# How Trustworthy Are Your Health Checks?

## Introduction
  
In esports, where a fraction of a second can determine the outcome of a game, understanding and assessing a player’s **health, fitness, and wellbeing** is essential. But to make meaningful decisions based on these assessments, the tools and methods used must be **valid**, **reliable**, and **evidence-based**.

Whether you're a coach evaluating your team, a student learning about performance science, or a player looking to improve, it's important to ask:

* *Is this assessment accurate?*
* *Can it be trusted?*
* *Are the conclusions supported by reliable data?*

This article explores:

* The meaning and importance of **validity** and **reliability**
* Key factors in conducting trustworthy assessments
* How to identify **authentic sources**
* Misuse of data and how to avoid it
* What makes conclusions meaningful and credible
* Real-life applications in the world of esports and fitness

  

## What Are Validity and Reliability?

Let’s define these two crucial concepts:

### **Validity**

Validity refers to **how well a test or assessment actually measures what it claims to measure**.

> **Example**: If a sleep tracker says you had a “good night’s sleep,” did it actually measure your sleep quality using meaningful data, like REM cycles and wake periods?

A test is valid if:

* The method fits the purpose (e.g. using heart rate to assess stress)
* The results lead to useful and appropriate conclusions
* The data supports what is being claimed

  

### **Reliability**

Reliability is about **consistency** — whether an assessment gives the same results under the same conditions over time.

> **Example**: If you measure your reaction time using the same tool every morning and get drastically different results without a reason, the tool may not be reliable.

A reliable test:

* Produces **consistent** results over multiple trials
* Can be **repeated** by others with similar outcomes
* Is **not affected** by random errors or environmental factors

  

## Why Validity and Reliability Matter in Esports Health Assessments

In the context of **esports performance**, players undergo physical and psychological assessments to monitor:

* Reaction times
* Focus and cognition
* Mental wellbeing
* Fitness and recovery

If these assessments are not valid or reliable:

* Training may be **ineffective**
* Players may be given **incorrect advice**
* Injuries, burnout, or performance drops may be **missed**
* Data may be **misinterpreted**, leading to bad decisions

  

## Key Considerations When Conducting and Measuring Assessments

Let’s look at the essential factors students and practitioners should consider:

  

### 1. **Sample Size**

A large and diverse sample size makes data more **representative and reliable**.

**Example**:
If you're researching how physical activity affects esports players’ stress levels, testing 5 people won’t give you reliable data. Testing 50–100 with varied backgrounds will.

**Esports application**:
When analysing wellbeing across a team, include:

* Starters and substitutes
* Players in different roles
* Different age ranges or genders if possible

**Fun fact**:
The larger the sample size, the lower the impact of individual variation (like someone having a bad day).

  

### 2. **Suitability and Number of References**

Using **trusted sources** improves the **credibility** of your work.

Check that your research includes:

* Multiple references (3–5+)
* Relevant and up-to-date sources
* Trusted publications (e.g. academic journals, official reports, respected esports organisations)

**Good sources**:

* [PubMed](https://pubmed.ncbi.nlm.nih.gov/)
* [British Esports Association](https://britishesports.org)
* [NHS Live Well](https://www.nhs.uk/live-well/)
* Esports teams’ official wellbeing programs (e.g. Fnatic’s HPU)

**Poor sources**:

* Forums or personal blogs without evidence
* Social media “hot takes”
* Outdated or vague articles with no authors

  

### 3. **Use of Peer Review**

**Peer-reviewed** research means other experts have reviewed the methods and agreed the work is valid.

**Why it's important**:

* It filters out flawed or biased research
* Increases confidence in the findings
* Sets a high standard of evidence

**How to check**:
Search the journal name (e.g. "Journal of Sports Science") and see if it lists itself as "peer-reviewed" or is indexed in research databases.

**Real-life link**:
Research into reaction time training in esports is now being published in peer-reviewed journals like *Frontiers in Psychology*.

  

### 4. **Use and Misuse of Data**

**Using data responsibly** is essential for valid conclusions. Problems include:

* **Cherry-picking**: Selecting only the data that supports your argument
* **Misquoting**: Taking quotes out of context to change their meaning
* **Over-generalising**: Assuming results from a small group apply to everyone

> “Physical exercise improves mental health, so every esports player should run 10km daily!” — this is an **over-generalisation** and ignores individual needs.

