Interview with a Sports Nutritionist: What Elite Athletes Get Wrong About Calories

You would think that elite athletes, the people who dedicate their entire lives to physical performance, would have nutrition figured out. They have coaching staffs, team doctors, and access to the best sports science available. Surely they know how to eat.

According to Dr. Marcus Rivera, they often do not.

Dr. Rivera is a Board Certified Specialist in Sports Dietetics (CSSD) with 14 years of experience working with Olympic track and field athletes, professional MMA fighters, and elite endurance runners. He has consulted for two Olympic training centers, worked ringside at UFC events, and designed fueling strategies for athletes competing in ultramarathons across six continents. His client list includes medalists, title holders, and world record contenders.

And his biggest professional frustration? Even at the highest levels of sport, athletes consistently misunderstand the most fundamental concept in nutrition: calories.

We sat down with Dr. Rivera for an in-depth conversation about the calorie mistakes he sees among elite performers, why undereating is more dangerous than most athletes realize, how periodized nutrition changes everything, and where AI-powered tracking tools are starting to reshape how professionals approach sports nutrition.

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The Interview

Q: Dr. Rivera, you have worked with some of the most elite athletes in the world. What is the single biggest calorie-related mistake you see them make?

A: Undereating. Without question. I know that surprises people because the public perception of athletes is that they eat enormous amounts of food, and some do. But the most common and most damaging mistake I encounter, across every sport, is chronic energy deficiency.

Athletes undereat for different reasons depending on the sport. In weight-class sports like MMA and wrestling, there is an obvious incentive to keep body weight low. In endurance sports, athletes often believe that being lighter automatically means being faster. In track and field, particularly in events like high jump or the aesthetic-adjacent events, there is cultural pressure to maintain a lean physique.

But here is the critical point: these athletes are not skipping meals because they are lazy. They genuinely believe they are eating enough. They look at their plate and think it is adequate. What they do not realize is that their energy expenditure is so far above that of a normal person that their intuition about food volume is completely miscalibrated.

I had an Olympic 1500-meter runner who was eating what most people would consider a generous diet, around 2,400 calories a day. She looked at her meals and saw plenty of food. But when we actually measured her training expenditure, she needed closer to 3,200 calories on hard training days. She had been running an 800-calorie daily deficit for months without knowing it. Her performance plateau, her recurring stress fractures, her disrupted menstrual cycle, they all traced back to that gap.

Q: Is the problem that athletes are not tracking at all, or that they are tracking incorrectly?

A: Both, but in different populations. The MMA fighters and bodybuilders I work with tend to track, but they track obsessively and often inaccurately. They will weigh their chicken breast raw, then cook it in oil and not count the oil. They will track every gram of protein but completely ignore the calories in their pre-workout supplements, their recovery shakes, or the handful of almonds they grab between sessions. The selective nature of their tracking creates blind spots.

Endurance athletes, on the other hand, frequently do not track at all. There is a culture in distance running and triathlon that views calorie counting as unnecessary or even counterproductive. The attitude is, "I run 80 miles a week, I can eat whatever I want." And for maintaining body weight, that might be loosely true. But for optimizing performance, recovery, and long-term health, "whatever I want" is not a strategy. It is a gamble.

The track and field athletes I have worked with at Olympic training centers fall somewhere in between. Many of them have a general sense of their macros but lack precision around total energy intake. And in a sport where the difference between making the Olympic team and missing it can come down to fractions of a second, that imprecision has real consequences.

Q: You mentioned that undereating is more common than overeating. Can you explain the performance consequences in more detail?

A: Relative Energy Deficiency in Sport, which the IOC now refers to as REDs, is one of the most significant and underrecognized problems in elite athletics. It used to be called the Female Athlete Triad, but the updated framework acknowledges that it affects men as well, and that its consequences extend far beyond the three original components.

When an athlete chronically undereats relative to their training load, the body starts making triage decisions. It does not have enough energy to support all of its systems at full capacity, so it starts shutting things down in order of survival priority.

The first things to go are the systems that are not immediately essential for survival: reproductive function, bone density maintenance, immune function, and tissue repair. An athlete might not notice this at first. They might even feel fine for weeks or months. But underneath, they are accumulating damage.

