What makes someone strong right now isn’t the same as what makes them get stronger after training — your starting point doesn’t tell you how much you’ll improve.
Scientific Claim
The neuromuscular variables that best predict maximum strength in a population (e.g., muscle size, activation, moment arm) do not predict strength gains following 10 weeks of training in previously untrained men, indicating that cross-sectional and longitudinal determinants of strength differ fundamentally.
Original Statement
“The best models previously identified for predicting maximum torque within a population [...] were unable to predict the changes in torque with chronic training (R² = 0.00 to 0.07)”
Evidence Quality Assessment
Claim Status
appropriately stated
Study Design Support
Design supports claim
Appropriate Language Strength
association
Can only show association/correlation
Assessment Explanation
The claim accurately reflects the study’s direct comparison between cross-sectional predictors and longitudinal change. No causal language is used, and the design supports the correlational conclusion.
Gold Standard Evidence Needed
According to GRADE and EBM methodology, here is what ideal scientific evidence would look like to definitively prove or disprove this specific claim, ordered from strongest to weakest evidence.
Longitudinal Cohort StudyLevel 2bIn EvidenceThat the same neuromuscular predictors of baseline strength consistently fail to predict training-induced gains across multiple populations and training protocols.
That the same neuromuscular predictors of baseline strength consistently fail to predict training-induced gains across multiple populations and training protocols.
What This Would Prove
That the same neuromuscular predictors of baseline strength consistently fail to predict training-induced gains across multiple populations and training protocols.
Ideal Study Design
A prospective cohort of 500+ untrained individuals (men and women, ages 18–60) undergoing 10–12 weeks of standardized resistance training, with pre-training neuromuscular profiles (CSA, EMG, MA, %VA) measured and correlated with strength gains, replicated across multiple labs.
Limitation: Cannot determine if the disconnect is due to measurement error or true biological divergence.
Systematic Review & Meta-AnalysisLevel 1aWhether the disconnect between cross-sectional predictors and training response is a consistent phenomenon across all published studies.
Whether the disconnect between cross-sectional predictors and training response is a consistent phenomenon across all published studies.
What This Would Prove
Whether the disconnect between cross-sectional predictors and training response is a consistent phenomenon across all published studies.
Ideal Study Design
A systematic review and meta-analysis of all longitudinal resistance training studies (n≥20) that report both baseline strength predictors and training-induced changes, pooling correlation coefficients between cross-sectional predictors and Δstrength.
Limitation: Cannot establish mechanisms — only confirms statistical pattern.
Cross-Sectional StudyLevel 3Whether the same variables predict strength across different training statuses (trained vs. untrained).
Whether the same variables predict strength across different training statuses (trained vs. untrained).
What This Would Prove
Whether the same variables predict strength across different training statuses (trained vs. untrained).
Ideal Study Design
A cross-sectional analysis comparing 300+ individuals across training statuses (untrained, novice, experienced) to determine if the strongest predictors of strength change with training experience.
Limitation: Cannot determine direction of causality or temporal sequence.
Evidence from Studies
Supporting (1)
This study found that how strong you are at the start isn't what helps you get stronger after training — instead, it's how much your muscles activate and grow during training that matters. So yes, what makes you strong now is different from what helps you get stronger.