Ulrik Brandes: Catalogue data in Spring Semester 2022 |
| Name | Prof. Dr. Ulrik Brandes |
| Name variants | Ulrik Brandes |
| Field | Social Networks |
| Address | Professur für Soziale Netzwerke ETH Zürich, WEP J 14 Weinbergstr.109 8006 Zürich SWITZERLAND |
| Telephone | +41 44 632 21 96 |
| ubrandes@ethz.ch | |
| Department | Humanities, Social and Political Sciences |
| Relationship | Full Professor |
| Number | Title | ECTS | Hours | Lecturers | |
|---|---|---|---|---|---|
| 851-0252-04L | Behavioral Studies Colloquium  | 0 credits | 2K | E. Stern, U. Brandes, D. Helbing, C. Hölscher, M. Kapur, C. Stadtfeld | |
| Abstract | This colloquium offers an opportunity to discuss recent and ongoing research and scientific ideas in the behavioral sciences, both at the micro- and macro-levels of cognitive, behavioral and social science. The colloquium features invited presentations from internal and external researchers as well as presentations of doctoral students close to submitting their dissertation research plan. | ||||
| Learning objective | Participants are informed about recent and ongoing research in different branches of the behavioral sciences. Presenting doctoral students obtain feedback on their dissertation research plan. | ||||
| Content | This colloquium offers an opportunity to discuss recent and ongoing research and scientific ideas in the behavioral sciences, both at the micro- and macro-levels of cognitive, behavioral and social science. It covers a broad range of areas, including theoretical as well as empirical research in social psychology, research on higher education, sociology, modeling and simulation in sociology, decision theory and behavioral game theory, economics, research on learning and instruction, cognitive psychology and cognitive science. The colloquium features invited presentations from internal and external researchers as well as presentations of doctoral students close to submitting their dissertation research plan. | ||||
| Prerequisites / Notice | Doctoral students in D-GESS can obtain 1 credit point for presenting their research in the colloquium. | ||||
| 851-0557-00L | Soccer Analytics Students should be comfortable with mathematical derivations and scripting for data analysis. | 3 credits | 2G | U. Brandes | |
| Abstract | Soccer analytics refers to the use of data in tactical decision-making, strategic planning, and fan engagement in the context of association football. This course is first and foremost about data, problems, and methods. They are discussed, however, with reference to the broader context of measurement and data science in sports and society. | ||||
| Learning objective | Students gain insight into the role of data science in professional football. They learn about attempts to capture aspects of the beautiful game in observable data to inform tactical, strategic, and communicative decision-making. By appreciating difficulties that arise even in activities with highly regulated interactions such as team sports, they reflect on the use of data science in the study of collective behavior. | ||||
| Content | The content is organized into lectures with time for reflective discussions and a practical part, in which small teams use free software tools to gain first-hand experience in working with sports data. The following is a tentative overview of course contents, with exemplary aspects listed for each topic. A major element for each of the analytic topics are various forms of visualization such as timelines, step plots, scatterplots, density maps, shot maps, and networks. 1. Introduction - history of measurement and analytics in sports - laws of the game: equipment, space, time, players - data: master, match, event, tracking; sources, availability, uses 2. Scores - competitions: tournaments, leagues - ranking teams: coefficients, latent strengths - predicting results: odds, statistics 3. Individual Actions - running: heatmaps, pitch control - passing: packing, line breaking, crosses - shooting: expected goals & co. 4. Match Phases - set pieces, penalties, free kicks, etc. - possession, location, organization 5. Collective Behavior - formations: spatial distributions, proximity networks - attacking: possession value, positional play, passing networks - defending: (counter-)pressure, marking networks - team composition: plus/minus, interactions 6. Environment - recruitment: player profiles, transfer market, agents, salaries - governance: clubs, leagues, associations, confederations - engagement: attendance, merchandise, social media - simulation: robocup, esports, fantasy football - betting market Fair warning: This is the first edition of the course and it may be adjusted depending on interest and feedback. | ||||
| Prerequisites / Notice | Credits are awarded for active participation and a group project. To get the most out of the project, basic knowledge of programming languages such as python or R is advisable. Whether the course is offered again will be decided at the end of the semester. | ||||
| 851-0586-03L | Applied Network Science: Sports Networks  Number of participant limited to 20 | 3 credits | 2S | U. Brandes | |
| Abstract | We study applications of network science methods, this time in the domain of sports. Topics are selected for diversity in research questions and techniques with applications such as passing networks, team rankings, and career trajectories. Student teams present results from the recent literature, possibly with replication, in a mini-conference on the day before the UEFA Champions League Final. | ||||
| Learning objective | Network science as a paradigm is entering domains from engineering to the humantities but application is tricky. By examples from recent research on sports, sports administration, and the sociology of sports, students learn to appreciate that, and how, context matters. They will be able to assess the appropriateness of approaches for substantive research problems, and especially when and why quantitative approaches are or are not suitable. | ||||
| Literature | Original research articles will be introduced in the first session. General introduction: Wäsche, Dickson, Woll & Brandes (2017). Social Network Analysis in Sport Research: An Emerging Paradigm. European Journal for Sport and Society 14(2):138-165. DOI: 10.1080/16138171.2017.1318198 | ||||
| 860-0045-00L | Applied Network Science: Sports Networks - Research Paper Permit by the lecturer is required. Students must be enrolled in the lecture 851-0586-03L Applied Network Science: Sports Networks. | 3 credits | 2A | U. Brandes | |
| Abstract | This is an activity course augmenting the topical project seminar 851- 0586-03 Applied Metwork Science with a research paper that combines the discussion of a result from the literature with work of their own (as conducted in the associated project seminar). Papers are cross-reviewed and revised before their final submission. | ||||
| Learning objective | Students practice collaborative academic writing and peer review. | ||||