Chapter 26 Quiz

Multiple Choice Questions

Question 1. What is the most common injury type in professional soccer, accounting for approximately one-third of all injuries?

(a) Ligament injuries (b) Muscle injuries (c) Bone fractures (d) Contusions

Answer: (b) Muscle injuries account for approximately 33% of all injuries in professional soccer, with hamstring strains being the single most common diagnosis.

Question 2. The injury burden metric is calculated as:

(a) Total injuries divided by total exposure hours (b) Incidence multiplied by mean severity (c) Total days lost divided by total injuries (d) Incidence divided by severity

Answer: (b) Injury burden = Incidence (injuries per 1,000 hours) x Mean Severity (days of absence), capturing both frequency and impact.

Question 3. Which of the following is the strongest intrinsic risk factor for future injury in professional soccer?

(a) Age over 30 (b) High body mass index (c) Previous injury (d) Low aerobic fitness

Answer: (c) Previous injury is consistently the strongest predictor of future injury, increasing risk by approximately 2-3 times.

Question 4. In the standard ACWR framework, the acute workload window covers:

(a) 3 days (b) 7 days (c) 14 days (d) 21 days

Answer: (b) The standard acute window is 7 days, representing recent workload, compared against a 28-day chronic window.

Question 5. According to Gabbett's framework, the ACWR "sweet spot" associated with lowest injury risk is:

(a) 0.5 - 0.8 (b) 0.8 - 1.3 (c) 1.0 - 1.5 (d) 1.3 - 1.8

Answer: (b) The 0.8-1.3 range is considered the "sweet spot" where the player's acute load is well-matched to their chronic preparation.

Question 6. What is the primary advantage of using an exponentially weighted moving average (EWMA) over a simple rolling average for ACWR calculation?

(a) It requires less data (b) It is computationally simpler (c) It reduces mathematical coupling and weights recent loads more heavily (d) It eliminates all sources of bias

Answer: (c) The EWMA approach assigns greater weight to more recent loads and reduces the mathematical coupling artifact present in the standard rolling average model.

Question 7. Session RPE (sRPE) load is calculated as:

(a) Heart rate x Duration (b) RPE x Distance covered (c) RPE x Duration in minutes (d) RPE x Number of high-intensity actions

Answer: (c) sRPE load = RPE rating (0-10 scale) x session duration in minutes, expressed in arbitrary units.

Question 8. Training monotony is defined as:

(a) The total weekly training load (b) The mean daily load divided by the standard deviation of daily loads (c) The ratio of match load to training load (d) The number of consecutive training days

Answer: (b) Training monotony = mean daily load / standard deviation of daily loads. High monotony indicates low day-to-day variation, which has been associated with increased illness and injury risk.

Question 9. A key challenge in building injury risk models for soccer is:

(a) Too much data to process (b) The high base rate of injuries making models too sensitive (c) The low base rate of injuries causing extreme class imbalance (d) The inability to collect any relevant predictor variables

Answer: (c) Injuries on any given day are rare events (approximately 1-2% probability), creating extreme class imbalance that leads to models with low precision despite reasonable AUC-ROC scores.

Question 10. If an injury risk model has 80% sensitivity and 90% specificity, and the daily injury base rate is 1%, the approximate positive predictive value (precision) is:

(a) 75% (b) 50% (c) 25% (d) 9.5%

Answer: (d) Using Bayes' theorem: PPV = (0.80 x 0.01) / (0.80 x 0.01 + 0.10 x 0.99) = 0.008 / 0.107 = approximately 9.5%. This highlights the precision problem with rare-event prediction.

Question 11. Which survival analysis model estimates the hazard of injury as a function of covariates while making no assumption about the baseline hazard function?

(a) Kaplan-Meier estimator (b) Cox proportional hazards model (c) Exponential survival model (d) Weibull regression

Answer: (b) The Cox proportional hazards model is semi-parametric -- it estimates covariate effects without specifying the form of the baseline hazard function.

Question 12. The Brier score is useful for evaluating injury risk models because it measures:

(a) Only discrimination (ranking ability) (b) Only calibration (probability accuracy) (c) Both discrimination and calibration (d) Feature importance

Answer: (c) The Brier score = (1/N) * sum((p_i - y_i)^2) captures both how well the model ranks observations (discrimination) and how accurate the predicted probabilities are (calibration).

Question 13. What is the typical re-injury rate for hamstring injuries within the first 2 months of return to play?

(a) 2-5% (b) 12-16% (c) 25-30% (d) 40-50%

Answer: (b) Hamstring re-injury rates are approximately 12-16% within the first 2 months of return, making careful return-to-play management essential.

