Tag Archives: tracking

Training Low

Carbohydrates are undisputedly ergogenic aids for endurance exercise training. There basically isn’t a single study out there that shows a negative effect of carbs on performance. So when going Low carb in training period, your training performance will suffer, either in volume, intensity or RPE (rating of perceived exertion). I finally managed to perform an analysis of my key training periods before Hawaii Ironman triathlon 2012 (High Carb) and before Hawaii 2013 (Low Carb), that confirmed my initial observations and findings from scientific literature.

I compared the last 14 weeks of training heading into Hawaii Ironman in 2012 or 2013 (three 4-week training blocks + 2-week taper), as this is considered the most important training period before Ironman race. In 2012 I was still on “traditional endurance” High Carb diet, in accordance with all guidelines and with no junk food. For 2013 season I changed to Low Carb nutrition at the start of the year, so the compared period in 2013 was well after adaptation to new nutrition (i.e. 8 months after the switch to Low Carb).

VOLUME COMPARISON

The first (and easiest) comparison is of course the volume of training, represented in km or hours.

B01101 Volume comparison

The numbers speak for themselves, as 11% reduction in total training time was hard to overlook even back when I was training for 2013 Hawaii. I averaged 3 h 03 min per day in 2012 and only 2 h 42 min per day in 2013. Only swim volume was greater in 2013, and that was due to broken ribs and arm lacerations in 2012, that limited my ability to swim. Both run (-18%) and bike (-18%) volumes were markedly lower in 2013, in accordance with previous observations, that I just couldn’t train that much. It wasn’t for the lack of time or motivation; it was just the volume that was killing me in 2013.

As far as the sleep goes, I averaged 9,0 hours of sleep per day in 2012 and 8,6 hours in 2013, so no major differences.

WORKOUT TYPE COMPARISON

The volume is only one determinant of training, with quality being probably more important. So the comparison of workout types may provide a better glimpse into changes between my 2012 and 2013 Hawaii preparation period.

B01102 workout type comparison

In running, I did a couple more interval training sessions and a couple of tempo and long distance workouts less in 2013 when compared with 2012. The major difference comes in other run workouts (i.e. recovery runs, “garbage miles”…), that I performed almost one third less in 2013! And the picture is almost identical for bike workouts in 2013, with the numbers of workout types quite similar except of “garbage miles” workouts (approx. one fourth less in 2013). So all in all, the quality of training was more or less comparable between 2012 and 2013, also confirming my initial feelings.

RPE, FATIGUE, WILLINGNESS TO TRAIN

As mentioned before, I also track Rating of perceived exertion, Fatigue and Willingness to train for every session. I assign a 0-9 value to each based on the following index:

Rating of perceived exertion Fatigue Willingness to train
1 – Very light
2
3 – Fairly light
4 – Moderate
5 – Somewhat hard
6 – Hard
7 – Very hard
8
9 – Maximum
1 – Feeling new
2
3 – Rested
4
5 – Average
6
7 – Tired
8
9 –Destroyed
1 – Very High
2
3 – High
4
5 – Average
6
7 – Low
8
9 – Zero

So another possible comparison between years could be based on RPE, Fatigue and Willingness to train criteria. RPE is excellent measure of how hard I went in each session (i.e. intensity) while Fatigue and Willingness to train are good indicators for overtraining status. By comparing these indicators for key workouts, I can get another view of the training quality.

I averaged these indicators for key workouts (i.e. interval, tempo or distance workouts) and for “garbage miles” workouts (i.e. all other).

B01103 RPE, FATIGUE, WILLINGNESS TO TRAIN

When looking through results, no difference appears in “garbage miles” workouts, whether they were run or bike workouts. This would indicate that intensity was the same as well as Fatigue level and Willingness to train. But when looking at averages from key workouts (i.e. intervals, tempos and distance sessions), the most notable difference is RPE, being quite higher in 2013 for both run and bike workouts. While on first thought this would indicate higher intensity and quality of key workouts in 2013, I would most probably ascribe that to typical characteristic of Low Carb training. Namely, for a given workout performed at lower muscle glycogen content (which is the case in Low Carb training) the RPE is higher at the same intensity or power. This fact is well established and proven in scientific literature, as subject always report higher RPE on Low Carb for the same workout intensity in comparison to High Carb.

