3rd
Danielle Lewis' scorecard
IRONMAN Arizona
Sunday 20th November, 2022
Within recommended ranges
Just outside recommended ranges
Significantly outside recommended ranges
64g
Carb per hour
522mg
Sodium per hour
624ml
Fluid per hour
837mg/L
Relative sodium concentration
253mg
Total caffeine
How Danielle hit those numbers
How Danielle's hydration and fueling went...
- Danielle worked with the Sports Science team at PF&H during the months leading up to IRONMAN Arizona, with a focus on on nailing her hydration, and overcoming GI discomfort issues that she'd experienced in previous races
- Danielle adapted her strategy and perceived her hydration on the day as a 9 (out of 10), and fueling as an 8, despite a major mechanical setback while on the bike
- Impressively, Danielle broke a 12 year old run course record with her 2:52:44 marathon. This effort meant that she fought her way back and secured 3rd place
Hydration
- Danielle adapted her usual pre-race routine to include preloading with PH 1500, both the night before and the morning of the race. This topped up her blood plasma volume and ensured she started the race optimally hydrated
- During the race itself, she mainly focused on getting sodium via her two 750ml (24oz) home made drink mix bottles on the bike (a mixture of ~150g carb,~700ml fluid and 1500mg sodium). Before using salt tablets, and a soft flask containing PH 1500 through T2 and while running
- This meant she averaged an intake across the bike and run of ~713ml (23oz) fluid per hour, with a relative sodium concentration of ~837mg/L (mg/32oz)
- This concentration will have sufficiently replaced what she was losing in the relatively mild conditions of Arizona, where Danielle's sweat rate was likely to be lower. But we know from her Sweat Test that she's classified as a high sodium sweater, losing 1,310mg of sodium per litre of sweat, and so she will want to increase the relative sodium concentration of her intake when racing in hotter conditions in future
- Danielle’s Coca Cola intake on the run supplemented her overall caffeine intake, which, at ~252mg, would certainly fall between the 3-6mg/kg range generally recommended by the current scientific literature
Fueling
Quick Carb Calculator Recommendation
30g
carb 30 mins before
60-90g
carb per hour during
- By increasing her carb intake in the days prior to the race, culminating in a dinner of pasta and a breakfast bagel with banana and honey, Danielle ensured she had maximal stored energy come race-day
- Around 20 minutes prior to starting, she also had a PF 30 Caffeine Gel which helped top up her blood glucose and allowed her to increase her mental alertness
- Danielle got most of her carb intake while on the bike from a homemade carbohydrate drink in her bottles, but also had some PF 30 Gels and a pack of chews to eat ‘when she felt hungry’. These helped her to avoid the dreaded ‘flavour fatigue’ which long course triathletes know all too well
- An unfortunate mechanical issue meant that Danielle had a ~20 minute wait on the roadside before she could finish the bike and get running, this is likely to have contributed to the dip in energy she experienced at this point
- Without this delay, Danielle’s fuel intake would have been significantly closer to her ideal target, at ~71g carb per hour, whereas she achieved ~65g/h on the day
- Hopefully, Danielle won’t experience unforeseen stoppages in the future, but if she does, we would recommend consuming fuel to maintain energy levels
- During the run, a large proportion of Danielle’s fuel came from aid station Coca-Cola collections, alongside soft flasks containing PF 90 Gels
- This meant that she was able to average ~75g of carb per hour while running, where her “legs and body felt amazing”, leading her to crush a course record run split (2:52:44) and claim 3rd position
Conclusions
- Danielle did well to overcome unforeseen setbacks in this race, and her solid fuel and hydration strategy undoubtedly played a part in this story unfolding
- Reflecting on the race, Danielle said: “I’m happy I could provide an inspiring performance showing people what is possible when you move past hardship and just keep going”
- In future races, Danielle has some things to work on, including building up her overall carb intake while maintaining GI comfort and ensuring she eats extra fuel if forced to stop for any reason
Key info
Danielle Lewis
Female
Sweat sodium concentration
1310mg/L
Sweat sodium classification
High
* determined by a PH Advanced Sweat Test
Result
Position
3rd
Overall Time
9:03:18
Swim Time
1:00:48
Bike Time
5:03:23
Run Time
2:52:44
Event information
Sport
Triathlon
Discipline
Full distance
Event
IRONMAN Arizona
Location
Tempe, USA
Date
20th November, 2022
Website
Swim Distance
3.8km / 2.4mi
Bike Distance
180.2km / 112.0mi
Run Distance
42.2km / 26.2mi
Total Distance
226.2km / 140.6mi
Race conditions
Weather Conditions
Mild
Precipitation
No Rain
Min Temp
10°C / 50°F
Max Temp
22°C / 72°F
Avg Temp
16°C / 61°F
Humidity
20%
Athlete feedback
Race Satisfaction
7/10
Hydration rating
9/10
I would rate this a 10, but I forgot to pack the bottle of fluid with the PH tab to consume in T2.
Energy levels
8/10
I had an energy dip late in the bike
GI comfort
8/10
Cramping
No cramping
Danielle's Thoughts
I'm happy I could provide an inspiring performance showing people what is possible when you move past hardship and just keep going
Danielle's full stats
Carbohydrate (g) | Sodium (mg) | Fluid (ml) | Caffeine (mg) | Relative sodium concentration (mg/L) | |
---|---|---|---|---|---|
Overall | |||||
Total intake | 582 | 4,725 | 5,645 | 253 | 837 |
Per hour | 64 | 522 | 624 | 28 | |
Bike and Run | |||||
Total intake | 552 | 4,725 | 5,645 | 153 | 837 |
Per hour | 70 | 597 | 713 | 19 | |
Bike | |||||
Total intake | 338 | 3,300 | 3,725 | 100 | 886 |
Per hour | 67 | 653 | 738 | 20 | |
Run | |||||
Total intake | 214 | 1,425 | 1,920 | 53 | 742 |
Per hour | 75 | 497 | 670 | 18 |
Data Confidence
1
2
3
4
5
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.