The best examples of injury risk assessment in athletes (and how to use them)

Real examples of injury risk assessment in athletes

Let’s start with what you actually care about: real examples of injury risk assessment in athletes and how they play out on the field, in the weight room, and in the training room.

Think of injury risk assessment as building a case. You rarely get one smoking gun. Instead, you collect clues:

• Movement quality
• Strength and power asymmetries
• Workload spikes
• Previous injury history
• Sport-specific demands

When enough clues stack up, you don’t wait for an injury. You change the plan.

Below are practical examples coaches and clinicians are using right now.

Example 1: ACL risk screening in a women’s soccer team

A Division I women’s soccer program wants fewer ACL tears. The staff runs a preseason screening that includes:

• Single-leg drop jump with video from the front and side
• Single-leg squat to a box
• Isometric hamstring strength with a handheld dynamometer
• Previous knee and ankle injury history
• Menstrual cycle–related symptom questionnaire

From this, they flag players who show:

• Strong knee valgus (knee collapsing inward) on landing
• More than 15% strength difference between legs
• History of ACL or serious ankle sprain

Those athletes are placed in a targeted neuromuscular program: extra hamstring work, landing mechanics drills, deceleration practice, and progressive plyometrics twice per week.

Over three seasons, the staff tracks injuries and finds a drop in ACL tears compared with their historical average and with conference peers. Is it perfect science? No. But it’s a strong, practical example of injury risk assessment in athletes leading to a meaningful shift in outcomes.

Example 2: Pitcher workload and elbow injury risk in baseball

A pro baseball organization uses a blend of data and simple observation to assess injury risk in pitchers:

• Daily pitch counts and high-intent throws (bullpens, long toss)
• Acute:chronic workload ratio (short-term vs. 4-week workload)
• Range of motion in shoulder internal rotation and elbow extension
• Self-reported soreness, especially medial elbow and posterior shoulder

When a pitcher’s acute workload spikes more than about 1.5x their recent average and they also show:

• Loss of shoulder internal rotation
• Persistent elbow soreness

the medical staff flags them for a load management intervention. That might mean:

• Shortening bullpen sessions
• Adding an extra rest day
• Increasing recovery modalities and targeted arm care

This is a classic example of injury risk assessment in athletes where the “test” is not one single screen but a pattern: workload spike + range-of-motion loss + pain. The decision isn’t to shut the pitcher down automatically, but to reduce risk before the UCL becomes a headline.

Example 3: High school basketball player with repeated ankle sprains

A high school guard has rolled her ankle three times in one season. The athletic trainer doesn’t just tape and pray; they run a focused risk assessment:

• Single-leg balance test with eyes open and closed
• Y-Balance Test for reach distance in three directions
• Calf strength (single-leg heel raises to fatigue)
• History of ankle sprains and time missed
• Shoe wear pattern and court surface

They find poor balance on the injured side and a 10% reach deficit on the Y-Balance Test, along with weak calf endurance.

The plan:

• Daily balance work on stable and unstable surfaces
• Progressive calf strengthening and plyometrics
• Mandatory lace-up brace during games and practices

This is a straightforward, field-based example of injury risk assessment in athletes that doesn’t require fancy tech, just structured observation and simple tests.

Example 4: Distance runner with early bone stress signs

A collegiate distance runner reports vague shin pain that “warms up” during runs but returns after. Instead of waiting for a stress fracture, the sports medicine team assesses risk:

• Training log review: weekly mileage, intensity, recent spikes
• Menstrual history and energy availability (REDs screening)
• Vitamin D and bone density where indicated
• Hop test and pain provocation with percussion

Workload data show a 30% mileage jump in three weeks plus more interval sessions. The athlete also reports irregular periods and low energy intake.

The staff flags high risk for tibial stress injury and:

• Cuts mileage by 30–40% temporarily
• Increases cross-training volume
• Refers for nutrition consult

This is a textbook example of injury risk assessment in athletes where the “injury” is still developing. The intervention is about changing the environment (training and fueling) before bone fails.

Example 5: NFL combine–style screening for hamstring risk in sprinters

A track coach working with elite sprinters adapts an NFL-style hamstring risk screen:

• Nordic hamstring strength test
• Isometric hip extension strength
• Sprint video at max speed
• History of prior hamstring strains and where they occurred

Sprinters with:

• Prior high-speed hamstring strains
• Low Nordic strength relative to body weight
• Poor front-side mechanics on video

are flagged for a high-hamstring-strain risk category. Their program shifts to:

• Extra eccentric hamstring work
• Gradual exposure to max-velocity sprinting
• More consistent warm-up and ramp-up protocols

Again, this isn’t about predicting the exact athlete who will pull a hamstring, but it’s a best example of injury risk assessment in athletes that tightens exposure to known risk factors.

