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Building your diet as an athlete - calculating your energy needs



The Hierarchy of Importance

Similar to the hierarchy of importance for body composition (credit to Eric Helms), performance follows a similar pattern where kcals are king, macronutrients (carbs, protein and fat) are next in terms of importance followed by meal timing and supplements.

Like any sport, adequate energy intake should be the cornerstone of your diet setup and due to its heavy energy demands in both volume (a lot of sessions) and intensity, calorific intake is especially important for competitive fitness or any sport power based sport. It’s all well and good eating ‘clean’ or ‘Paleo’ but if you’re not meeting the energy demands, it’s not just performance that will suffer but also health, recovery and an increased likelihood of getting ill.

Determining your energy needs


Energy requirements will depend on individual differences, goals, preferences, training, competition cycle and should be periodised day to day based on activity levels, volume and intensity. Energy intake should be determined by your total energy expenditure (TEE) or simply eating enough to match the kcals you will expend.

Your TEE is made up of basal metabolic rate, thermic effect of activity an thermic effect of food.

TEE = BMR + TEA + TEF

1. BMR - Basal metabolic rate - Daily energy expenditure at complete rest

2. TEA - Energy cost of all physical activity (included NEAT - Non-execie activity thermogenesis - fidgeting, around 10% of TEA) and planned exercise energy expenditure

​3. TEF - Thermic effect of feeding (around 10% of TEE)

Calculating each component

To work out your BMR you can use a simple equation like the ‘Mfflin-St Jeer’ or 'Harris-Benedict' method. Although this may not be entirely accurate (calculations don’t equate for individual differences), it will at least give you a starting figure to move forward with.

Calculating total exercise activity (TEA) can roughly be done by using something like a 7 day exercise log and cross referencing it with the MET scale or similar exercise activity index (Shephard, 2012).


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Energy expenditure will of course differ from workout to workout because of the variety of competitive fitness, however using data on other similar types of exercise (weight training, running, circuit training) we can still grasp a relatively good idea of the calorific cost of some of your typical WOD's.

A recent study looked at the energy expenditure of the workout Cindy (pull ups/push ups/air squats) and showing an average expenditure of 10.1 - 15.9 kcals per minute (13 ± 2.9 kcals/min) for the 20mins workout. (Kliszczewicz et al., 2014). Depending on the length of your training this gives you a relatively good idea about its energy expenditure. Compared to weight based circuit training, the average energy cost per minute was 6.21+/-1.01 kcal/min for males and 4.04+/-1.45 kcal/min for females (Beckham, 1999). Obviously the type of exercises will have an impact on calorific cost but we can still draw a reasonable correlation between the two.


Another study looked at one of the popular benchmark workouts ‘Fran', which is more power based compromising of barbell lifts (front squat/push press) and pull ups. The average calorific cost here were 9.38-13.82 per minute (females) and 16.71- 24.09 (men) (Babyish, 2013). We can see that this type of workout, which is more consistent with the High Intensity Power Training (HIPT) coined by Smith et al., 2013 has a higher energy expenditure than Cindy, which just highlights the difference in expenditure between workouts that should ultimately be reflected with your eating.

A more recent concept worth being aware of is energy availability (EA). Energy availability is defined as dietary energy intake minus the energy expended in exercise (Loukes et al., 2011). Or, ‘The amount of energy available to the body to perform all other functions after the cost of exercise is subtracted’ (Nutrition and athletic performance, 2015). This can be especially useful as many dietary reference values fail to account for competitive athletes needs. A low EA can come from either not eating enough, too high energy expenditure or a combination of both. Either will subsequently lead to a detriment in performance and health. This is something you need to pay particular attention to when training phases change and volume and intensity increases or decreases, especially in a demanding sport like CrossFit. So eat enough!!


However, for EA to be accurate you need to be able to accurately measure energy expenditure, which is not very easy especially when workouts are so all so different! There is also always going to be a discrepancy between what you think you’re eating, what you think you’re expending and what’s actually happening. So rather than worrying about being too strict, an easier way is to simply calculate the estimated energy expenditure based on your training volume (activity multiplier).

Activity multipliers

• Sedentary = BMR x 1.2 (little or no exercise, desk job) • Lightly active = BMR x 1.375 (light exercise/ sports 1-3 days/week) • Moderately active = BMR x 1.55 (moderate exercise/ sports 6-7 days/week) • Very active = BMR x 1.725 (hard exercise every day, or exercising 2 xs/day) • Extra active = BMR x 1.9 (hard exercise 2 or more times per day, or training for marathon, or triathlon, etc.

(K-state.edu, n.d.)

Like your BMR, this number will not be entirely accurate where some elite competitors will have activity factors higher than those mentioned. This is why it should only be used as a starting measure, but nothing else. This is also why I wouldn’t worry about TEF as it’s roughly only 10% of TEA , especially considering the number you calculate is only an estimation anyway.

You could also cross reference this figure with a fitness wearable (smart watches/Fitbits) which can give you an idea about your energy expenditure for the day although there is a high degree of inaccuracy (Kaewkannate and Kim, 2016) so take it with a pinch of salt.

So don’t worry too much about what calculations you use and what numbers they give you. Instead, it’s the monitoring of performance, recovery and body composition metrics, then adjusting your intake based on these numbers that matter most.

What about body composition?

