Chapter 28 Exercises: Career Paths in Sports Analytics

Overview

These exercises guide you through practical career development activities. Unlike technical exercises in previous chapters, these focus on self-assessment, planning, portfolio building, and professional development.

Level 1: Self-Assessment and Planning

Exercise 1.1: Skills Inventory

Objective: Create an honest assessment of your current skills.

Task: Rate yourself on each skill using this scale: - 1 = No experience - 2 = Basic understanding - 3 = Can complete tasks with guidance - 4 = Proficient; can work independently - 5 = Expert; can teach others

Technical Skills:

Domain Knowledge:

Soft Skills:

Analysis: 1. What are your top 3 strengths? 2. What are your 3 biggest skill gaps for your target role? 3. Create a 90-day plan to address your most critical gap.

Exercise 1.2: Target Role Definition

Objective: Clearly define your target role and organization type.

Task: Answer these questions thoughtfully.

Part A: Role Exploration

Research 5 real job postings in sports analytics. For each: - Job title - Organization - Required skills - Preferred skills - Salary (if listed) - What attracts you to this role?

Part B: Your Ideal Role

Describe your ideal role in 5 years:

1. Job title:
2. Organization type (team, media, tech, etc.):
3. Sport/league focus:
4. Day-to-day responsibilities:
5. Key stakeholders you'd work with:
6. Impact you'd have:
7. Compensation target:

Part C: Gap Analysis

Compare your current skills (Exercise 1.1) to your target role requirements:

Part D: Path Planning

Create a timeline with milestones: - 6 months: - 1 year: - 2 years: - 5 years:

Exercise 1.3: Career Narrative

Objective: Develop your professional story.

Task: Write the following in your own voice.

Your Story (150-200 words): Write a narrative that explains your journey to sports analytics. Include: - What sparked your interest - Key experiences that shaped you - Why you're passionate about this field - What you want to accomplish

Elevator Pitch (30 seconds): Condense your story to 30 seconds. Practice delivering it naturally.

LinkedIn Summary (100-150 words): Write a professional summary for your LinkedIn profile.

Application Letter Opening (2-3 sentences): Write a compelling opening paragraph for a cover letter to your dream organization.

Level 2: Portfolio Development

Exercise 2.1: Portfolio Project Planning

Objective: Plan three portfolio projects that demonstrate your capabilities.

Task: Design portfolio projects using this template.

Project 1: Data Analysis Project

Project 2: Model Building Project

[Use same template]

Project 3: Visualization/Dashboard Project

[Use same template]

Portfolio Strategy: 1. How do these three projects complement each other? 2. What skills are demonstrated across all three? 3. What's missing that you should add in future projects?

Exercise 2.2: Project Execution

Objective: Complete one portfolio project end-to-end.

Task: Execute one of the projects planned in Exercise 2.1.

Requirements: - Clean, documented code in GitHub repository - README file explaining project context and methodology - Written analysis (blog post or report format) - At least 3 visualizations - Clear conclusions with actionable insights

Evaluation Rubric:

Submission: Share link to GitHub repository and blog post.

Exercise 2.3: Portfolio Presentation

Objective: Practice presenting your work professionally.

Task: Create a presentation of your portfolio project.

Requirements: - 5-7 minute presentation - Maximum 10 slides - Assume audience includes both technical and non-technical members - Include: question, approach, key findings, implications

Presentation Structure: 1. Hook (30 seconds): Why should they care? 2. Question (30 seconds): What did you investigate? 3. Approach (1 minute): How did you analyze it? 4. Key Findings (2 minutes): What did you discover? 5. Implications (1 minute): What does it mean for decisions? 6. Conclusion (30 seconds): Summary and next steps

Practice: Record yourself delivering the presentation. Watch it back and identify areas for improvement.

Level 3: Professional Development

Exercise 3.1: Network Mapping and Outreach

Objective: Build your professional network strategically.

Task: Create and execute a networking plan.

Part A: Network Map

List 15 people you'd like to connect with:

Categories to include: - 3 people at your target organizations - 3 people in your target role (different orgs) - 3 industry thought leaders - 3 peers on similar career paths - 3 people who could be mentors

Part B: Outreach Template

Write a template for cold outreach:

Subject line: Body (3-4 sentences max): Call to action:

Part C: Execute

Reach out to at least 5 people this week. Track responses and follow-ups.

Exercise 3.2: Informational Interview

Objective: Learn from someone working in your target field.

Task: Conduct an informational interview.

Preparation: 1. Identify target interviewee 2. Research their background thoroughly 3. Prepare 10 thoughtful questions

Sample Questions: - How did you break into sports analytics? - What does a typical day/week look like? - What skills have been most valuable? - What do you wish you knew when starting? - What trends do you see in the industry? - What advice would you give someone in my position? - Are there others you'd recommend I speak with?

Post-Interview: - Send thank you note within 24 hours - Write summary of key insights - Follow up on any referrals - Connect on LinkedIn if not already

Deliverable: Write a 1-page summary of insights from your interview.

Exercise 3.3: Conference / Community Participation

Objective: Engage with the sports analytics community.

