From Monitoring to Prediction: Velocity-Based Strength Training in Female Floorball Athletes

Area of Science:

• Sports Science
• Biomechanics
• Strength and Conditioning

Background:

• Velocity-based training (VBT) is increasingly used in athletic development.
• Optimizing training for female athletes in team sports requires specific strategies.
• Predictive modeling can enhance the efficacy of training interventions.

Purpose of the Study:

• To examine the predictive capability of linear regression models for VBT outcomes in female floorball players.
• To assess the impact of a six-week VBT intervention on key performance metrics.
• To identify potential improvements in neuromuscular adaptation and sport-specific performance.

Main Methods:

• A six-week VBT intervention involving back squats and trap bar deadlifts was implemented.
• Seventeen female floorball players completed 12 training sessions divided into strength and power blocks.
• Linear regression models were used to predict performance changes, with key metrics including neuromuscular adaptation, sprint speed, jump performance, and load-velocity profiles.

Main Results:

• Predictive models explained 54% to 79% (R2 = 0.54-0.79) of performance improvement in strength tests.
• Significant gains were observed in estimated one-repetition maximum (1RMest) and average mean concentric velocity.
• Improvements in sprint speed, jump performance, and stop-and-go (SAG) performance were noted.

Conclusions:

• Linear regression models demonstrate significant predictive potential for VBT interventions in female athletes.
• VBT effectively enhances neuromuscular adaptation, strength, and power in floorball players.
• Integrating task-specific exercises alongside VBT is crucial for optimizing sport-specific performance in female athletes.