TRIQ – Triathlon Training Plan 1.7.1

TRIQ offers a comprehensive solution for triathlon preparation, tailored to both seasoned athletes and beginners. Its innovative algorithm designs personalized training plans that adjust to your performance, motivation, and current fitness levels continuously. Leveraging machine learning, TRIQ refines its plans over time to suit your availability and assist in maintaining a balanced schedule between training, work, and personal life.

To utilize the app effectively, users must have a Garmin tracking watch and a Connect account. This integration allows TRIQ to access performance data in real-time and make instant adjustments based on the provided metrics.

With a strong focus on training objectives, TRIQ enables users to select their preferred triathlon race and set a specific target finish time. Additionally, the platform evaluates individual availability and fitness status from the onset, verifying the feasibility of set goals. It suggests alternative strategies if needed, such as adjusting finish times, extending training periods, or considering different triathlon options.

• Full Distance Triathlon: 2.4 miles swim (3.9 km), 112 miles bike (180 km), 26.2 miles marathon run (42.2 km)
• Half Distance Triathlon: 1.2 miles swim (1.9 km), 56 miles bike (90 km), 13.1 miles half marathon run (21.1 km)
• Olympic Distance Triathlon: 0.93 miles swim (1.5 km), 25 miles bike (40 km), 6.2 miles run (10 km)
• Sprint Triathlon: 0.47 miles swim (750 m), 12 miles bike (20 km), 3.1 miles run (5 km)

Individualized training plans are central to TRIQ's approach, with each schedule uniquely generated by its advanced algorithm to meet specific athlete requirements. These plans encompass swim, bike, and run sessions tailored to individual capabilities and goals, along with dedicated recovery periods derived from user data and feedback dynamics.

Continuous monitoring of progress forms the core of TRIQ's strategy, utilizing physiological and performance data from Garmin Connect fitness trackers and built-in heart rate monitoring via iPhone cameras to deliver targeted feedback for optimized training experiences.

The platform's development is backed by a team of expert sports scientists and advisors, including Dr. Ruby Otter-Drost – a sports scientist specializing in athlete monitoring – and Dr. Stephen Seiler, a distinguished professor with significant contributions in endurance sports research.

User experience feedback remains crucial for TRIQ's continuous enhancement, with reviews and comments welcomed to facilitate ongoing improvements toward an optimal training platform. For more details about TRIQ, please visit the website: www.triq.ai

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