Also, the track run workouts indicate the above mentioned fact of higher RPE at same pace as well. In 2012 I was performing 10x400m run repeats at 74 sec with average HR 150 bpm and 60 sec rest periods in between, while in 2013 I could only do 77 sec 10x400m repeats with average HR 150 bpm. But on 90 sec rests, so the overall intensity was substantially lower in 2013, albeit at higher RPE!

MY 2013 NUTRITION

Unfortunately, I do not have any nutrition data for the last 14 weeks before 2012 Hawaii when I was training High Carb Low Fat, but I would guesstimate that I was consuming well over 500 g of carbs per day. Probably more in 600 – 700 g region, as only my usual (cereal) breakfasts consisted of more than 200 g of carbs!

I started tracking my nutrition intake in 2013, so I have complete nutrition data for whole year. In last 14 weeks of training for Hawaii in 2013, my average daily carb intake was 199 g on 5.011 kCal consumption.

B01104 average nutrient intake

Average fat intake was 360 g, while protein at 231 g, which means that I got almost 2/3 of my energy from fat! As far as food groups goes, they averaged out as follows.

B01105 average food groups

CONCLUSION

Quite evidently, the most important training period (14 weeks before an Ironman) was lower in volume and at best similar with regards to quality in 2013 when compared to 2012. But as stated before, training performance is of minor importance with regards to race performance, as I train for races and not for training “bragging rights” 😉 The end result of different training approaches taken in 2012 and 2013 can be nicely summarized by the following graphic:

Comparison of 2012 and 2013 Ironman Hawaii race performances (2013 was Train low Race high Carb approach)

Comparison of 2012 and 2013 Ironman Hawaii race performances (2013 was Train low Race high Carb approach)

So where did this 38 minute (7%!) improvement come from? Some of it was evidently from better weather conditions, some were undoubtedly because of additional endurance training year, additional experiences… And I believe the major factor was also a change in nutrition. As far as I experienced until now, the Train Low Race High approach with regards to carbs has two major advantages:

  • Smaller reliance on carbs for fuel and correspondingly greater fat burning capacity, which means lower chances of bonking.
  • Greater training adaptation at lower (or the same) training stimulus (i.e. intensity and volume).

Especially the second advantage is most often overlooked and seldom mentioned. This may also be the consequence of quite limited research on this topic, as you can basically count studies that deal with this question on the fingers of one hand! But sadly, this advantage is in my opinion also one of major reasons, why people don’t stick with Low Carb training approach. They only see the reduction in performance in training, get scared and conclude that they are not suited to Low Carb.

In my opinion, based on my experiences gather so far and with regards to studied scientific literature, I could compare Train Low Race High Carb approach to altitude training. You are training at tougher conditions (higher altitude or lower muscle glycogen content) so that the races seem easier (sea level altitude or full muscle glycogen)!

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How I track my training

On 5th February 2000 I ran 3,7 km in the time of 15:45. This was my first entry into training log, which was in paper back then. 3.757 workouts later (until 2014) I get very nostalgic when holding those couple of papers that were my training log at that time. Now in the electronic age, I cannot hold my training log anymore as it is stored in a cloud. Being data geek, this is how I track my workouts.

My training log is of course in a form of Excel spreadsheet. The data entry sheet for specific year is arranged in rows, so that each row represents a date in a year. For each day I record the following things:

  • run training,
  • swim training,
  • bike training,
  • strength training,
  • In which part of the day workouts were performed (i.e. morning, AM, PM, evening),
  • weight,
  • and hours of sleep.

B00701 Daily data entry

For running sessions I firstly assign a label for the workout type, so that I can easily determine the intervals sessions, tempo sessions and long runs. Before the session numbers comes a brief description of the workout, while the numbers present duration, length, vertical gain, average and max HR and calories burned (as calculated by Polar watch).

