If there’s one lesson I learned from my PhD studies at age 40, it’s that methods matter. In research, the methods section is crucial because it explains what the researchers did, how they collected data, and the statistical analyses used. Ben Goldacre, in his book Bad Science, advises, “Always read the methods and results section of a trial to decide what the findings are because the discussion and conclusion pages at the end are like the comment pages in a newspaper.”
As sports performance professionals, we rarely conduct experimental research in the academic sense. Experimental research involves randomization, internal and external validity, laboratory setups, and inferential statistics. Here’s a quick rundown of these concepts:
- Randomization: Assigning groups and treatments randomly to avoid sampling bias.
- Internal Validity: Ensuring data collection procedures are reliable and valid, and the experimental design is sound.
- External Validity: The ability to generalize results to a larger population, considering the real-world similarities.
- Inferential Statistics: Using a representative sample to infer results to a larger population (e.g., ANOVA, T-Tests).
In controlled lab environments, consistency is key—same people, places, times, materials, and conditions. However, as coaches, we operate in less controlled settings, often with small staffs, limited time, and tight budgets.
Real World vs. Academia
As sports performance coaches, we are more like observational researchers. We observe athletes in their natural settings (weight room, ice, field, court). Our aim is to maintain high internal validity with reliable and valid tools, but our research design differs. We don’t typically have control groups. Our team is both our sample and our population.
We use descriptive statistics to narrate our observations and inform players and coaches. This includes:
- Central Tendency: Mean, median, mode.
- Measures of Dispersion: Variance, standard deviation.
- Measures of Correlation: Pearson’s correlation coefficient.
The Texas Sharpshooter
In sports science, we are like the Texas sharpshooter who shoots randomly at the side of a barn and then draws a bullseye around the cluster of bullet holes. This method, while frowned upon in traditional experimental research, is often how we operate. We collect data, assess trends, and then form hypotheses. This approach is known as HARKing (hypothesizing after the results are known).
In traditional experimental research, the process is: Hypothesis → Data Collection → Results. In sports science, it often looks like this: Collect Data → Assess Trends → Hypothesize.
Do Coaches Need to Understand Statistics?
Understanding statistics can be valuable for coaches. A basic grasp of descriptive statistics helps in communicating effectively and displaying data in meaningful ways (e.g., choosing the correct plot or graph). While inferential statistics are more complex, having a basic understanding can enhance your ability to read and digest research efficiently, fostering a more critical mindset.
Methods Matter
Understanding the limitations and strengths of various methods is a powerful tool. It allows coaches to make informed decisions and better interpret data, ensuring that training programs are both effective and safe for athletes.
As Karl Popper said, “Science may be described as the art of systematic over-simplification.” By simplifying complex data into actionable insights, we can better serve our athletes and help them reach their full potential.
Conclusion
In sports performance, methods and statistics are not just academic concepts; they are practical tools that help us understand and improve athletic performance. By embracing a critical, methodical approach, we can navigate the complexities of training and ensure our athletes are not just competing, but excelling.