Task: Actively participate in the community.

Options (complete at least 2):

1. Online Community Engagement: - Follow 20 sports analytics professionals on Twitter/X - Engage meaningfully with 5 posts per week for a month - Share your own analysis at least once

2. Conference Participation: - Attend a sports analytics conference (virtual or in-person) - Connect with at least 5 new people - Write up 3 key takeaways

3. Local Meetup: - Find or create a local sports analytics meetup - Present your work or facilitate a discussion - Exchange contact info with attendees

4. Open Source Contribution: - Contribute to a sports analytics open source project - This could be code, documentation, or bug reports - Engage with project maintainers

Deliverable: Document your participation and what you learned.

Level 4: Application and Interview Preparation

Exercise 4.1: Application Materials

Objective: Create polished application materials.

Task: Develop a complete application package.

Resume: - One page maximum - Tailored to sports analytics - Quantify impact where possible - Include portfolio links - Have 3 people review

Cover Letter Template: - Paragraph 1: Hook + specific interest in organization - Paragraph 2: Relevant skills and experience - Paragraph 3: Portfolio highlight with results - Paragraph 4: Closing with call to action

Portfolio Summary: Create a one-page document highlighting: - 3 best projects with brief descriptions - Skills demonstrated - Links to full projects - Contact information

LinkedIn Profile: - Professional photo - Compelling headline - Complete summary - Skills section optimized - Portfolio links in featured section

Exercise 4.2: Technical Interview Preparation

Objective: Prepare for technical interview questions.

Task: Prepare and practice responses.

Statistics Questions: 1. Explain p-values to a non-statistician 2. What is the bias-variance tradeoff? 3. When would you use logistic vs. linear regression? 4. How do you evaluate a classification model? 5. What is overfitting and how do you prevent it?

Sports Analytics Questions: 1. Explain EPA to a coach 2. How would you build a win probability model? 3. What factors should go into fourth-down decisions? 4. How would you evaluate quarterback performance beyond basic stats? 5. What's wrong with traditional stats like rushing yards?

Coding Practice: Complete these exercises in Python: 1. Calculate EPA for a set of plays 2. Build a simple logistic regression model 3. Create a visualization comparing team performance 4. Write SQL queries to aggregate play-by-play data 5. Clean and merge datasets from different sources

Time yourself: Can you complete each in 15-20 minutes?

Exercise 4.3: Case Study Practice

Objective: Practice solving case studies under time pressure.

Task: Complete timed case studies.

Case Study 1 (30 minutes): You're given play-by-play data from an upcoming opponent. The defensive coordinator asks: "What are their tendencies on third down?"

Approach: - What data would you need? - What analysis would you perform? - How would you present findings?

Case Study 2 (30 minutes): It's 4th and 2 at the opponent's 35-yard line, tied game, 3 minutes left. The head coach asks for your recommendation.

Approach: - What factors would you consider? - How would you calculate expected value? - How would you communicate your recommendation?

Case Study 3 (45 minutes): You're given a dataset of quarterback performance. Leadership asks: "Who should we target in free agency?"

Approach: - How would you frame the analysis? - What metrics would you use? - How would you present recommendations?

Deliverable: Write up your approach for each case study.

Exercise 4.4: Behavioral Interview Preparation

Objective: Prepare compelling behavioral interview responses.

Task: Develop STAR responses for common questions.

STAR Format: - Situation: Set the context - Task: Describe your responsibility - Action: Explain what you did - Result: Share the outcome

Prepare responses for:

1. "Tell me about a time you had to communicate complex analysis to a non-technical audience."

2. "Describe a project where your initial approach didn't work. How did you adapt?"

3. "Give an example of when you had to work with incomplete or messy data."

4. "Tell me about a time you disagreed with a stakeholder. How did you handle it?"

5. "Describe your most impactful analytical project."

Practice: Have someone interview you using these questions. Record if possible.

Capstone Exercise: Career Launch Plan

Objective: Create a comprehensive career launch plan.

Deliverables:

1. Self-Assessment Summary (1 page): - Current strengths and gaps - Target role and timeline

2. Portfolio (3+ projects): - GitHub repository - Blog posts or write-ups - Presentation materials

3. Application Materials: - Polished resume - Cover letter template - LinkedIn profile

4. Network Development Plan: - Target connections - Outreach tracking - Community involvement

5. Interview Preparation: - Technical question responses - Case study practice documentation - Behavioral interview responses

6. 90-Day Action Plan: - Specific goals and milestones - Weekly actions - Success metrics

Timeline: Complete over 2-3 months, with regular check-ins on progress.

Reflection Questions

After completing these exercises, reflect on:

1. What surprised you about the self-assessment?
2. Which portfolio project are you most proud of?
3. What did you learn from networking activities?
4. Where do you feel most confident for interviews?
5. What gaps remain in your preparation?
6. What's your single most important next step?

Resources

• Resume templates: resume.io, Canva
• Portfolio inspiration: GitHub, Kaggle, Open Source Football
• Interview practice: Pramp, interviewing.io
• Community: Sports Analytics Society, Twitter/X
• Job listings: TeamWork Online, LinkedIn