# Longitudinal cohort study on subsequent injury risk in professional football players in the Qatar Stars League: a probabilistic approach using basic learning

**Authors:** Montassar Tabben, Karim Chamari, Khalid Alkhelaifi, Tanvir Alam, Jassim Almulla

PMC · DOI: 10.5114/biolsport.2026.152345 · Biology of Sport · 2025-10-07

## TL;DR

This study examines injury recurrence patterns in professional football players in Qatar, showing that certain muscle groups have high probabilities of re-injury, suggesting the need for targeted prevention.

## Contribution

The study introduces a probabilistic approach using a Markov model to analyze injury recurrence patterns in football players.

## Key findings

- Hamstring injuries had a 7.5% probability of recurrence within the same season.
- Groin injuries had a 2.9% probability of resulting in subsequent hamstring injury.
- 34% of all injuries were subsequent, with a focus on thigh and groin areas.

## Abstract

Better understanding of the biomechanical and physiological mechanisms underlying subsequent injuries could have substantial implications for clinical practice in sports medicine. We investigated subsequent injury risk among professional football players in the Qatar Stars League (QSL), focusing on injury recurrence patterns over nine competitive seasons (2013–2021). Through an observational cohort study, we collected data on time-loss injuries from 1,258 players, recording 4,700 injuries categorized by body part, injury type, and recurrence. Utilizing Markov model, we explored probabilistic links between initial/index and subsequent injuries (defined as those occurring within the same season), highlighting patterns of recurrence in muscle groups prone to biomechanical strain. Our analysis identified 1,599 injuries (34% of total) as subsequent, primarily affecting the thigh (notably hamstrings) and groin. For instance, hamstring injuries exhibited an 7.5% (± 1.3%) probability of recurrence within the same season, while groin injuries had a 2.9% (± 0.82%) probability of resulting in subsequent hamstring injury. Our findings suggest that even basic probabilistic modeling, such as Markov chains, can enhance targeted injury prevention strategies. The high rate of recurrence, particularly in lower limb muscles, underscores the need for tailored rehabilitation programs emphasizing biomechanical stability. This comprehensive study offers a robust evidence base for injury mitigation strategies in elite football, recommending proactive monitoring and data-driven interventions to reduce injury recurrence and enhance player health, availability, and long-term performance.

## Full-text entities

- **Diseases:** Chronic Ankle Instability (MESH:D016512), Hip and Groin Muscle Injury (MESH:D025981), fatigue (MESH:D005221), Injuries (MESH:D014947), arthrogenic muscle (MESH:D019042), sports injuries (MESH:D001265), ACL (anterior cruciate ligament) injury (MESH:D000070598), Hamstring Muscle Injury (MESH:D009135), impaired neuromuscular control (MESH:D009468), quadriceps injury (MESH:D020389), re-injuries (MESH:D000083102), joint injury (MESH:D000092464), Re (MESH:D000084063), Hip and Groin Tendon Injury (MESH:D013708), MCL (MESH:C535516), concussion (MESH:D001924)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

_Full body text omitted from this summary view._ Fetch the complete paper as Markdown: https://tomesphere.com/paper/PMC12954500/full.md

## Figures

7 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12954500/full.md

## References

26 references — full list in the complete paper: https://tomesphere.com/paper/PMC12954500/full.md

---
Source: https://tomesphere.com/paper/PMC12954500