Example 6: Youth athlete clearance after concussion

A 14-year-old soccer player is returning from a concussion. The medical team doesn’t just run a symptom checklist; they assess multiple layers of risk:

• Neurocognitive testing compared with baseline
• Balance and vestibular screening
• Symptom provocation during controlled aerobic activity
• History of previous concussions

If symptoms are easily provoked or balance is clearly impaired, they delay full return and keep the athlete in a graded exertion protocol.

This is an example of injury risk assessment in athletes where the main risk isn’t a muscle or tendon but the brain. The assessment protects against premature return and higher odds of repeat injury.

Example 7: Recreational CrossFit athlete with shoulder pain

Not every useful example has to come from pro or college sports. A recreational CrossFit athlete with nagging shoulder pain during overhead lifts is assessed by a physical therapist:

• Shoulder range of motion (flexion, external rotation)
• Scapular control during push-ups and overhead press
• Strength testing of rotator cuff and scapular stabilizers
• Training frequency and volume of overhead work

They find limited shoulder flexion and poor scapular upward rotation, combined with a heavy weekly diet of kipping pull-ups and snatches.

The risk assessment leads to:

• Temporary reduction in overhead volume
• Mobility and control work for the shoulder complex
• Gradual reintroduction of overhead lifting with better mechanics

This is a real-world example of injury risk assessment in athletes that matters for the millions of adults training hard outside formal team environments.

Key components behind these examples of injury risk assessment in athletes

Across all these stories, the same ingredients keep showing up. When you look at examples of injury risk assessment in athletes, you’ll usually find four pillars working together.

1. Medical and injury history

Previous injury is one of the strongest predictors of future injury. That’s not opinion; it’s well documented in the sports medicine literature and echoed by organizations like the CDC and NIH.

Patterns to watch:

• Multiple ankle sprains on the same side
• Prior ACL tear, especially in cutting sports
• Repeated hamstring strains in sprinters or field sport athletes
• History of bone stress injuries in runners

Any example of injury risk assessment in athletes that ignores history is incomplete. History tells you where the weak links have already shown themselves.

2. Movement quality and biomechanics

Movement screens are not crystal balls, but they’re useful when combined with other data. Examples include:

• Single-leg squat and step-down tests
• Landing mechanics from a box or small jump
• Sprint and change-of-direction video
• Overhead squat or lunge patterns

Research has moved away from the idea that a single movement test can predict injury on its own. Instead, movement screens now serve as one piece of a broader profile, helping you:

• Spot asymmetries
• Identify poor control under load
• Guide targeted strength and technique work

3. Workload and training load

One of the biggest 2024–2025 trends in injury risk assessment is the use of workload monitoring:

• GPS data for field and court sports
• Wearables tracking distance, speed, and accelerations
• Session RPE (rate of perceived exertion) to estimate internal load

Research published over the last decade has highlighted that rapid spikes in workload are associated with higher injury rates, especially in team sports. While there’s debate about exact thresholds, the principle holds: big jumps in intensity or volume raise risk.

In practice, that means:

• Tracking total distance and high-speed running in soccer
• Monitoring total throws in baseball
• Logging weekly mileage and intensity in runners

The best examples of injury risk assessment in athletes blend this workload data with symptoms and movement changes, rather than chasing one magic metric.

4. Context: age, level, and sport demands

A 12-year-old gymnast, a 30-year-old marathoner, and a 19-year-old linebacker do not share the same risk profile.

Context matters:

• Youth athletes: growth plate issues, overuse from early specialization
• Collegiate athletes: high total load from sport + strength training + academics
• Pros: dense schedules, travel fatigue, high external pressure to play

Good injury risk assessment respects those realities. The examples of injury risk assessment in athletes we walked through all adjust for age, sport, and competitive level.

How to build your own injury risk assessment process

You don’t need a lab. You need a repeatable system.

Think in three layers:

Baseline screening

At the start of a season or training block:

• Collect injury and medical history
• Run a small set of movement and strength tests relevant to the sport
• Record simple metrics you can repeat: single-leg hop distance, balance time, range of motion

The goal is not to label athletes as “safe” or “unsafe.” It’s to create a baseline you can compare against when something feels off.

