CPSS Key Performance Indicator Identification 5 — Questions and Answers
Question 1: Which data visualization method is most effective for communicating KPI trends to coaching staff on a weekly basis?
- Raw data tables exported from the database
- Traffic light dashboards with contextual thresholds (Correct answer)
- Detailed statistical reports with confidence intervals
- Individual athlete spreadsheets with all collected variables
Correct answer: Traffic light dashboards with contextual thresholds
Traffic light dashboards present KPI status against thresholds in an immediately interpretable format, enabling rapid coach decision-making.
Question 2: A sport scientist observes that an athlete's GPS high-speed running KPI remains stable while session RPE spikes. What is the most likely explanation?
- GPS unit malfunction causing underestimation of speed
- Increased perceived exertion not captured by external load metrics (Correct answer)
- The athlete has adapted to the training stimulus
- High-speed running thresholds are set too low
Correct answer: Increased perceived exertion not captured by external load metrics
Divergence between external load (GPS) and internal load (RPE) KPIs typically indicates the athlete is working harder physiologically or psychologically to achieve the same output.
Question 3: Which principle guides the recommended number of KPIs in a monitoring system to avoid data overload?
- Collect as many KPIs as technology allows for maximum coverage
- Select only 2-3 KPIs per performance domain, prioritizing actionability (Correct answer)
- Use only KPIs that can be automated without human scoring
- Standardize to the same KPI set used by national governing bodies
Correct answer: Select only 2-3 KPIs per performance domain, prioritizing actionability
Limiting KPIs to a small number of actionable, high-quality indicators per domain prevents cognitive overload and ensures each metric drives decisions.
Question 4: In Paralympic sport, which additional factor must be considered when identifying KPIs that is not typically required for able-bodied athletes?
- Classification category and impairment type affecting performance expression (Correct answer)
- Greater emphasis on psychological KPIs over physical ones
- Elimination of GPS-based external load monitoring
- Use of age-matched normative databases only
Correct answer: Classification category and impairment type affecting performance expression
Impairment type and sports classification fundamentally alter physiological and biomechanical performance expression, requiring KPIs to be classification-specific.
Question 5: Which scenario represents the BEST use of a leading KPI (predictor) versus a lagging KPI (outcome) in injury prevention?
- Using injury incidence rate to predict next season's performance
- Monitoring ACWR and jump asymmetry to intervene before injury occurs (Correct answer)
- Tracking days missed due to injury after the season ends
- Reporting medical costs as the primary prevention metric
Correct answer: Monitoring ACWR and jump asymmetry to intervene before injury occurs
ACWR and jump asymmetry are leading KPIs that signal elevated injury risk prospectively, enabling proactive intervention before injury occurs.
Question 6: A sport scientist is asked to benchmark an athlete's KPI performance. Which reference standard provides the most actionable context?
- General population norms from public health databases
- Position- and competition-level-matched athlete norms (Correct answer)
- Age-matched normative data from a different sport
- The athlete's own historical average from the previous year
Correct answer: Position- and competition-level-matched athlete norms
Position- and competition-level-matched norms provide the most relevant benchmark because they reflect the demands of the athlete's actual competitive context.
Question 7: Which statistical approach is recommended to establish individual KPI thresholds rather than relying on group-level norms?
- One-sample t-test against population mean
- Individual z-scores based on the athlete's own historical data (Correct answer)
- Pearson correlation with competition outcome
- Between-subjects ANOVA across the squad
Correct answer: Individual z-scores based on the athlete's own historical data
Using the athlete's own historical mean and standard deviation to compute individual z-scores accounts for inter-individual variability and personalizes threshold setting.
CPSS Key Performance Indicator Identification 5
Which data visualization method is most effective for communicating KPI trends to coaching staff on a weekly basis?