SPORT DATA ANALYTICS EXAMINATION QUESTIONS AND
CORRECT ANSWER WITH EXPLANATION GRADED A+
STUDY GUIDE SOUTHERN NEW HAMPSHIRE UNIVERSITY
1. Sport data analytics is the use of:
A. Data to improve sports performance and decisions
B. Stadium construction methods
C. Refereeing rules
D. Ticket printing systems
Answer: A
Rationale: Analytics uses data for performance insight.
2. The main purpose of sports analytics is to:
A. Improve decision-making in sport
B. Replace athletes
C. Build stadiums
D. Sell tickets only
Answer: A
Rationale: Data improves decisions.
3. Performance data in sports includes:
A. Player statistics and metrics
B. Stadium design
C. Ticket prices
D. Referee uniforms
Answer: A
Rationale: Performance data tracks athletes.
4. Descriptive analytics focuses on:
A. What has happened
B. What will happen
C. Why it happened only
D. Stadium design
Answer: A
Rationale: Descriptive explains past events.
5. Predictive analytics focuses on:
A. Forecasting future outcomes
, B. Past records only
C. Ticket sales
D. Stadium size
Answer: A
Rationale: Predictive uses models.
6. Prescriptive analytics suggests:
A. Best actions to take
B. Past performance
C. Refereeing decisions
D. Stadium design
Answer: A
Rationale: Prescriptive guides actions.
7. Data in sports comes from:
A. GPS, sensors, and match stats
B. Stadium walls
C. Ticket booths
D. Referees only
Answer: A
Rationale: Multiple data sources exist.
8. Big data refers to:
A. Large and complex datasets
B. Small reports
C. Referee notes
D. Ticket records only
Answer: A
Rationale: Big data is large-scale.
9. Player tracking systems monitor:
A. Movement and performance
B. Ticket sales
C. Stadium lights
D. Refereeing errors only
Answer: A
Rationale: Tracking measures movement.
10. Key Performance Indicators (KPIs) are:
A. Measurable performance metrics
, B. Stadium rules
C. Ticket systems
D. Referee decisions
Answer: A
Rationale: KPIs measure success.
11. Data visualization is used to:
A. Present data graphically
B. Build stadiums
C. Sell tickets
D. Referee games
Answer: A
Rationale: Visualization simplifies data.
12. A heat map shows:
A. Player movement intensity
B. Ticket sales
C. Stadium structure
D. Referee decisions
Answer: A
Rationale: Heat maps show activity.
13. GPS tracking in sports measures:
A. Player position and movement
B. Ticket sales
C. Stadium size
D. Referee actions
Answer: A
Rationale: GPS tracks movement.
14. Wearable technology collects:
A. Athlete performance data
B. Ticket information
C. Stadium data
D. Referee data only
Answer: A
Rationale: Wearables monitor athletes.
15. Data cleaning means:
A. Removing errors from data
CORRECT ANSWER WITH EXPLANATION GRADED A+
STUDY GUIDE SOUTHERN NEW HAMPSHIRE UNIVERSITY
1. Sport data analytics is the use of:
A. Data to improve sports performance and decisions
B. Stadium construction methods
C. Refereeing rules
D. Ticket printing systems
Answer: A
Rationale: Analytics uses data for performance insight.
2. The main purpose of sports analytics is to:
A. Improve decision-making in sport
B. Replace athletes
C. Build stadiums
D. Sell tickets only
Answer: A
Rationale: Data improves decisions.
3. Performance data in sports includes:
A. Player statistics and metrics
B. Stadium design
C. Ticket prices
D. Referee uniforms
Answer: A
Rationale: Performance data tracks athletes.
4. Descriptive analytics focuses on:
A. What has happened
B. What will happen
C. Why it happened only
D. Stadium design
Answer: A
Rationale: Descriptive explains past events.
5. Predictive analytics focuses on:
A. Forecasting future outcomes
, B. Past records only
C. Ticket sales
D. Stadium size
Answer: A
Rationale: Predictive uses models.
6. Prescriptive analytics suggests:
A. Best actions to take
B. Past performance
C. Refereeing decisions
D. Stadium design
Answer: A
Rationale: Prescriptive guides actions.
7. Data in sports comes from:
A. GPS, sensors, and match stats
B. Stadium walls
C. Ticket booths
D. Referees only
Answer: A
Rationale: Multiple data sources exist.
8. Big data refers to:
A. Large and complex datasets
B. Small reports
C. Referee notes
D. Ticket records only
Answer: A
Rationale: Big data is large-scale.
9. Player tracking systems monitor:
A. Movement and performance
B. Ticket sales
C. Stadium lights
D. Refereeing errors only
Answer: A
Rationale: Tracking measures movement.
10. Key Performance Indicators (KPIs) are:
A. Measurable performance metrics
, B. Stadium rules
C. Ticket systems
D. Referee decisions
Answer: A
Rationale: KPIs measure success.
11. Data visualization is used to:
A. Present data graphically
B. Build stadiums
C. Sell tickets
D. Referee games
Answer: A
Rationale: Visualization simplifies data.
12. A heat map shows:
A. Player movement intensity
B. Ticket sales
C. Stadium structure
D. Referee decisions
Answer: A
Rationale: Heat maps show activity.
13. GPS tracking in sports measures:
A. Player position and movement
B. Ticket sales
C. Stadium size
D. Referee actions
Answer: A
Rationale: GPS tracks movement.
14. Wearable technology collects:
A. Athlete performance data
B. Ticket information
C. Stadium data
D. Referee data only
Answer: A
Rationale: Wearables monitor athletes.
15. Data cleaning means:
A. Removing errors from data