Ongoing monitoring

During the season:

• Track training load (volume and intensity) in a way that fits your environment
• Ask for quick soreness or wellness ratings
• Watch for changes in movement quality: limping, favoring one side, slower decelerations

Patterns matter more than one bad day. When you see a cluster of red flags—load spike, soreness, movement change—that’s your cue to reassess.

Targeted follow-up testing

When an athlete is flagged:

• Repeat key tests from baseline
• Add more specific tests for the suspected area (e.g., hamstring strength after a sprinting spike)
• Adjust training and rehab based on what you find

This is how you turn theory into action, using the same logic pattern you saw in the earlier examples of injury risk assessment in athletes.

2024–2025 trends shaping injury risk assessment

Sports science in 2024–2025 is less about shiny toys and more about useful data.

Key trends:

Smarter, cheaper wearables

Wearables are now common even in high schools and serious recreational settings:

• GPS units for soccer, lacrosse, and football
• Accelerometers in basketball and volleyball
• Running watches that track pace, heart rate, and variability

The shift is from collecting data to interpreting it. Coaches are using simple dashboards to spot:

• Sudden jumps in high-speed running
• Unusual fatigue patterns
• Athletes whose workloads don’t match their positional peers

Force plates and jump testing

Force plates have moved from pro facilities to some colleges and private gyms. They’re used to:

• Measure asymmetries in jump height and landing forces
• Track neuromuscular fatigue across a season

When combined with subjective fatigue and soreness reports, force plate data can be a powerful example of injury risk assessment in athletes that goes beyond “you look tired.”

Integrated medical-performance teams

The best environments in 2025 don’t separate “medical” and “performance” silos. They:

• Share data between athletic trainers, strength coaches, and sport coaches
• Agree on red-flag criteria (e.g., no full practice if jump asymmetry exceeds a threshold and soreness is high)
• Make return-to-play decisions as a group

This integration is where many of the best examples of injury risk assessment in athletes actually live: not in a test, but in the way people talk to each other about the test results.

Limitations you should respect

One honest note: no assessment can predict injuries with perfect accuracy.

Common pitfalls:

• Relying on a single test score as destiny
• Ignoring athlete input (“I’m fine” or “something feels off”) in favor of numbers
• Collecting data with no plan to act on it

The goal of using these examples of injury risk assessment in athletes is not to guarantee a healthy season. It’s to:

• Reduce preventable injuries
• Catch problems earlier
• Make smarter decisions under pressure

If you treat assessments as decision-support tools—not crystal balls—you’ll get far more value out of them.

FAQ: examples of injury risk assessment in athletes

Q: What are some simple, field-based examples of injury risk assessment in athletes I can use without fancy equipment?
A: You can use single-leg balance tests, single-leg squats, hop tests, basic range-of-motion checks, and simple soreness/wellness questionnaires. Combine these with injury history and weekly training load (minutes, distance, or number of high-intensity efforts). Those basic tools mirror many of the real examples of injury risk assessment in athletes used in schools and clubs.

Q: Is there a single best example of injury risk assessment in athletes that works for every sport?
A: No. The best examples are always sport-specific. ACL risk screens make sense for soccer and basketball, hamstring-focused tests fit sprinters and football, and bone stress risk assessments are more relevant for runners and gymnasts. The core logic is the same—history, movement, load, and context—but the tests change with the sport.

Q: How often should I repeat injury risk assessments during a season?
A: Many programs run a full baseline once or twice per year and then use shorter check-ins weekly or biweekly. For example, a quick jump test plus a soreness survey can be done weekly, while more detailed strength and movement screens might be repeated every 6–8 weeks, or when an athlete shows warning signs.

Q: Are movement screens alone good examples of injury risk assessment in athletes?
A: Movement screens are useful, but on their own they’re incomplete. Research has shown that no single screen reliably predicts injury by itself. The strongest real examples of injury risk assessment in athletes combine movement data with training load, history, and current symptoms.

Q: Where can I learn more about evidence-based injury risk assessment?
A: Good starting points include the Centers for Disease Control and Prevention (CDC) pages on sports injuries, the National Institutes of Health (NIH) for research articles, and educational content from organizations like Mayo Clinic. These sources regularly publish updates on sports injury trends, prevention strategies, and assessment tools.