in total.

Supporting evidence — 3 representative gaps

• Early Rate of Force Development and Maximal Strength at Different Positions of the Athletic Shoulder Test in Baseball Players (2025) · Sports · cited 5× · doi

  One challenge is the complexity of the throwing motion, which involves high abduction angles and explosive movements. Another challenge is the need to consider individual differences in shoulder strength and neuromuscular coordination among baseball athletes. The study also highlights the challenge of measuring force output accurately and reliably in different shoulder positions.

  generalstated challengesevidence 5/5
  Keywords: one challenge complexity throwing motion involves high abduction
• Pose-derived biomechanical feature profiling and proxy pattern classification of basketball player movements (2026) · Scientific Reports · doi

  The lack of action-level labels in existing basketball datasets makes it challenging to classify basketball-specific movements. Prior work has focused on classifying basketball actions using machine learning models, but these models require large amounts of labeled data. The analysis of basketball player movements is a complex task due to the variability in player movements and environments.

  generalstated research gapevidence 5/5
  Keywords: lack action-level labels existing basketball datasets makes challenging
• Action Recognition in Basketball with Inertial Measurement Unit-Supported Vest (2025) · Sensors · cited 16× · doi

  The system was evaluated using a single sensor placed on the back, which, while effective, may not capture the full range of complex movements involving the arms and legs, such as shooting or passing variations with greater biomechanical complexity. The dataset used, though diverse, included a limited number of participants, which may have reduced the generalizability of the results to larger and more diverse athletic populations. The study also focused on fundamental basketball movements, and the system's performance in more complex sequences or game scenarios with increased movement overlap was not fully tested.

  generallimitations sectionevidence 5/5
  Keywords: system was evaluated using single sensor placed back

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