B0070101 Run

Then I have 3 categories that present my Rating of perceived exertion, Fatigue and Willingness to train for that session. I assign a 0-9 value to each based on the following index:

Rating of perceived exertion Fatigue Willingness to train
1 – Very light
2
3 – Fairly light
4 – Moderate
5 – Somewhat hard
6 – Hard
7 – Very hard
8
9 – Maximum
1 – Feeling new
2
3 – Rested
4
5 – Average
6
7 – Tired
8
9 –Destroyed
1 – Very High
2
3 – High
4
5 – Average
6
7 – Low
8
9 – Zero

This allows me to assess my training / overtraining status. Furthermore, I also track in which running shoes I ran. The workout tempo and TSS (my Training Stress Score, more on that in a later post) are calculated automatically, and the yearly summary sits on the top of workout list.

I track swim training very unclearly, as I still haven’t found a suitable way to easily browse through main sets in a sea of drills. So I describe each workout in a list manner, then I note training duration and the total swim distance. I also note RPE, Fatigue and Willingness to train for that session and weather the swim was done in wetsuit.

B0070102 Swim

As with running, I first assign a label for workout type when logging cycling session. Then duration, distance, vertical climb, cadence, average power, HR and calories come, along with RPE, Fatigue and Willingness to train. At the end comes the notion of which bike, wheel set, tire and cycling shoes were used.

B0070103 Bike

I also track the type and reps / sets of strength exercises and their total duration.

B0070104 Strenght

On this sheet I also have some basic statistics of workouts I performed in the last week, month or in last specified days (i.e. number of workout, duration of workouts…). Beside this summary table is one very annoying cell, that shows me how many hours I am behind (or above) the planned weekly hours, which I have set at 21. If the cell is white, than I am on plan (at least based on duration), and if it is red, then I have some training to do.

B0070105 summary

This sheet in a workbook represents the data entry point, while I have some computed statistics on other sheets. They are weekly, monthly and yearly view sheets, which show weekly, monthly and yearly summaries.

B00702 Weekly view

B00703 Monthly view

B00704 Yearly view

I also have two other sheets, which show my cumulative yearly data for run / bike / swim volumes and run / bike / swim volumes in chosen time periods (i.e. in 30 days).

B00706 Cummulative view

B00705 Period view

Other various sheets include a list of all my races (122 up to this day), list and description of all my injuries, list of all my triathlon expenses, list of all my run track sessions and bike hill workouts and a list for yearly planning of training and races.

B00707 Races summary

B00708 Equipment summary

I find Excel really excellent program for my tracking purposes as it enables me any statistical analysis I choose. Over the last 10 year that I am using Excel, I updated this file gradually, adding various statistics and features along with some fancy formatting touches. This is the main reason for not using online programs like Garmin Connect or Strava as they limit me either in their statistics or at their presentation of the data.

I made a simplified version of my Excel spreadsheet for tracking triathlon training. Feel free to download and use it, if you find it useful!

Download “Training log” Training-log.xlsx – Downloaded 705 times – 257 KB

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Tracking body composition changes

Human body is composed of several materials, some of which are muscle, fat, bone, blood, urine… So measuring or tracking changes in body composition with weight scale is pretty much like observing total points scored in basketball games – 153 baskets scored doesn’t tell you who won and by how much! And when you factor also gut contents, gut microbioma (over 1kg in adults!), glycogen content (with all bound water), urine volume, hydration status… into body weight, the picture becomes quite messy.

Body fat caliper

Body fat caliper

So while I do track my body weight on daily basis (I am data geek, who thinks that even bad data is better than no data at all!), I now mostly rely on body fat measurements with skin caliper to track my body composition changes. The skinfold estimation method is based on measuring the skinfolds at several standardized body points to determine the subcutaneous fat layer. These measurements can then be converted into estimated body fat percentage by various equations. Although this method may not give you an accurate reading of real body fat percentage, it is very useful for tracking composition changes over a period of time. I mainly compare the skinfolds values (individual or the sum of values) over time and do not pay much regards to the estimated body fat percentage. All in all, the main goal is to reduce the subcutaneous body fat, so why not measure it directly!

The calipers are very cheap; you can even get electronic calipers for very reasonable prices! As previously described, I use mechanical caliper on 10 body locations (Chest, Abdominal, Thigh, Bicep, Tricep, Subscapular, Suprailiac, Lower Back, Calf and Midaxillary).