Here is what I typically see in a chronically underfueled athlete:

Bone stress injuries become recurring. I have worked with runners who had three or four stress fractures in two years, and in every case, their energy intake was inadequate. The body cannot maintain bone density when it is in a sustained calorie deficit.

Hormonal disruption is widespread. In women, this manifests as menstrual irregularity or amenorrhea. In men, testosterone levels drop, sometimes to levels you would normally see in men twice their age. Both of these directly impair recovery and adaptation to training.

Immune suppression leads to frequent illness. I had an MMA fighter who caught every cold and respiratory infection that went around his gym. He was convinced the gym was unsanitary. It turned out he was eating 2,800 calories a day while burning close to 4,000 in double training sessions. Once we corrected his intake, the chronic infections resolved within two months.

Paradoxically, the athlete often gains body fat. When the body is in sustained energy deficit, it downregulates metabolism and preferentially stores any excess intake as fat rather than directing it toward muscle repair. So the athlete is undereating, losing muscle, and gaining fat simultaneously. They respond by eating even less, which makes the problem worse.

Q: That last point seems counterintuitive. Can you explain the mechanism?

A: It is counterintuitive, and it is one of the hardest things to get athletes to accept. They come to me frustrated because they are eating "clean" and training hard but their body composition is moving in the wrong direction. When I tell them they need to eat more, I can see the disbelief on their faces.

The mechanism is straightforward from a physiological standpoint. When the body detects sustained energy deficit, it increases cortisol production. Cortisol is catabolic, meaning it breaks down tissue, and it preferentially targets muscle protein. At the same time, chronically elevated cortisol promotes visceral fat storage. This is an ancient survival mechanism. The body is preparing for famine by preserving its most energy-dense storage medium, which is fat, while metabolizing the most metabolically expensive tissue, which is muscle.

The practical result is that an underfueled athlete ends up lighter on the scale but with a worse power-to-weight ratio. They have less muscle to produce force and more fat that is not contributing to performance. Their metabolic rate drops because muscle is metabolically active and fat is relatively inert. So the deficit that initially caused the problem now becomes self-reinforcing. They need fewer calories because they have less muscle, but they are still training at the same intensity, so they need more calories from that standpoint. It becomes a vicious cycle.

The fix is always counterintuitive. You have to eat more to get leaner. It does not work overnight. It takes 8 to 12 weeks of sustained adequate fueling for the hormonal environment to normalize and for the body to start prioritizing muscle maintenance over fat storage again. During that period, the athlete might gain a small amount of weight, which is psychologically difficult but physiologically necessary.

Q: Let us talk about the flip side. Do you ever see elite athletes who overeat?

A: Absolutely, though it tends to cluster in specific sports and situations. The pattern I see most often is what I call "license to eat" syndrome. An athlete finishes a brutal three-hour session and thinks, "I earned this," then consumes 2,500 calories in a single post-workout meal when the actual expenditure from the session was 1,200.

I worked with a professional rugby player who was gaining body fat despite training harder than ever. His post-training meals were averaging 2,800 to 3,200 calories. He had no frame of reference because he had never tracked anything. He just ate until he felt like he had "replaced" the energy, and his perception was wildly inaccurate.

The more subtle form of overeating that I encounter among elite athletes is nutritional noise. An athlete will dial in their three main meals perfectly but then accumulate 400 to 700 extra calories per day from sources they do not think of as food: sports drinks during training, recovery shakes, protein bars between sessions, the peanut butter they add to their smoothie, the olive oil they drizzle on their salad. Each of these items is individually small, but collectively they can push an athlete well above their energy needs on rest days or light training days.

Human intuition about caloric intake is remarkably poor. Research shows that even trained dietitians underestimate meal calories by 10 to 15 percent when eyeballing portions. For athletes with no nutrition education, the error margin can be 40 to 60 percent.

Q: Can you explain periodized nutrition and why it matters for calorie management?

