Study Guide

Objective

Having completed this study unit,

- You will understand sport organisation's need to exploit data, predict behaviours and extract valuable information for real-world insights.

- You will understand data analytics and their importance for sport´s businesses to develop a competitive edge.

- You will learn how sport businesses constantly strive to offer better products and services than their competitors and the techniques used to achieve progress.

- You will explore various data visualisations available and how to use them for analysis.

Competences: Proactive development Competence, Leadership and Management Competence

Content

Theme 1: Basics of sport business intelligence, data management and insight generation.
Theme 2: Fundamentals of applied quantitative sports research, statistics and insights.
Theme 3: Pursuing commercial value from data-driven management.
Theme 4: Data visualisation and dashboards

Location and time

Teaching is carried out mainly at the Rovaniemi campus autumn semester 2024 during weeks 36-45:
- 1st intensive on-campus study period 2.-4.9.
- 3 webinars on week 39, 41 & 43. Each webinar is approximately 60 minutes and scheduled for late afternoon.
- 2nd intensive on-campus study period 4.-6.11.
No distance learning possibility. Intensive on-campus periods are full day sessions taking place between 9am.-16pm.

Materials

Lecture materials, articles and exercises - will be provided in the beginning of the course and upon completion of the course.

Recommended course books are:

Green, F. 2021. Winning with data: CRM and analytics for the business of sports. Routledge.

Harrison, C.K. & Bukstein, S. 2017. Sport business analytics: using data to increase revenue and improve operational efficiency. Taylor & Francis.

Teaching methods

Teaching methods in the course follows combined face-to-face lectures and workshops organized on-campus as well as online learning methods where students participate in webinars and workshops via Zoom or equivalent platform.

When studying in the course, student demonstrates personal learning through individual assignments (written essays) in a form of pre-assignment and main course assignment. Pre-assignment and course assignment are presented in Moodle workspace. Additionally, students prepare a case study (group work) for a selected sport organization and deliver comprehensive presentations summarizing the course contents and learnings.

Students' learning is assessed through pre-assignment (10 %), individual course assignment (50 %), development assignment conducted in groups (30 %) and peer evaluation (10 %). Students can choose the target of their case study independently and groups have the possibility to get an assignment from a professional ice-hockey club playing in Liiga – top league of Finnish ice-hockey.

Evaluation scale

H-5

Assessment criteria, satisfactory (1)

Level 1
Sport Business Intelligence and Data Analytics:
You have a basic understanding of sport business intelligence and data analytics. The student displays a basic coverage for the required level but shows an attempt to address the subject. Significant gaps and errors but include >40% of the expected factual content.

Level 2
Sport Business Intelligence and Data Analytics:
You have a satisfactory understanding of sport business intelligence and data analytics. There may be gaps not developed at the appropriate level, but the overall standard of understanding is satisfactory.

Assessment criteria, good (3)

Level 3
Sport Business Intelligence and Data Analytics:
You know how to describe the relationship between sport intelligence and data analytics. You understand the importance of data and product and service development. You have a basic understanding to data visualisations. Good understanding of the material with coverage at the appropriate level. Some aspects may not be covered but this would be compensated by the overall quality.

Level 4
Sport Business Intelligence and Data Analytics:
You have a comprehensive understanding of sport intelligence and data analytics. You can expand importance of data and product and service development. You have a satisfactory understanding to data visualisations. Excellent coverage of the topic, focusing precisely on the set question. You also display a grasp of research and how to follow current sport trends.
The students understanding is articulated such that it contributes to the reader’s understanding. Depth and breadth of content is very good.

Assessment criteria, excellent (5)

Level 5
Sport Business Intelligence and Data Analytics:
You have a comprehensive understanding of sport intelligence and data analytics. You can expand importance of data and product and service development. You have a good understanding to data analysis and data visualisations.
Evidence of understanding is outstanding and completely demonstrates understanding of the topics covered. Depth and breadth of content is excellent.

Assessment methods and criteria

The assignments are introduced at the beginning of the course. Assessment is based on the process and actual skills and knowledge evaluation. All assignments must be done and passed to complete the study unit.

Plagiarism and use of references:
Please notice that in study unit assignment returns the plagiarism detection programs (for example Turnitin) will be used.

Also notice that you need to use Lapland UAS templates (essay, thesis, report etc) and writing instructions. Textual references must be done according to the given instructions.

Submitting assignments against given instructions may lead to failing and other possible consequences according to the Degree Regulations.