Skinfold measuring sites

Skinfold measuring sites

I made Excel spreadsheet for tracking my skinfolds, with body fat estimates from various equations from literature. The formulas used are from Parillo (9 sites), Jackson Pollock (7 sites), Jackson Pollock (4 sites), Ball (7 sites for general population), Faulkner (4 sites for athletes) and Wilmore (7 sites for athletes). But as stated earlier, I mainly check the skinfolds values.

On the next graph are represented my values from July 2013, when I started using caliper. I had average skinfold of 5 mm, and at just above 71 kg body weight the formulas estimated my body fat percentage to be in the range of just over 7%. Going into my A race of the year, Hawaii in October, I had a racing weight between 71 and 72 kg with 3,4 mm average skinfold (around 5,5% body fat). In my offseason (November, December) I gained back some weight to just over 75 kg and my average skinfold increased to just over 5mm. This indicates that most of my weight gain was due to muscle mass gain, in the range of 2 – 3 kg. Naturally, I also gained approx. 1 kg of body fat, mostly for insulation purposes 🙂 The increase in weight is intentional, as I am emphasizing strength work in this training period by performing a lot of leg and upper body strength work along with core strength exercises. The underlying reason is to build a solid foundation for demanding training sessions that will come later in the season.

My skinfold data with average body weight (red line) and average skinfold (green line)

My skinfold data with average body weight (red line) and average skinfold (green line)

So to summarize, I think the caliper is superior tool in comparison to weight scales for tracking body composition changes and far more useful in daily practice. That is if you are quite ambitious athlete, and need to lose only couple kg of body fat for that optimal race performance. When I will return to “normal” life without racing ambitions, I will gladly ditch the use of both weight scale and caliper and replace them with another proficient measuring device: my eyes!

So if you are an ambitious athlete, you can download my Excel spreadsheet for tracking body composition changes here:

Download “Body composition tracking spreadsheet” Body-Composition-Tracking.xlsx – Downloaded 1471 times – 69 KB

 

And  here are the preprinted notes for easier measurements:

Download “Skinfold measurement” Skinfold-measurement.doc – Downloaded 758 times – 509 KB

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My running shoes (so far)

I’ve used a lot of running shoes over the years, 39 to be exact. I have around 5 – 6 pairs in daily rotation that I cycle through depending on workout type. Currently they are:

  • Trainers for longer runs: Saucony Kinvara 4, Mizuno Sayonara
  • Tempo or quicker runs: Saucony Virrata
  • Speedwork: Saucony Gridtype A5
  • Barefoot: Vivobarefoot evo
  • Offroad and snow: Merrell Mix Master Aeroblock

As you can see, nowadays I run mainly in low drop and flexible shoes, as I believe that extra heel cushioning and pronation control affect the stride style and hence running economy in negative way. As a result, my foot strike has become more and more fore footed over the years and I believe that this was mainly the consequence of using lighter shoes with lower heel-to-toe difference. The graph bellow presents the average weight of shoes that I ran with over the years. My progression to lighter shoes was slow, where I managed to drop the weight of shoes for about 100 grams (-30%) over the span of 5 years. As studies have shown, a 100 g reduction in running shoe weight presents approx. 1% improvement in running economy (~ 2 minutes at 3h marathon).

B00600 Average weight of shoesOtherwise, I started running in more conventional shoes in 2004. There were no “barefoot “or “minimalist” running shoes back then, so I was of course heavily influenced by marketing and “pronation control” dogma. So my early shoes were mainly pronation controlled Asics shoes, from 1000 to 2000 series and then finally to Kayano. Being overly cushioned shoes with pronation control, really heavy with large heel to toe height difference, I then started using 2 running shoes simultaneously. The second pair was usually a lighter trainer (i.e. Nike Elite) for races and speed work. In 2009 I made my first foray into minimalist running shoes with Nike Free shoes. I barely managed to run 5 km in them once per week, as I got sore calf muscles after every run in them. The next stepping stone in my transition to more minimalist running shoes were Saucony Mirage with their 4mm heel to toe drop. I really needed a couple of months to get used to running in them, but then I was hooked. Especially when I later progressed to Kinvara (4 mm drop) and now to Virrata (0 mm drop).