A: Periodized nutrition means adjusting your calorie and macronutrient intake to match the demands of your training cycle. It sounds obvious when you say it out loud, but the reality is that most athletes eat roughly the same amount every single day regardless of whether it is a heavy training day, a light recovery day, or a full rest day.

Consider a marathon runner whose weekly training includes two high-intensity interval sessions, one long run, two moderate-effort runs, and two rest days. On a long-run day, they might burn 3,500 total calories. On a rest day, they might burn 2,000. If they eat 2,800 calories every day, which is the average, they are underfueled on their hardest days and overfueled on their rest days. They get the worst of both worlds.

The better approach is to think of calorie intake on a spectrum that tracks with training load. On high-intensity or long-duration training days, carbohydrate intake should be elevated to support glycogen replenishment, and total calories should be at or slightly above expenditure. For an elite endurance athlete, this might mean 3,200 to 3,600 calories with carbohydrates providing 55 to 65 percent of total energy. On moderate training days, total intake comes down modestly. Carbohydrates decrease while protein stays consistent to support ongoing muscle repair. On rest and recovery days, total intake drops further, but protein actually increases slightly. The body does most of its structural repair during rest, and it needs amino acids to do that work.

I will give you a concrete example from one of my MMA fighters preparing for a title fight. Twelve weeks out, during the high-volume phase of camp, we had him at 3,400 calories per day with protein at 2.2 grams per kilogram of body weight, carbohydrates high because he was doing two sessions a day six days a week, and fats moderate. At eight weeks out, as intensity increased but volume slightly decreased, we adjusted to about 3,100 calories. Protein stayed the same, carbohydrates dropped slightly, and we increased fats because his training shifted toward more skill work and less pure conditioning. At three weeks out, we began a controlled weight cut. Calories dropped to 2,400, carbohydrates were significantly reduced, protein increased to 2.6 grams per kilogram to preserve lean mass, and we carefully managed sodium and water intake.

A common mistake is cutting protein on rest days because the athlete "did not train." The training stimulus already happened. The rest day is when the adaptation occurs, and that adaptation requires protein. I would estimate fewer than 10 percent of elite athletes I encounter actually adjust their nutrition to match their training periodization. The rest are winging it.

Q: How do you approach calorie tracking with your athletes in practice?

A: My approach has evolved significantly over the past five years. Early in my career, I would give athletes a meal plan and expect them to follow it. This works for about two weeks, and then compliance drops off a cliff. Meal plans are rigid, they do not account for travel or social situations, and they require the athlete to eat specific foods at specific times, which is not compatible with real life.

Now, I focus on giving athletes calorie and macronutrient targets for different training day types, and then I let them choose the foods that fill those targets. This requires them to track what they eat, and it requires the tracking to be accurate and low-friction.

I have tried every tracking method imaginable. Food diaries on paper. Spreadsheets. Traditional calorie counting apps where you search a database and log every item manually. The problem with all of them is compliance. An MMA fighter who is training twice a day, attending media obligations, and managing the stress of an upcoming fight is not going to spend 15 minutes per meal searching for items in a database. The tracking has to be fast, or it will not happen.

This is where AI-based tools have made a meaningful difference. I started having some of my athletes use Nutrola about a year ago, initially because the photo-based logging was dramatically faster than manual entry. An athlete can take a photo of their plate, confirm or adjust the AI's identification, and move on in under 30 seconds. That speed difference sounds trivial, but it is the difference between an athlete who tracks consistently for six months and one who abandons tracking after two weeks.

Q: Has the shift to AI-powered tracking changed the quality of data you receive from athletes?

A: Significantly. The biggest change is consistency. When tracking is fast and low-effort, athletes actually do it every day, including on weekends, during travel, and on rest days. Those are exactly the time periods where nutritional blind spots tend to develop.

Before AI tracking, I would review an athlete's food diary and see meticulous logging from Monday to Friday, then nothing over the weekend. When I asked about it, the answer was always some version of "I ate pretty normally." That phrase is meaningless from a data standpoint. "Pretty normally" could mean anything from a perfect 2,800 calories to a 4,500-calorie day with post-training restaurant meals.

