Chapter 28 Quiz: Building an Analytics Department

Instructions

Answer all 25 questions. Each question is worth 4 points for a total of 100 points. Select the single best answer for each multiple-choice question. Short-answer questions require concise responses of 2-4 sentences.

Question 1

Which organizational model is best suited for a multi-club ownership group like City Football Group?

A) Embedded within Football Operations B) Centralized Analytics Unit reporting to club CEO C) Multi-Club / Group Model with centralized services and local liaisons D) Outsourced to a third-party analytics consultancy

Question 2

According to the budget allocation framework in Section 28.1.4, what is the approximate recommended proportion of total analytics budget allocated to personnel costs?

A) 35% B) 45% C) 55% D) 70%

Question 3

A club at Maturity Stage 2 (Foundational) would most likely have which of the following characteristics?

A) A single analyst using Excel, responding to ad-hoc coaching requests B) 3-5 dedicated staff with established data pipelines and basic dashboards C) 6-12 people including data scientists building custom models D) A 25+ person team with proprietary data collection systems

Question 4

Which role should typically be the FIRST hire when building an analytics department from scratch?

A) Data Scientist B) Data Engineer C) Head of Analytics D) Video Analyst

Question 5 (Short Answer)

Explain what a "T-shaped" competency profile means in the context of analytics hiring, and why it is preferable to deep specialization alone.

Question 6

In the technology stack described in Section 28.3.1, which layer would Tableau, Power BI, or Streamlit belong to?

A) Layer 1: Data Sources B) Layer 2: Data Infrastructure C) Layer 3: Analytics Tools D) Layer 4: Delivery and Communication

Question 7

According to the build-vs-buy framework, a club should generally build in-house when:

A) Commercial options are available and affordable B) The in-house solution offers a competitive advantage that justifies development and maintenance costs C) The club has a single developer who wants to build custom tools D) Building is always cheaper than buying in the long run

Question 8

Which of the following is NOT listed as a criterion in the data provider evaluation framework?

A) Coverage of relevant leagues B) Data granularity C) Provider company stock price D) API quality

Question 9

In the matchday analysis workflow, opponent analysis typically begins on which day relative to the match?

A) Day -6 (six days before) B) Day -5 (five days before) C) Day -3 (three days before) D) Day -1 (day before)

Question 10 (Short Answer)

Describe three key areas of routine analytics work that should be prioritized for automation, and explain why automation in these areas creates value.

Question 11

What percentage of departmental capacity should ideally be allocated to Tier 3 (research and development) work?

A) 5-10% B) 10-15% C) 20-30% D) 40-50%

Question 12

Which stakeholder relationship is described as "the single most important determinant of analytics effectiveness"?

A) The relationship with the club CEO B) The relationship with the ownership group C) The relationship with the coaching staff D) The relationship with data providers

Question 13

Which of the following is the correct order for presenting analysis to non-technical audiences?

A) Methodology, then results, then conclusion B) Context, then data exploration, then finding C) Conclusion first, then supporting evidence D) Raw data, then analysis, then interpretation

Question 14 (Short Answer)

Explain the "So What?" test framework and list its four components.

Question 15

A coaching staff member says: "I've been coaching for 20 years. No spreadsheet can tell me what I already know from watching the game." Which source of resistance does this represent?

A) Threat perception B) Complexity aversion C) Cultural inertia and valid skepticism D) Past experience with failed analytics

Question 16

The primary reason measuring analytics ROI is difficult is:

A) Analytics departments are too small to have measurable impact B) Attribution is challenging because multiple factors influence outcomes simultaneously C) Clubs do not keep financial records D) Analytics has no impact on sporting performance

Question 17

In the financial ROI formula for analytics, which of the following components are included in the numerator?

A) Revenue Gains + Cost Savings - Analytics Investment B) Revenue Gains only C) Analytics Investment + Cost Savings D) Revenue Gains + Cost Savings + Analytics Investment

Question 18

The "Points Above Replacement" (PAR) model for analytics draws its conceptual inspiration from which sport?

A) Basketball (NBA) B) Cricket (IPL) C) Baseball (MLB) D) American Football (NFL)

Question 19 (Short Answer)

Describe two methods for estimating the financial impact of an analytics department's contribution to recruitment decisions.

Question 20

Which KPI category would "average turnaround time for analysis requests" fall under?

A) Output KPIs B) Outcome KPIs C) Process KPIs D) People KPIs

Question 21

According to the case studies in Section 28.7, which common success factor appears across ALL clubs that have successfully built analytics operations?

A) Hiring former professional players as analysts B) Ownership commitment to analytics C) Using exclusively open-source technology D) Having the largest analytics budget in their league

Question 22

FC Midtjylland's analytics approach was particularly notable for its specialization in:

A) Tracking data analysis B) Machine learning for injury prediction C) Set-piece analysis and optimization D) Real-time in-match tactical adjustments

Question 23 (Short Answer)

Explain why physical presence (attending training, traveling with the team) matters for analytics staff, beyond the analytical work itself.

Question 24

The long-term value creation formula for analytics departments uses which financial concept to capture compounding benefits over time?

