SPORTS ANALYTICS EXAMINATION QUESTIONS AND
CORRECT ANSWER WITH EXPLANATION GRADED A+
STUDY GUIDE SOUTHERN NEW HAMPSHIRE UNIVERSITY
1. Sports analytics refers to:
A. The use of data to analyze sports performance and decisions
B. Playing sports
C. Refereeing games
D. Stadium construction
Answer: A
Rationale: It focuses on data-driven sports decisions.
2. The main purpose of sports analytics is to:
A. Improve performance and decision-making
B. Increase ticket sales only
C. Build stadiums
D. Replace coaches
Answer: A
Rationale: Analytics improves outcomes.
3. Data in sports analytics comes from:
A. Matches, training, and sensors
B. Only fans
C. Only referees
D. Only stadiums
Answer: A
Rationale: Multiple sources generate data.
4. Performance analytics focuses on:
A. Measuring athlete and team performance
B. Ticket sales
C. Stadium design
D. Refereeing decisions
Answer: A
Rationale: It evaluates performance.
5. Descriptive analytics answers:
A. What happened
, B. What will happen
C. Why it happened
D. How to build stadiums
Answer: A
Rationale: Descriptive = past data.
6. Predictive analytics answers:
A. What is likely to happen
B. What happened
C. Stadium design
D. Referee decisions
Answer: A
Rationale: Predictive forecasts outcomes.
7. Prescriptive analytics answers:
A. What should be done
B. What happened
C. Who played
D. Where stadium is
Answer: A
Rationale: Prescriptive gives recommendations.
8. Key performance indicators (KPIs) in sports measure:
A. Performance success metrics
B. Ticket prices
C. Stadium size
D. Referee count
Answer: A
Rationale: KPIs measure performance.
9. Player tracking uses:
A. GPS and sensors
B. Paper records
C. Fans
D. Coaches only
Answer: A
Rationale: Technology tracks movement.
10. Sports data analytics helps coaches to:
A. Make better tactical decisions
, B. Build stadiums
C. Sell tickets
D. Referee games
Answer: A
Rationale: Data improves coaching.
11. Big data in sports refers to:
A. Large and complex datasets
B. Small records only
C. Stadium data only
D. Referee notes only
Answer: A
Rationale: Big data is large-scale.
12. Data visualization is used to:
A. Present data in charts and graphs
B. Play games
C. Build stadiums
D. Referee matches
Answer: A
Rationale: Visualization simplifies data.
13. A dashboard in sports analytics is:
A. A real-time performance display
B. Stadium control room
C. Ticket system
D. Referee tool
Answer: A
Rationale: Dashboards show metrics.
14. Match analysis focuses on:
A. Breaking down game performance
B. Ticket sales
C. Stadium design
D. Refereeing rules
Answer: A
Rationale: Analysis studies matches.
15. Video analysis helps to:
A. Review player movements
CORRECT ANSWER WITH EXPLANATION GRADED A+
STUDY GUIDE SOUTHERN NEW HAMPSHIRE UNIVERSITY
1. Sports analytics refers to:
A. The use of data to analyze sports performance and decisions
B. Playing sports
C. Refereeing games
D. Stadium construction
Answer: A
Rationale: It focuses on data-driven sports decisions.
2. The main purpose of sports analytics is to:
A. Improve performance and decision-making
B. Increase ticket sales only
C. Build stadiums
D. Replace coaches
Answer: A
Rationale: Analytics improves outcomes.
3. Data in sports analytics comes from:
A. Matches, training, and sensors
B. Only fans
C. Only referees
D. Only stadiums
Answer: A
Rationale: Multiple sources generate data.
4. Performance analytics focuses on:
A. Measuring athlete and team performance
B. Ticket sales
C. Stadium design
D. Refereeing decisions
Answer: A
Rationale: It evaluates performance.
5. Descriptive analytics answers:
A. What happened
, B. What will happen
C. Why it happened
D. How to build stadiums
Answer: A
Rationale: Descriptive = past data.
6. Predictive analytics answers:
A. What is likely to happen
B. What happened
C. Stadium design
D. Referee decisions
Answer: A
Rationale: Predictive forecasts outcomes.
7. Prescriptive analytics answers:
A. What should be done
B. What happened
C. Who played
D. Where stadium is
Answer: A
Rationale: Prescriptive gives recommendations.
8. Key performance indicators (KPIs) in sports measure:
A. Performance success metrics
B. Ticket prices
C. Stadium size
D. Referee count
Answer: A
Rationale: KPIs measure performance.
9. Player tracking uses:
A. GPS and sensors
B. Paper records
C. Fans
D. Coaches only
Answer: A
Rationale: Technology tracks movement.
10. Sports data analytics helps coaches to:
A. Make better tactical decisions
, B. Build stadiums
C. Sell tickets
D. Referee games
Answer: A
Rationale: Data improves coaching.
11. Big data in sports refers to:
A. Large and complex datasets
B. Small records only
C. Stadium data only
D. Referee notes only
Answer: A
Rationale: Big data is large-scale.
12. Data visualization is used to:
A. Present data in charts and graphs
B. Play games
C. Build stadiums
D. Referee matches
Answer: A
Rationale: Visualization simplifies data.
13. A dashboard in sports analytics is:
A. A real-time performance display
B. Stadium control room
C. Ticket system
D. Referee tool
Answer: A
Rationale: Dashboards show metrics.
14. Match analysis focuses on:
A. Breaking down game performance
B. Ticket sales
C. Stadium design
D. Refereeing rules
Answer: A
Rationale: Analysis studies matches.
15. Video analysis helps to:
A. Review player movements