With tools like Nutrola, I now see seven-day data from most of my athletes. That seven-day picture reveals patterns that a five-day snapshot never could. I can see that an athlete consistently undereats on Mondays after a heavy Sunday long run, or that their protein intake drops by 30 percent when they travel for competitions. Those patterns are actionable. I can build specific strategies around them.

The other improvement is in portion accuracy. When athletes manually estimate portions, they tend to normalize everything. A large serving becomes "a serving." A heaping tablespoon becomes "a tablespoon." AI-based photo estimation is not perfect, but it is more consistent than human estimation, and it does not have the psychological biases that cause people to unconsciously minimize their intake.

Consider two athletes. Athlete A meticulously weighs every ingredient for two meals per day but skips the other three. Athlete B photographs every meal with an AI tracker, getting estimates that might be off by 8 to 12 percent, but captures all five meals. Athlete B gives me a dramatically more useful dataset. I can see patterns in their intake across the entire day. Consistency of tracking beats precision of tracking, every time.

Q: What are the biggest recovery nutrition myths you encounter among elite athletes?

A: The biggest myth is the 30-minute anabolic window, the idea that you must consume protein within 30 minutes of training or the session is wasted. This has been so thoroughly debunked by research at this point that it surprises me how persistent it is. A 2013 meta-analysis by Schoenfeld, Aragon, and Krieger in the Journal of the International Society of Sports Nutrition found that total daily protein intake is far more important than the specific timing of any single dose. The real window is four to six hours, and for most athletes eating regular meals, timing takes care of itself.

I had an Olympic shot putter so stressed about the 30-minute window that he was consuming over 1,500 calories in a three-hour post-training window: a shake immediately after, a full meal 45 minutes later, then his scheduled meal two hours after that. No wonder he was gaining body fat.

The second myth is that recovery nutrition is only about protein. Athletes fixate on protein at the expense of everything else. After a two-hour high-intensity session, an athlete's glycogen stores are substantially depleted. If they consume only a protein shake and skip carbohydrates, they are replenishing the structural repair materials but not the fuel stores. Their next session will suffer because they started it with partially depleted glycogen. I recommend a 3:1 or 4:1 carbohydrate-to-protein ratio in the post-training meal after high-intensity or long-duration sessions. For shorter or lower-intensity sessions, the ratio can shift toward more protein and fewer carbohydrates.

The third myth is that more protein is always better. There is a ceiling on the rate at which your body can utilize protein for muscle protein synthesis, roughly 0.4 to 0.55 grams per kilogram of body weight per meal, depending on the research you reference. Consuming 80 grams of protein in a single meal does not produce twice the muscle protein synthesis of 40 grams. The excess is simply oxidized for energy or converted to other substrates. For most athletes, spreading 1.6 to 2.2 grams per kilogram of body weight across four meals per day is more effective than loading it all into one or two massive protein meals.

Tracking tools are genuinely useful here because they make protein distribution visible. When I look at an athlete's daily log in Nutrola, I can immediately see whether their protein is evenly spread or clustered into one or two meals. That visual pattern makes the coaching conversation much easier.

Q: How do you handle the psychological aspects of calorie tracking with athletes, especially in sports with body image pressures?

A: This is something I take very seriously. Calorie tracking is a tool, and like any tool, it can be misused. In sports with weight-class requirements or aesthetic components, tracking can reinforce obsessive tendencies if it is not managed carefully.

My approach is to frame tracking as a performance tool rather than a restriction tool. The language matters. I never say "you need to stay under this number." I say "your training today requires this much fuel." The frame shifts from deprivation to performance optimization. The athlete is not limiting food. They are fueling work.

For athletes who show signs of disordered eating patterns, I adjust the approach. Sometimes that means removing calorie targets entirely and focusing only on macronutrient ratios. Sometimes it means having the athlete log their food but only sharing the data with me, not displaying calorie totals on their own screen. Sometimes it means pausing tracking entirely and working with a sports psychologist before reintroducing it.

The key principle is that tracking should reduce anxiety, not increase it. If an athlete feels more stressed after logging a meal than before, the tracking protocol needs to change. Data should empower decision-making, not drive fear.

Q: Is there a difference in how male and female athletes should approach calorie tracking?