**Best practice**:

* Present all findings — even those that contradict your hypothesis
* Use data transparently, with citations
* Be honest about **limitations** (e.g. “small sample size”)

  

### 5. **Authenticity of Information**

Check that your sources are:

* **Up to date** (preferably within the last 5 years)
* **Authored by qualified professionals**
* **Published in reputable outlets**

**Look for**:

* Publication date
* Author bio or credentials
* Organisation behind the article

**Warning signs**:

* No named author
* Outdated statistics (e.g. pre-COVID health data)
* Unclear source (e.g. copied across multiple websites)

**Example**:
An article from 2012 about “gaming posture” might not reflect current knowledge or equipment setups.

  

## Evaluating the Validity of Conclusions

When a report or assessment makes a conclusion, ask:

* **Does the data support the conclusion?**
* **Were the right methods used?**
* **Is the conclusion relevant to the esports context?**

> Example: A conclusion that “hydration improves esports performance” is valid *if* the study included hydration measurements and tracked gameplay outcomes.

**Invalid conclusion**:

* A conclusion based on **assumption** or **uncited claims**
* Ignoring variables like player age, game type, or environment

**Relevant conclusion**:

* Matches the purpose (e.g. improving team performance, reducing stress)
* Is backed by evidence and directly linked to the research question

  

## Supporting Evidence for Claims

For a conclusion or claim to be meaningful, it must be supported by:

* **Data** from valid assessments
* **Observations** over time
* **Literature** from credible sources

### Strong claim:

> “Players who exercised 3x a week showed a 12% faster reaction time after 4 weeks.”
>  Supported by numerical data
>  Matches the research goal
>  Easy to replicate

### Weak claim:

> “Exercise is good for all players.”
>  Too vague
>  Lacks evidence or specific outcomes

  

## Real-World Application: How Pro Esports Teams Ensure Validity

### Case Study: **Astralis**

* Regularly assesses sleep, heart rate, and screen exposure
* Uses peer-reviewed methods (e.g. WHO sleep quality index)
* Compares physical and mental wellbeing to win/loss ratios

### Case Study: **Excel Esports**

* Collaborates with physiotherapists and nutritionists
* Runs body composition scans (bioelectrical impedance)
* Applies psychology tools like WEMWBS to assess player readiness

**Outcome**:
Players report fewer stress-related issues, fewer injuries, and greater team cohesion.

  

## Summary Table: Validity & Reliability Checklist

| Assessment Factor | Why It Matters | Tip |
| ----------------------- | -------------------------------- | -------------------------------- |
| **Sample Size** | Larger size = more reliable data | Aim for 30+ participants |
| **References** | Improves credibility | Use NHS, PubMed, British Esports |
| **Peer Review** | Ensures quality | Check journal reputation |
| **Misuse of Data** | Leads to wrong conclusions | Avoid cherry-picking or bias |
| **Authenticity** | Trustworthy sources only | Check authorship and date |
| **Conclusion Validity** | Must match purpose and data | Ask: “Does the data prove this?” |
| **Supporting Evidence** | Back up claims with data | Use quotes, stats, and visuals |

  

## Final Thoughts

In esports health, wellbeing, and fitness, the **quality of your assessment methods** matters just as much as the results.

A report, training plan, or wellbeing review is only useful if:

* It is **valid** — measuring what it claims to measure
* It is **reliable** — producing consistent results over time
* Its conclusions are **evidence-based** and relevant to the player or team

Whether you're a student, coach, or player, developing the habit of **critical analysis and data integrity** will serve you well in esports — and beyond.

  

## Further Reading and Useful Links

* [British Esports – Research and Resources](https://britishesports.org/)
* [PubMed – Health Studies Database](https://pubmed.ncbi.nlm.nih.gov/)
* [NHS Live Well – Healthy Living Tools](https://www.nhs.uk/live-well/)
* [WEMWBS – Official Mental Wellbeing Scale](https://warwick.ac.uk/fac/sci/med/research/platform/wemwbs/)
* [Team Liquid – Performance Department](https://www.teamliquid.com/)
* [Excel Esports Performance Philosophy](https://excelesports.com/)