A) Internal Rate of Return (IRR) B) Net Present Value (NPV) C) Earnings Before Interest and Tax (EBIT) D) Return on Assets (ROA)

Question 25

A club wants to protect its analytics department from being dismantled when a new manager arrives. Which organizational change would MOST improve resilience?

A) Move the department to report to the CEO or sporting director instead of the head coach B) Give all analysts multi-year contracts with large termination clauses C) Have analysts avoid building relationships with coaching staff D) Keep the analytics department's work confidential from the coaching staff

Answer Key

Question 1: C --- The Multi-Club / Group Model provides centralized services with local adaptation, which is specifically designed for multi-club ownership structures.

Question 2: C --- The chapter states $B_{\text{personnel}} \approx 0.55 \cdot B_{\text{total}}$, making 55% the correct answer.

Question 3: B --- Stage 2 (Foundational) is characterized by 3-5 dedicated roles, established data pipelines from providers, and basic dashboards.

Question 4: C --- The Head of Analytics should be the first hire to establish the vision, credibility, and strategic direction for the department.

Question 5: A T-shaped competency profile means having deep expertise in one primary domain (the vertical bar) combined with working knowledge across several adjacent areas (the horizontal bar). This is preferable to pure specialization because analytics in football requires integrating technical skills with football knowledge, communication ability, and cross-functional collaboration. An analyst who can only code but cannot explain findings to coaches, or who understands football but cannot build models, will be less effective than one with breadth across both domains.

Question 6: D --- Dashboarding and visualization tools like Tableau, Power BI, and Streamlit are classified under Layer 4: Delivery and Communication.

Question 7: B --- The build decision is justified when the competitive advantage gained exceeds the total development and maintenance costs relative to the cost of buying.

Question 8: C --- The seven criteria listed are: Coverage, Granularity, Timeliness, Accuracy, API quality, Cost, and Exclusivity. Provider stock price is not a relevant evaluation criterion.

Question 9: B --- According to the matchday cycle, opponent analysis begins on Day -5 (five days before the match).

Question 10: Three key areas for automation are: (1) Data ingestion --- scheduled pulls from provider APIs save hours of manual downloading and formatting, ensuring data is always current. (2) Report generation --- templated post-match and weekly reports can be automatically populated with updated statistics, freeing analysts for higher-value interpretive work. (3) Dashboard updates --- automatic data refresh ensures stakeholders always have access to current information without requiring analyst intervention. Automation in these areas creates value by redirecting analyst time from routine tasks to creative, high-impact analysis.

Question 11: C --- The chapter recommends allocating at least 20-30% of capacity to Tier 3 (R&D) work.

Question 12: C --- The chapter states that "the relationship between the analytics department and the coaching staff is the single most important determinant of analytics effectiveness."

Question 13: C --- The chapter advises leading with the conclusion first, then providing supporting evidence, reversing the academic convention of methodology-then-results.

Question 14: The "So What?" test has four components that every analysis must answer before delivery: (1) "So What?" --- why does this finding matter? (2) "Now What?" --- what action should be taken as a result? (3) "Says Who?" --- what evidence supports this conclusion? (4) "How Confident?" --- what is the uncertainty around this finding? If all four cannot be clearly answered, the analysis is not ready for delivery.

Question 15: C --- This combines cultural inertia ("I've always done it this way") with valid skepticism ("can data really capture what I see?"). The coach's experience-based confidence reflects both resistance to change and a legitimate question about data's limitations.

Question 16: B --- The primary challenge is attribution: when outcomes result from the combined effects of analytics, coaching, player talent, luck, and other factors, isolating analytics' specific contribution is inherently difficult.

Question 17: A --- The formula is: $\text{ROI} = \frac{\text{Revenue Gains} + \text{Cost Savings} - \text{Analytics Investment}}{\text{Analytics Investment}} \times 100\%$.

Question 18: C --- The Points Above Replacement concept is explicitly described as borrowing from baseball's Wins Above Replacement (WAR).

Question 19: Two methods are: (1) Transfer profit comparison --- compare the actual transfer profit generated by analytically-identified signings versus the club's historical average transfer outcomes, attributing the differential (weighted by analytics influence) as financial impact. (2) Salary optimization / market value modeling --- estimate cost savings by comparing what the club paid for analytically-vetted signings versus estimated market rates, capturing situations where data identified undervalued players before the broader market.

Question 20: C --- Average turnaround time for analysis requests is a Process KPI, measuring the efficiency of the department's operational workflows.

Question 21: B --- Ownership commitment to analytics is identified as a common factor across all successful case studies (FCM, Manchester City/CFG, Brentford, Liverpool).

Question 22: C --- FC Midtjylland is specifically noted for their set-piece specialization driven by statistical analysis.

Question 23: Physical presence matters because it builds trust and relationships with coaching staff, which is essential for analytics to influence decisions. Being present at training sessions helps analysts develop contextual understanding of tactical decisions, player dynamics, and team culture that cannot be gained from data alone. It also signals commitment and reduces the perception that analysts are disconnected "ivory tower" figures, making coaches more receptive to analytical insights.

Question 24: B --- The chapter uses the Net Present Value (NPV) formulation to capture the compounding benefits of sustained analytics investment over time.

Question 25: A --- Moving the reporting line from the head coach to the CEO or sporting director provides structural resilience against managerial changes, as the department's existence and budget are not tied to any single coach's preferences.