A: Yes. Female athletes have unique considerations around the menstrual cycle and relative energy deficiency in sport. During the luteal phase, resting metabolic rate increases by 5 to 10 percent with a shift toward greater fat oxidation. A female athlete who eats the same thing every day is ignoring a significant physiological variable.

I adjust targets based on cycle phase. During the follicular phase, we emphasize higher carbohydrate intake to match the body's preference for carbohydrate as fuel. During the luteal phase, we increase total calories slightly and shift toward higher fat. These are modest changes, 100 to 200 calories and a few percentage points in macro distribution, but they add up over months. Tracking allows us to correlate performance with intake and cycle phase, revealing patterns specific to each individual.

Q: What role do you see AI and technology playing in sports nutrition over the next five years?

A: We are at an inflection point. For decades, sports nutrition has been limited by the quality of dietary data we could collect. Athletes either did not track, tracked inaccurately, or tracked diligently for two weeks and then stopped. Every intervention I designed was built on incomplete information.

AI tracking changes the data problem fundamentally. When an athlete can log a meal in five seconds by taking a photo, the compliance issue largely goes away. And when that data flows to me in real time, I can make adjustments on the fly instead of waiting for a weekly check-in where the athlete tries to remember what they ate on Tuesday.

But the bigger impact will come from pattern recognition at scale. Right now, I rely on my own experience and published literature to identify problems and design solutions. In the future, AI systems that have analyzed hundreds of thousands of athlete diets will be able to identify nutritional patterns associated with injury, performance decline, or optimal adaptation. Imagine an AI system that knows an athlete has a high-intensity interval session tomorrow morning, that they underslept the previous night, and that their glycogen stores are likely depleted based on yesterday's training and food intake. That system could proactively recommend a higher-carbohydrate dinner with specific food suggestions, timed to optimize glycogen replenishment before the morning session.

We are not fully there yet, but the pieces are coming together. Wearable devices provide continuous physiological data. Food tracking apps provide nutritional data. Training platforms provide load and performance data. The missing piece has been an intelligent layer that synthesizes all of these data streams into actionable guidance. I think that layer is going to mature rapidly.

I am cautiously optimistic. The technology is not a replacement for a qualified sports nutritionist. An AI can tell you how many grams of carbohydrate you ate. It cannot tell you that your mood has been off for three weeks and that might be related to low iron, or that you need to have a conversation about your relationship with food. The human element remains essential. But as a data collection and pattern recognition tool, AI is going to transform this field in the next five to ten years.

Q: If you could give one piece of calorie-related advice to every serious athlete, what would it be?

A: Stop guessing. Measure.

The athletes who make the fastest progress and sustain the best long-term health are the ones who actually know their numbers. Not roughly. Not approximately. Actually.

I understand the resistance. Tracking feels tedious. It feels obsessive. It feels like it should not be necessary for someone who has been competing for years. But the data consistently shows that even experienced athletes misjudge their intake by 20 to 30 percent. At the elite level, where margins are razor-thin, that level of error is the difference between PR performances and unexplained plateaus.

The tools available today make tracking less burdensome than it has ever been. Taking a photo of your plate and spending 20 seconds confirming the contents is not a significant time investment for the quality of information it provides. And when that data is reviewed by a qualified sports nutritionist who can contextualize it within your training program, it becomes one of the most powerful performance tools available.

Nutrition is the one variable in athletic performance that you have complete control over. You cannot control genetics, you cannot always control sleep quality, and you cannot control what your competitors do. But you can control what and how much you eat. Choosing not to measure that is choosing to leave performance on the table.

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Key Takeaways from Dr. Rivera

1. Undereating is more common and more damaging than overeating in elite athletes. Chronic energy deficiency leads to bone injuries, hormonal disruption, immune suppression, and paradoxical fat gain.

2. Periodized nutrition is non-negotiable at the elite level. Eating the same amount every day regardless of training load means being underfueled on hard days and overfueled on easy days.

3. The "anabolic window" is largely a myth. Total daily protein intake distributed across multiple meals matters far more than post-workout timing.

