Crafting Champions: An Observation Study of Esports Coaching Processes

Research Background and Issues

• What problems or challenges did the authors identify?
  The field of esports coaching is still in its early stages of development, lacking standardized best practices, methods for evaluating student performance, and systematic technological tools to support coaches. Current research on coaching practices is insufficient, particularly in terms of fine-grained observation and analysis of coaching processes from an HCI perspective. Additionally, many coaches face challenges such as pressure, limited resources, and a lack of standardized methods for guiding students.

• Why is this issue important?
  As esports evolves into a multi-million-dollar industry, the demand for professional coaches is increasing. A thorough understanding of the coaching process not only helps improve students' skills but also leverages HCI (Human-Computer Interaction) theories and practices to provide technological support for coaches, thereby enhancing the overall performance and well-being of participants.

• Research Motivation and Related Work
  The authors emphasize that traditional approaches primarily focus on interviews without delving into the activities and interactions within the coaching process. While the HCI field has made progress in supporting sports-related health, learning, and emotional management, these findings and theories have not been fully applied to the esports coaching domain.

Solutions

• What methods or solutions did the authors propose?
  The authors adopted an observational research method to document and analyze specific activities and events during the esports coaching process. They conducted their study at a professional esports training academy in South Korea, collecting 112 hours of coaching session videos, audio recordings, and screen capture data, supplemented by interview data with coaches. From this data, they identified 18 themes related to the coaching process.

• What are the innovative aspects of this solution?

  1. Observational Research Method: Unlike previous interview-based studies, this observational approach captures subtle interaction processes and dynamic information.
  2. High-Level Esports Coaching Cases: The study was conducted in an advanced esports academy, providing an opportunity for in-depth analysis of top-tier training environments.
  3. Integration of HCI Theories: Grounded in HCI theories, the study connects research findings with the potential for technological support, exploring ways to enhance the effectiveness of esports coaching.

• What are the implementation steps and key technologies used?

  1. Collect interaction data between coaches and students, including live game evaluations, student game replays, and external game case analyses.
  2. Transcribe and analyze the collected audio, screen, and video data.
  3. Supplement observational data with interviews to clarify coaches' perspectives and challenges.
  4. Use thematic analysis to categorize the data, identifying and summarizing common activities and events.

Research Findings

• What specific results were achieved?
  Through analysis, the authors developed an activity model of the esports coaching process, categorized into three main activities (real-time guidance, student game replay analysis, and other player replay analysis) and 18 detailed events. These events include coaches' inputs (e.g., error correction, lifecycle advice), students' participation (e.g., agreeing with or explaining the coach's feedback), emotional and motivational management, and evidence sources used by coaches (e.g., game states, statistics).

• What advantages does it have over existing solutions?

  1. Fine-Grained Data Analysis: The study reveals real-time activities within the coaching process and their specific impacts on students' behavior and skill improvement.
  2. Application of HCI Perspectives: By linking coaching practices with HCI theories, the study opens up new technological directions to support coaching roles, such as AI assistants and emotion-sensing tools.
  3. High-Level Esports Data Samples: Data from top-tier esports coaches and students provide valuable references.

• What are the experimental or evaluation results?

  1. Focus on Logical Errors: Coaches spend more time and effort correcting students' decision-making errors, with less emphasis on physical operational skills.
  2. Student Motivation Issues: Despite students paying high fees, coaches generally feel that students lack motivation.
  3. Coaches' Burden: Coaches are tasked with managing students' emotions, explaining game states, and overseeing student performance, but their support resources are limited.

• Limitations and Future Directions

  1. Sample Limitations: The study focused on three coaches and their students at a South Korean esports academy, without involving samples from other countries or competitive levels.
  2. Single Game Type: The research centered on League of Legends, and coaching practices for other game types may differ.
  3. Incomplete Psychological and Behavioral Analysis: The study did not deeply analyze interaction details between coaches and students, such as tone and body language.

  Future Directions:

  • Expand the scope of observation to study practices at more academies and with students of varying skill levels and cultural backgrounds.
  • Explore team coaching models and compare them with existing individual coaching approaches.
  • Develop technological tools to support coaching roles, such as AI-assisted systems and emotion-sensing platforms, to reduce workload and improve student outcomes.

Conclusion

This study, through the observation of actual esports coaching processes, highlights the challenges coaches face in correcting logical errors, managing emotions, and enhancing student motivation. The research underscores the necessity of integrating HCI theories to implement technological interventions that support coaching roles and improve the overall performance of esports students. It lays a solid foundation for future research in the esports coaching domain and opens new avenues for applying HCI in esports contexts.