Matthew Marquardt
PTO US Open
Matthew's headline numbers
Matthew's strategy
Fueling
Carbohydrate is the main fuel you burn when racing. Failing to fuel properly is a leading cause of underperformance in longer races.
Much like the other athletes competing in the US Open, Matthew chose to extend his normal pre-race carb load due to the later start time (4:15pm). Beyond breakfast time, Matthew took in carbohydrate-rich foods which would bolster the glycogen stores in his muscles and liver. In the immediate build up to the event, Matthew also consumed several supplements he has found to be personally beneficial in training, including tart cherry juice, sodium bicarbonate and beetroot powder. During the race, Matthew frontloaded his carb intake on the bike (~121g/h), providing him with plenty of available energy to crush the run course in just 1:04:28 (taking an impressive 105g/h!). The fact that Matthew could comfortably stomach no less than 9 different products during his race is a testament to his rigorous gut training and experimentation to improve his overall energy availability while maintaining gastrointestinal comfort.
Hydration
Taking on board an appropriate amount of fluid and sodium is essential to maintaining blood volume and supporting the cardiovascular effort needed to perform on race day.
Whilst the absolute amount of sodium and fluid consumed per hour is important, it’s critical to consider these in relation to each other. This is known as 'relative sodium concentration' and it’s expressed in milligrams per litre (mg/L). How much sodium you’re taking in per litre of fluid is more important than the absolute amount taken in per hour.
Sweat sodium concentration (mg/L) is largely genetically determined and remains relatively stable. Knowing how salty your sweat is enables you to replace a good proportion of your sweat losses, which can range from 200-2,000mg/L.
Whilst Matthew’s losses are on the low side, getting his hydration strategy right is still crucial when it’s hot and/or humid as his higher sweat rate in these conditions can result in significant net losses over the duration of a race.
Learn moreAs a medical school student with an extensive knowledge of human physiology, Matthew understands that there’s a constant balancing act in the body between blood electrolyte and fluid levels. Prior to the 4:15pm race-start, he drank several electrolyte drinks, including a PH 500 (Tablet) to induce some degree of hypervolemia (increased blood plasma volume) and start his race optimally hydrated. To get the most out of his bike’s hydration system, which allowed him to drink from a straw while staying in an aerodynamic position, Matthew primarily used a highly concentrated electrolyte and carbohydrate mix. He averaged just over 1.5L (48oz) of fluid per hour on the bike, dropping to ~844ml (30oz) per hour on the run, where he relied on the aid stations for energy drinks and water. He supplemented his fluid intake throughout the race with electrolyte capsules to ensure he maintained a relative sodium concentration of ~410mg/L, which closely matched his sweat sodium concentration (655 mg/L) as determined by a Sweat Test.
Caffeine
Beyond the Three Levers of Performance (carb, sodium and fluid), caffeine is one of only a few substances that is proven to improve performance for most endurance athletes as it can help stave off mental and physical fatigue.
Matthew’s caffeine intake sat just over the recommended intake of 3-6mg/kg of bodyweight. As he didn't experience any negative side effects from slightly high caffeine intake, we wouldn’t suggest he makes any major changes to his current plan.
How Matthew hit his numbers
Here's everything that Matthew ate and drank on the day...
Matthew's weapons of choice
Final thoughts
Matthew's full stats
Data Confidence?
There is an adequate level of accuracy in the data collected and the numbers reported. The athlete manages to recall what they ate and drank including most specifics (brands flavours quantities plausible estimations of volumes). However there are estimations made within the data which affect the overall confidence level in the data reported.