https://ecp.ep.liu.se/index.php/linhac/issue/feedLinköping Hockey Analytics Conference2024-07-12T14:00:04+02:00Open Journal Systems<p>LINHAC brings together professionals and academics with an interest in hockey analytics. It features the latest research in hockey analytics in academia and companies, discussions with analysts and coaches, industry sessions with the latest hockey analytics products, and an analytics competition for students.</p>https://ecp.ep.liu.se/index.php/linhac/article/view/1035Cognitive Assessment and Profiling for increased understanding of Individual and Team Game Intelligence and Performance in Ice hockey2024-07-12T13:35:10+02:00Anders Norénanders.noren@capacio.com<p>Game intelligence, the ability to be in the right place at the right time and make optimal decisions, is crucial for athletic performance. This whitepaper explores how neurocognitive testing and profiling can deepen our understanding of game intelligence, which includes elements such as situational awareness, decision-making, problem-solving, and flexibility.</p> <p>The whitepaper targets sports professionals aiming to enhance their understanding of game intelligence through neurocognitive assessments. The assessments mentioned in the paper provide insights into athletes’ cognitive strengths and weaknesses, aiding in talent identification, personalized coaching, strategic team composition, tactical adaptations, and injury prevention. Executive functions are crucial in both open sports (e.g., soccer, basketball) and closed sports (e.g., archery, golf). For example, in ice hockey, players must continuously adapt to dynamic environments, requiring quick decision-making, strategic thinking, and creativity.</p> <p>Integrating neurocognitive assessments into sports practices has the potential to enhance the understanding of game intelligence, reduce subjectivity and bias, and improve individual and team performance, As well as ensure the wellbeing of athletes through tailored mental health support and coping strategies. Testing and profiling of individuals and teams can practically help enhance understanding of Game Intelligence. The process involves assessment, awareness, individual acceptance, strategic development, integration into coaching, and continuous follow-up to monitor progress and aid adjustments.</p>2024-07-12T00:00:00+02:00Copyright (c) 2024 Anders Norénhttps://ecp.ep.liu.se/index.php/linhac/article/view/1036Evaluating Space Creation in the National Hockey League using Puck and Player Tracking Data2024-07-12T13:39:14+02:00Hassaan Inayataliep@ep.liu.seTimothy Chanep@ep.liu.se<p>Star ice hockey players are often described as having a magnetic pull, with the ability to draw out opponents and generate dangerous opportunities for their linemates in the space left vacant by defenders. Using spatiotemporal Puck and Player Tracking (PPT) data, we develop a quantitative approach to measure how players create space while in possession of the puck, termed On-Puck Space Generation (OPSG). The benefits of our model’s approach include its decomposition into three components: 1) Rink Control, the probability of controlling the puck at a given location; 2) Rink Value, the probability of scoring from a given location; and 3) Transition Probability, the probability that the next on-puck event will occur at a given location. Preliminary results of our metric show that players who achieve high levels of OPSG are more likely to lead their team in goals, assists and points. Our model can be used to analyze which players are in positions of danger, identify instances in which an individual created valuable space for their teammates, and understand which teams are best at generating space.</p>2024-07-12T00:00:00+02:00Copyright (c) 2024 Hassaan Inayatali,Timothy Chanhttps://ecp.ep.liu.se/index.php/linhac/article/view/1037Examining the Role of Hockey Leadership to Foster Inclusive Coaching Practices: Discussions from Atlantic Canada2024-07-12T13:43:57+02:00Lynn LeVatteLynn_levatte@cbu.caChristina Phillipsc.phillips@mail.utoronto.caShaun RanniShaun_ranni@cbu.caSarah MacRaeSarah_macrae@cbu.caKristin O’RourkeKristin_o’rourke@cbu.ca<p>Coaching has been widely examined in the sport of ice hockey. Technical skill development, player management, and the ability to improve performance have been very notable areas of inquiry. As the critical roles of coaching leadership and communication become clearer, there is limited research available which explores the context of inclusive hockey coaching leadership to support more equitable practices. This paper will focus on specific data extracted from a previous study completed by the authors in which general hockey leadership skills and professional development were explored. This paper will present the outcomes of fostering inclusion and diversity from a coaching lens. Thirteen minor hockey coaches from Atlantic Canada (i.e., who are members of the Atlantic Hockey Group) participated in this qualitative study. Semi structured interviews were conducted online or in-person. A thematic analysis was used to explore data obtained from the interviews. Results revealed that coaches had limited communication training experience when working with diverse abilities, age groups, languages, genders, or cultures. Limited professional development specific to inclusive training was noted by participants. Our results demonstrated that various self-led leadership strategies were utilized to promote inclusive practices such as informal community-peer mentorship opportunities, and small group instructional sessions. Overall, the results give us insights into coaches’ experiences with inclusive leadership and highlight current gaps. During the conclusion, future recommendations for continued study, specifically within leadership training for diversity within ice hockey, are offered.</p>2024-07-12T00:00:00+02:00Copyright (c) 2024 Lynn LeVatte, Christina Phillips, Shaun Ranni, Sarah MacRae, Kristin O’Rourkehttps://ecp.ep.liu.se/index.php/linhac/article/view/1038Characterizing Playing Styles for Ice Hockey Players2024-07-12T13:50:43+02:00Anton Olivestamep@ep.liu.seAxel Rosendahlep@ep.liu.seErik Wilderothep@ep.liu.seNiklas Carlssonep@ep.liu.sePatrick Lambrixep@ep.liu.se<p>Although analytics is being used in, e.g., the evaluation of players and scouting, it is still challenging to quantify skills and playing styles of players. Such information is important for roster creation and scouting, where teams want to find players that have a playing style that fits within the team, as well as for game preparation to understand the playing style of opponents. In this paper we use player vectors to characterize a player’s playing style. The player vectors contain representations of skills that are computed from game event data. Further, we use fuzzy clustering on the vectors to generate five types of defender playing styles and five types of forward playing styles. For these types, we show the typical skill levels and players with similar styles.</p>2024-07-12T00:00:00+02:00Copyright (c) 2024 Anton Olivestam, Axel Rosendahl, Erik Wilderoth, Niklas Carlsson, Patrick Lambrixhttps://ecp.ep.liu.se/index.php/linhac/article/view/1039Puck Possessions and Team Success in the NHL2024-07-12T13:55:41+02:00Miles Pitassiep@ep.liu.seTim Brechtep@ep.liu.seMingyue Xieep@ep.liu.se<p>This paper investigates the relationship between puck possession and team success in the NHL, focusing on the games played during the 2023-2024 regular season (up to the All-Star break). The analysis first reveals a moderate correlation (r = 0.56) between average team possession percentage and Average Goal Differential (Avg. GoalDiff). Next, we introduce Average Offensive Zone Possession Time Differential (Avg. OZPTD) as a key metric, defined as the difference between a team’s offensive zone possession time and that of their opponents. We find a strong correlation (r = 0.77) between Avg. OZPTD and Avg. GoalDiff, thereby highlighting its relevance in assessing team performance. Our analysis confirms OZPTD’s stability, discriminatory power, and independence from existing metrics like Shot Attempt Percentage (SAT%), also known as Corsi. Additionally, we detail a comprehensive methodology for processing and cleaning possession data sourced from the NHL. This methodology underpins our findings and facilitates future research involving player and team possession data.</p>2024-07-12T00:00:00+02:00Copyright (c) 2024 Miles Pitassi, Tim Brecht, Mingyue Xie