4. Tracking compliance improves dramatically when the process is fast. AI-powered tools like Nutrola reduce logging time to under 30 seconds per meal, which makes consistent seven-day tracking realistic even for busy athletes.

5. Protein distribution matters as much as total protein intake. Spreading protein across four meals is more effective for muscle protein synthesis than loading it into one or two meals.

6. Tracking should be framed as a performance tool, not a restriction tool. Language and framing matter, especially in sports with body image pressures.

7. AI is poised to move beyond data collection into intelligent interpretation and personalized recommendation. The integration of nutritional, physiological, and training data will reshape sports nutrition practice.

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Frequently Asked Questions

How many calories do elite athletes actually need per day?

It varies enormously by sport, body size, training volume, and season phase. A 60-kilogram female distance runner in heavy training might need 2,800 to 3,200 calories per day. A 120-kilogram male rugby forward could need 5,000 to 6,000. During the off-season, these numbers may drop by 15 to 25 percent. Most athletes significantly underestimate their actual needs. Working with a qualified sports nutritionist or using a reliable tracking tool to quantify intake against expenditure is the most practical way to determine individual requirements.

What is the best macro split for athletic performance?

There is no universal best split, but general guidelines fall in these ranges: protein at 1.6 to 2.4 grams per kilogram of body weight per day, carbohydrates at 5 to 10 grams per kilogram depending on training intensity, and fat at 25 to 35 percent of total calories. Strength athletes tend toward higher protein, while endurance athletes need more carbohydrates. The most important factor is that total calorie intake matches expenditure and that protein is sufficient for recovery. Individual experimentation within evidence-based ranges is more productive than following a rigid formula.

What is Relative Energy Deficiency in Sport (REDs)?

REDs is a syndrome caused by chronic insufficient calorie intake relative to training demands. Previously known as the Female Athlete Triad, the updated framework recognizes that it affects all genders and involves impairments across multiple body systems including bone health, hormonal function, immune function, cardiovascular health, and psychological wellbeing. It is diagnosed through a combination of clinical assessment, dietary analysis, and biomarker testing. Athletes experiencing recurring injuries, hormonal irregularities, or unexplained performance plateaus should be evaluated for REDs.

Is calorie tracking safe for athletes with a history of disordered eating?

This requires individualized assessment. For athletes with a current or recent history of disordered eating, rigid tracking can reinforce unhealthy restriction patterns. These individuals should work with a mental health professional and a sports dietitian before implementing any tracking protocol. For those who have recovered and developed a healthy relationship with food, tracking can sometimes be reintroduced as a neutral data-gathering tool. The key distinction is the individual's psychological relationship with the numbers: if calorie data creates anxiety or compulsive behavior, tracking is not appropriate.

How accurate are AI calorie tracking apps for athlete-sized meals?

Current AI-powered apps, including Nutrola, typically estimate calories within 5 to 15 percent of actual values for standard meals. Accuracy is higher for simple, clearly visible meals and lower for complex dishes or very large portions. Athletes consuming above-average portions can supplement photo-based tracking with manual adjustments for items the camera might underestimate, such as added oils or calorie-dense sauces. The consistency advantage of AI tracking, capturing every meal rather than only some, typically outweighs per-meal accuracy limitations.

Should athletes track calories year-round or only during certain phases?

A phased approach works well for most athletes. An initial education phase of four to eight weeks involves daily tracking to build awareness and establish baselines. After that, athletes can shift to periodic tracking, perhaps one week per month or during phases where precision matters most, such as pre-competition weight management. Over time, many athletes develop enough intuitive understanding that they can rely on general habits with occasional check-ins. The goal is to use tracking as a learning tool that builds internalized knowledge, not a permanent obligation.

What should athletes look for in a nutrition tracking app?

Key features include a large and accurate food database, the ability to save custom meals and recipes, macro tracking alongside calories, integration with wearable devices, and low-friction logging. AI-powered photo recognition significantly reduces logging time, which directly impacts long-term compliance. Athletes should also look for apps that support different calorie targets for different days, since periodized nutrition requires varying intake across the training week. Data sharing with coaches or nutritionists is valuable for athletes who work with support staff.