Padel is a sport where strategy and teamwork take precedence over brute force. With the explosion of smart cameras and sensors, data is no longer an issue in professional sports. Artificial Intelligence (AI) and data analysis now offer Padel players and coaches precise metrics to dissect performance, improve weak points, and even choose the ideal partner.

Fundamental Data Measured by AI

Modern analysis systems do more than just count faults; they evaluate the effectiveness of each court zone and every type of shot.

Net and Backcourt Effectiveness

• "Net Attack Rate": The percentage of times a team successfully advances to the net after the serve or return. A low Rate indicates a lack of aggression.

• "Back Wall Recovery": The effectiveness of a team in turning a defense after the back glass wall into a neutral or offensive shot (often a Lob). A low Recovery reveals a technical deficiency.

• "Unforced Errors" Rate by Zone: Locates specific areas where the player commits the most unforced errors (e.g., the front side glass, the exit of the Bandeja).

Specific Metrics for Attack Shots

• The Effectiveness of the Diving Smash: Measures the quality of a smash, not by force, but by effectiveness. It evaluates the probability that the smash cannot be defended, taking into account the exit angle after the rebound on the glass.

• Analysis of the Víbora's Impact: The percentage of Víboras (aggressive shots with spin) that force a fault or a defensive return from the opponent, often correlated with the ball's spin speed.

Optimization of Tactics and Partner

AI does more than just judge; it helps optimize the pair's work, which is crucial since Padel is always played in doubles.

Positioning and Court Deficiencies

• Positioning Analysis: AI tracks the average distance of each player from the net and the walls. It can identify court areas (often the middle) that are not properly covered by the pair.

• Effectiveness of Rhythm Changes: Measures the impact of variations (transition from defensive Bandeja to offensive smash). Helps players know if their Víbora is more effective at the beginning or the end of a rally.

Pair Profiling

• Tactical Roles: Data analysis can confirm if a player is more effective as a "drive" (left side, powerful attack) or "revés" (right side, control and defense).

• Identifying the Opponent's Weakness: In pre-match, AI can provide the opponent's preferred zone for ending the point, allowing the pair to adapt their defense.

The Future of Padel Coaching

The use of data in Padel is no longer just retrospective; it is becoming predictive.

• Real-Time Coaching: Although competition rules limit access to data during the match, sensors integrated into equipment (rackets, shoes) already allow coaches to analyze fatigue and technique degradation between sets.

• Injury Prevention: Analysis of movement data and the impact of strikes helps identify risky gestures (e.g., excessive shoulder rotation during a Bandeja) to adapt training and prevent injuries.

• Targeted Training: Generic exercises are over. A player can now specifically work on their Salida de Pared (Wall Exit) on the forehand side which systematically results in a defensive Lob, thanks to the precise statistics provided by AI tools.

Conclusion

The integration of AI and performance metrics moves Padel from intuition to scientific analysis. By transforming the feel of the game into quantifiable data, players can now perfect their technique, optimize their doubles coordination, and approach every match with a strategy based on numbers. This data revolution is redefining what it means to play and coach at the highest level in any sport.