I am also quite nostalgic, as I took pictures of all my running shoes so far. Below is the collection of every running shoe I ever ran in. Brings back a lot of memories, when I look through the pictures. Hopefully you will recognize a model you ran in too!

 Mizuno Sayona #39 Mizuno Sayonara (2014)
Weight: 270 g
 (still in rotation) 85 km
 B00638 Saucony Kinvara 4 Kona #38 Saucony Kinvara 4 Kona (2013)
Weight: 250 g
(still in rotation) 163 km
 B00637 Saucony Virrata #37 Saucony Virrata (2013)  0 mm drop shoes, excellent for road speed work.
Weight: 220 g
(still in rotation) 488 km
 B00636 Asics Lyte33 v2 #36 Asics Gel Lyte33 2 (2013)  Asics approximation to Kinvara, bot not nearly there.
Weight: 264 g
(still in rotation) 706 km
 B00635 Saucony Grid Type A5 #35 Saucony Grid Type A5 (2013)  Excellent racing flats, for me even better than Asics Hyperspeed.
Weight: 183 g
Notable races: IM Hawaii 2013 (run split 2:57:04)
(still in rotation) 349 km
 B00634 Saucony Kinvara 2 #34 Saucony Kinvara 2  (2012)
Weight: 246 g
554 km
 B00633 Merrell Mix Master Aeroblock II #33 Merrell Mix Master Aeroblock (2012)  Trail running shoes for winter running.
Weight: 275 g
(still in rotation) 273 km
 B00632 Saucony Kinvara 2 #32 Saucony Kinvara 2  (2012)  Legendary shoes, really love them!
Weight: 246 g
Notable races: IM Lanzarote 2013 (run split 2:56:15)
615 km
 B00630 Vivobarefoot evo #30 Vivobarefoot evo (2012)  For barefoot style running, only 3 mm protection sole.
Weight: 226 g
(still in rotation) 128 km
 B00629 Mizuno Precision 12 #29 Mizuno Precision 12 (2012)
Weight: 308 g
945 km
 B00628 Saucony Mirage #28 Saucony Mirage (2012)  My first low-drop running shoes, excellent!
Weight: 306 g
797 km
 B00627 Saucony Fastwitch 5 #27 Saucony Fastwitch 5 (2011)
Weight: 269 g
Notable races: IM Florida 2011 (run split: 3:03:01)
476 km
 B00626 Asics DS Trainer 15 #26 Asics DS Trainer 15 (2011)
Weight: 335 g
671 km
 B00625 Brooks Racer ST4 #25 Brooks Racer ST4  (2011)
Weight: 271 g
656 km
 B00624 Asics 2150 #24 Asics 2150  (2011)
Weight: 366 g
700 km
 B00623 Nike LunarGlide 2+ #23 Nike LunarGlide2 + (2010)
Weight: 340 g
814 km
 B00622 Asics 2150 #22 Asics 2150 (2010)
Weight: 368 g
750 km
 B00621 Asics 2140 #21 Asics 2140 (2010)
Weight: 360 g
720 km
 B00620 Asics Hyperspeed 3 #20 Asics Hyperspeed 3 (2010)  Legendary racing flats!
Weight: 206 g
Notable races: New York marathon 2010 (2:40:13)
Rotterdam marathon 2011(2:37:45)
IM Austria 2012 (run split 3:12:38)
IM Hawaii 2012 (run split: 3:02:50)
(still in rotation) 530 km
 B00619 Brooks Racer ST4 #19 Brooks Racer ST4  (2010)
Weight: 285 g
Notable races: IM Frankfurt 2011 (run split: 3:05:04)
730 km
 B00618 Salomon XT Wings GTX #18 Salomon XT Wings GTX (2009)  Gore Tex trail running shoes for winter running, now used only for hiking due to high weight.
Weight: 434 g
308 km
 B00617 Nike Free 5.0 V4 #17 Nike Free 5.0 V4 (2009)  My first foray into minimalist running shoes.
Weight: 255 g
(still in rotation) 417 km
 B00616 Asics Kayano 15 #16 Asics Kayano 15 (2009)
Weight: 396,5 g
904 km
 B00615 Nike Zoom Elite 4 #15 Nike Zoom Elite+ 4 (2009)
Weight: 326 g
Notable races: Boston marathon 2009 (2:50:46)
1009 km
 B00614 Asics GT2130 #14 Asics GT2130 (2009)
Weight: 360 g
1052 km
 B00613 Asics Kayano 14 #13 Asics Kayano 14  (2009)
Weight: 397 g
1010 km
 B00612 Asics Kayano 13 #12 Asics Kayano 13  (2008)
Weight: 397 g
803 km
 B00611 Nike Zoom Elite 4 #11 Nike Zoom Elite+ 4  (2008)
Weight: 326 g
631 km
 B00610 Asics Kayano 14 #10 Asics Kayano 14 (2008)
Weight: approx 397 g
934 km
 B00609 Asics Racer #9 Asics Racer VII (2008)  My first racing flats!
Weight: 233 g
Notable races: Ljubljana marathon 2008 (2:55:32)
Berlin marathon 2009 (2:38:34)
(still in rotation) 833  km
 B00608 Asics Kayano 13 #8 Asics Kayano 13 (2008)
Weight: approx 397 g
1078 km
 B00607 Adidas Supernova Control 10 GTX #7 Adidas Supernova Control 10 GTX (2007)Gore Tex trail running shoes for winter running.
Weight: 400 g
681 km
 B00606 Nike Zoom Elite 3 #6 Nike Zoom Elite 3 (2007)  My first »faster« running shoes.
Weight: approx 326 g
Notable races: first marathon under 3 hr – Ljubljana marathon 2007 (2:59:08)
870 km
 B00605 Asics GT2120 #5 Asics GT2120 (2007)
Weight: approx 360 g
936 km
 B00604 Asics GT2110 #4 Asics GT2110 (2007)
Weight: approx 360 g
919 km
 B00603 Asics GT1110 #3 Asics GT1110 (2006)
937 km
 B00601 Nike Perseus 02 Nike Pegasus #2 Nike Pegasus (2005) and #1 Nike Perseus (2004)
986 km (Pegasus), 1056 km (Perseus)
Notable races: first marathon – Ljubljana marathon 2004 (3:46:36)
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Year in review – Training & Racing

