Linköping Hockey Analytics Conference https://ecp.ep.liu.se/index.php/linhac <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> en-US Fri, 08 Sep 2023 00:00:00 +0200 OJS 3.3.0.16 http://blogs.law.harvard.edu/tech/rss 60 Professionalism & Leadership Development in Ice Hockey https://ecp.ep.liu.se/index.php/linhac/article/view/738 <p>This qualitative research study investigated the Social Emotional Learning training experiences of ice hockey coaches in Atlantic Canada. Social Emotional Learning (SEL) and leadership in sport is an emergent field which has been gaining attention on a national level. The purpose of this study was to examine various aspects of SEL within coaching leadership training of Canadian ice hockey coaches in Atlantic Canada. Minor hockey coaches (n=8) were recruited to participate in semi-structured interviews. Five questions pertaining to hockey coaching background, leadership training, communication, and SEL training experiences were posed to participants. Interviews were offered both in person or virtually as an option for convenience. Analysis of data suggested that clear expectations and effective communication with players and guardians were valuable aspects for relationship building. Limited professional development opportunities surrounding aspects of SEL were noted by participants, training provided was outdated in certain aspects, and current topics of inclusion, diversity, and culture. Future recommendations for continued study within the field of SEL within ice hockey are offered.</p> Lynn LeVatte, Christina Phillips, Kristin O'Rourke, Shaun Ranni Copyright (c) 2023 https://creativecommons.org/licenses/by/4.0 https://ecp.ep.liu.se/index.php/linhac/article/view/738 Fri, 08 Sep 2023 00:00:00 +0200 Analyzing Passing Metrics in Ice Hockey using Puck and Player Tracking Data https://ecp.ep.liu.se/index.php/linhac/article/view/739 <p>Traditional ice hockey statistics are inherently biased towards offensive events like goals, assists, and shots. However, successful teams in ice hockey require players with skills that may not be captured using traditional measures of performance. The adoption of puck and player tracking systems in the National Hockey League (NHL) has significantly increased the scope of possible metrics that can be obtained. In this paper, we compute recently proposed passing metrics from 1221 NHL games from the 2021-2022 season. We analyze the distributions of values obtained for each player for each metric to understand the variance between, and within, different positions. We find that forwards tend to complete fewer passes with smaller passing lanes, while defensemen pass to forwards significantly more than their defensive partners . Additionally, because these new metrics do not correlate well with traditional metrics (e.g., assists), we believe that they capture aspects of players’ abilities that may not appear on the game sheet.</p> David Radke, Jaxin Lu, Jackson Woloschuk, Tin Le, Daniel Radke, Charlie Liu, Tim Brecht Copyright (c) 2023 https://creativecommons.org/licenses/by/4.0 https://ecp.ep.liu.se/index.php/linhac/article/view/739 Fri, 08 Sep 2023 00:00:00 +0200 Simple and Practical Goal Importance Metrics for Ice Hockey https://ecp.ep.liu.se/index.php/linhac/article/view/740 <p>To capture that not all goals are of the same importance, a new performance metric called the Game Points Importance Value (GPIV) was recently proposed. While this metric takes into account the expected impact that a goal has on the outcome of a game based on the context when the goal was scored, it relies on a relatively fine-grained state space. To address this problem, this paper presents simplified and more practical variations of the GPIV metric. Motivated by our analysis of the relative importance of different dimensions of the state space, we present two metrics that capture the most important component(s) of GPIV. Our evaluation shows that the metrics are relatively stable and capture most of the relative differences between GPIV and traditional metrics (e.g., goals, assist, points, and +/-). These results suggest that these simple and practical metrics are intuitive, capture most of the desirable variations that GPIV captures, and that the value of a goal can be well estimated using GPIV data based on historic data.</p> Rasmus Säfvenberg, Niklas Carlsson, Patrick Lambrix Copyright (c) 2023 https://creativecommons.org/licenses/by/4.0 https://ecp.ep.liu.se/index.php/linhac/article/view/740 Fri, 08 Sep 2023 00:00:00 +0200 The Importance of Special Teams in Ice Hockey https://ecp.ep.liu.se/index.php/linhac/article/view/741 <p>This paper explores the significance of special teams, particularly powerplay, in ice hockey. Despite the commonly held perception of their importance, little research has examined the impact of powerplay and penalty kill performance on overall team success. The paper uses several seasons of NHL data to characterize goal-scoring and manpower opportunities, and perform analysis from several perspectives. The results indicate that individual even strength goals and powerplay goals have similar value, but the larger share of even strength goals scored over a season makes even strength play a more important contributor to team success. The paper also finds a high correlation between teams that perform above/below average during even strength and powerplay. This study provides insights into the dynamics of ice hockey gameplay and the role of special teams in determining team success.</p> Rasmus Säfvenberg, Mikael Svarén, Niklas Carlsson, Patrick Lambrix Copyright (c) 2023 https://creativecommons.org/licenses/by/4.0 https://ecp.ep.liu.se/index.php/linhac/article/view/741 Fri, 08 Sep 2023 00:00:00 +0200 Towards a real-time possession value framework in ice hockey https://ecp.ep.liu.se/index.php/linhac/article/view/737 <p>Measuring the individual performance of players is an important task in sports analytics. Traditional statistics-based approaches for evaluating hockey players fail to account for context and long-term impact. Recent advances in data gathering have enabled valuing possessions and actions directly to address these issues. This talk describes the implementation of the first real-time possession value framework for ice hockey.</p> Frans Murto Copyright (c) 2023 https://creativecommons.org/licenses/by/4.0 https://ecp.ep.liu.se/index.php/linhac/article/view/737 Fri, 08 Sep 2023 00:00:00 +0200