There is clearly a relationship with body composition and performance in functional training. Better body composition will:

  • Optimise power to weight ratio

  • Low energy cost of movement

  • Increase speed and agility

  • Move your body within smaller spaces in some of your gymnastic movements

(Nutrition and athletic performance, 2016).


A stronger athlete is a better athlete after all.

A common problem with training for competitive fitness is that due to the heavy energy demands in terms of both volume (a lot of sessions) and intensity, it is very easy to under-eat when trying cut weight making it unwise to focus on this as your primary goal. A low EA will only negatively effect performance and health. This is why if body composition is an area that needs improvement then a carefully periodised strategy over the season should be implemented rather than a short term plan. The 'slow and steady wins the race' mantra certainly holds true here whereby small adjustments based on your training will ultimately bring about long term success.

Or, try and focus on one particular goal at a time whether it be eating for weight loss, eating to build muscle, strength or to perform at your best.

If you do compete It makes sense to 'programme body comp goals in the base phase of training or well out of competition to minimise loss of performance' (Nutrition and Athletic performance, 2016), where there should also be an emphasis on preserving muscle mass whilst reducing fat mass.

A sensible approach is to minimise the rate of weight loss by creating only a modest kcal deficit of around 250-500kcals per day or slightly increase energy expenditure (Hall, 2007). A high protein intake will also help maintain muscle even though you are in this deficit (Phillips, 2014). Although there is only limited data is available, fat loss from a small reduction in energy intake (0.02%-5.8% drop in BW over 30 days) does not seem to hamper performance (Slater/Rice (2014). However, other studies have shown even a small drop in bodyweight can impact aerobic, anaerobic performance and hormone levels highlighting how this is area you must pay close attention to. When operating in a kcal deficit you must also consider other overlapping factors that may affected performance including glycogen availability, over training, chronic energy restriction, heat or dehydration.

If weight gain is the goal, then operate a similar sensible approach to prevent unnecessary fat gain (Israetel, Case and Hoffmann, 2016). A general rule of thumb would be to increase your kcals by around 500-1000kcals where you can adjust it depending on how aggressive you want to be.

Like with most nutrition strategies, the important point is to operate on a case by case basis where individual differences, goals. day to day training, competition cycle (eating for competition will be very different to your off season), preferences and history should be accounted for where trial and error, continued monitoring and reassessment should be used to build a better long term strategy. Stay flexible and use recovery, performance and body composition metrics to dictate alterations in your plan going forward. Try to ere on the side of eating too much than not enough as a decrement in performance will be far less desirable than a slower rate of fat loss.

To sum up - Steps to determining energy balance:

  1. Calculate your BMR

  2. Multiply by your activity level. You can change this daily.

  3. Alter depending on your body composition goals (this should only be done earlier on in the competitive season). If your goal is weight loss reduce by 250-500kcals. If your goal is muscle gain then increase by 500-1000kcals per day

  4. Use recovery, performance and body composition metrics to monitor and adjust your needs going forward

Or let us do it for you! To save you the hassle of working this out the above for yourself, why not sign up to our FREE kcal and macro calculator.


Free kcal and macro calculator

References

  • Beckham, S. (1999). THE METABOLIC COST OF FREE WEIGHT CIRCUIT TRAINING. Medicine & Science in Sports & Exercise, 31(Supplement), p.S109.

  • Hall, K. (2007). What is the required energy deficit per unit weight loss?. International Journal of Obesity, 32(3), pp.573-576.

  • Israetel, M., Case, J. and Hoffmann, J. (2016). The Renaissance Diet. 1st ed.

  • Kaewkannate, K. and Kim, S. (2016). A comparison of wearable fitness devices. BMC Public Health, 16(1).

  • Kliszczewicz, B., Snarr, R. and Esco, M. (2014). METABOLIC AND CARDIOVASCULAR RESPONSE TO THE CROSSFIT WORKOUT ‘CINDY’: A PILOT STUDY. Journal of sport and human performance, 2(2), pp.2-6.

  • K-state.edu. (n.d.). Physical activity and controlling weight. [online] Available at: https://www.k-state.edu/paccats/Contents/PA/PDF/Physical%20Activity%20and%20Controlling%20Weight.pdf [Accessed 14 Dec. 2016].

  • Loucks, A., Kiens, B. and Wright, H. (2011). Energy availability in athletes. Journal of Sports Sciences, 29(sup1), pp.S7-S15.

  • Nutrition and Athletic Performance. (2015). Medicine & Science in Sports & Exercise® and in the Journal of the Academy of Nutrition and Dietetics, and the Canadian Journal of Dietetic Practice and Research., (Position Stand).

  • Paige E. Babiash, (2013). DETERMINING THE ENERGY EXPENDITURE AND RELATIVE INTENSITY OF TWO CROSSFIT WORKOUTS. College of Exercise and Sport Science Clinical Exercise Physiology, p.8.

  • Phillips, S. (2014). A Brief Review of Higher Dietary Protein Diets in Weight Loss: A Focus on Athletes. Sports Medicine, 44(S2), pp.149-153.

  • Shephard, R. (2012). 2011 Compendium of Physical Activities: A Second Update of Codes and MET Values. Yearbook of Sports Medicine, 2012, pp.126-127.

  • Smith, M., Sommer, A., Starkoff, B. and Devor, S. (2013). Crossfit-Based High-Intensity Power Training Improves Maximal Aerobic Fitness and Body Composition. Journal of Strength and Conditioning Research, 27(11), pp.3159-3172.

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