Question 14. Heart rate variability (HRV), specifically LnrMSSD, is used as a recovery metric because:

(a) It directly measures muscle damage (b) It indicates cardiac autonomic recovery status (c) It measures aerobic fitness (d) It quantifies training load

Answer: (b) HRV reflects the balance between sympathetic and parasympathetic nervous system activity. Reduced HRV suggests incomplete autonomic recovery and potential elevated stress.

Question 15. Creatine kinase (CK) levels following a match typically peak at:

(a) Immediately post-match (b) 6-12 hours post-match (c) 24-48 hours post-match (d) 72-96 hours post-match

Answer: (c) CK, a marker of muscle damage, typically peaks 24-48 hours post-match and returns to baseline within 72-96 hours.

Question 16. Research suggests that injury incidence increases by approximately what percentage when matches are separated by fewer than 4 days?

(a) 5-10% (b) 20-40% (c) 50-70% (d) 80-100%

Answer: (b) Injury incidence increases by approximately 20-40% during fixture congestion when recovery time between matches is insufficient.

Question 17. In the squad rotation optimization formulation, the constraint $\sum_{j=k}^{k+2} x_{ij} \leq 2$ ensures that:

(a) Each player plays at least 2 matches (b) No player starts more than 2 out of any 3 consecutive matches (c) At least 2 players are rotated per match (d) The squad has at least 2 backup players

Answer: (b) This constraint prevents any player from starting 3 consecutive matches in a congested period, ensuring minimum recovery time.

Question 18. The performance decay model $q_{ij} = q_i^{\max} \cdot (1 - \delta \cdot \sum w(d))$ captures the idea that:

(a) Player quality improves with more match experience (b) Player quality decreases with accumulated fatigue from recent matches (c) Player quality is constant regardless of fixture load (d) Player quality depends only on opponent strength

Answer: (b) The model captures the degradation of player performance due to insufficient recovery between matches, with the weight function encoding the relationship between recovery time and residual fatigue.

Question 19. For young players (under 21), the recommended annual load increase rate is typically:

(a) 5-8% per year (b) 10-15% per year (c) 20-25% per year (d) 30-40% per year

Answer: (b) A 10-15% annual increase is generally recommended for developing players to allow gradual adaptation without excessive spike risk.

Question 20. Former professional soccer players have approximately what increased prevalence of knee and hip osteoarthritis compared to age-matched controls?

(a) No increased risk (b) 1.5x higher (c) 2-3x higher (d) 5-10x higher

Answer: (c) Research indicates a 2-3x higher prevalence of osteoarthritis in former professional soccer players, highlighting the long-term physical cost of the sport.

Question 21. The "last mile" problem in injury prevention analytics refers to:

(a) The final kilometers of a match where most injuries occur (b) The challenge of translating analytical insights into behavioral change by coaches and staff (c) The last training session before a match (d) The final stage of rehabilitation

Answer: (b) The "last mile" problem describes the difficulty of ensuring that sophisticated analytical outputs are understood, trusted, and acted upon by non-technical decision-makers.

Question 22. Which of the following is NOT a recommended principle for communicating injury risk model outputs to coaching staff?

(a) Present metrics as z-scores relative to individual baselines (b) Use traffic light systems for at-a-glance interpretation (c) Report exact probability values with multiple decimal places (d) Convey uncertainty ranges rather than point estimates

Answer: (c) Reporting exact probabilities with excessive precision creates a false sense of certainty. Ranges, traffic light systems, and contextualized metrics are more effective communication approaches.

Question 23. In the context of injury risk data ethics, which statement best represents best practice?

(a) Injury risk predictions should be shared with all club stakeholders including agents (b) Injury risk data should be used for contract negotiation to protect club investment (c) Players should have informed consent regarding data collection and access to their own data (d) Injury risk data should be kept exclusively by the data science team

Answer: (c) Best practice requires informed consent, player access to their own data, clear governance policies, and protection against punitive use of health data.

Question 24. The "coupled" ACWR model refers to a formulation where:

(a) Two different load metrics are combined (b) The acute period is included within the chronic period calculation (c) Internal and external loads are coupled together (d) Training and match loads are analyzed jointly

Answer: (b) In the coupled model, the acute 7-day period overlaps with and is included within the 28-day chronic period, creating a mathematical coupling artifact that can bias the ratio.

Question 25. A club reduces its total injury burden from 120 to 85 (per 1,000 hours). Using the injury-performance coefficient of approximately -0.5 league points per injury and assuming a typical squad injury count drop from 55 to 40, the estimated gain in league points is approximately:

(a) 3-4 points (b) 7-8 points (c) 12-15 points (d) 20-25 points

Answer: (b) With 15 fewer injuries and a coefficient of approximately 0.5 points per injury: 15 x 0.5 = 9.5 points, a potentially season-defining improvement.