I recently got reminded that the year 2013 ended and that it would be appropriate to publish also training data summary for the year, not just nutrition data. I basically do not view 1st of January as the start of season marker, as my 2014 season already started back in December 2013. But minor details aside, here are the summary data for 2013 season in comparison with all previous seasons.

My yearly totals

My yearly totals

The season 2013 could be summarized in one number as: -10%. That was my reduction in total training time. The reduction in training volume was highest at running (-18%) and was a consequence of my early season injury (raptured Achilles tendon in January). I was unable to run for 3 weeks, but recovered quite well after that, thanks also to excellent treatment of Tina Maze’s personal physiotherapist Nežka Poljanšek. Even though I increased my bike training at that period, my total bike training time fell by 8% in comparison to 2012. Swimming was more consistent this year, only 2% reduction in training time. I also did less strength work, -12% with regards to 2012. All in all, that corresponded to approx. 106 hours less training in 2013.

As far as the quality of training goes, I would rate it the same as in 2012, at best. My training performance was quite lower this year due to “Train low Race high” carbohydrate approach, as I’ve written previously. Not that I care, as the race results this year were markedly better, with AG win at Ironman Lanzarote (9th overall) and 2nd place AG (29th overall) in Ironman World Championship Hawaii. Even though the slower training times are a bit hard to swallow, the race times are what really count for me. This year in Hawaii I managed half hour faster bike split and went 5 minutes faster on the run for a sub 3h marathon!

Comparison of 2012 and 2013 Ironman Hawaii race performances (2013 was Train low Race high Carb approach)

Comparison of 2012 and 2013 Ironman Hawaii race performances (2013 was Train low Race high Carb approach)

Injury wise, 2013 was much kinder to me. Beside above mentioned Achilles injury, I only experienced 3 episodes of diarrheas and one instance of eye inflammation. When looking through the 2012 list, which consists of broken ribs, arm lacerations, sciatica pain, shin splints on both legs, multiple occasions of ear infections, couple of diarrheas, lower leg muscle strains…, I would say that 2013 was relatively injury free 🙂

So what so conclude of 2013? It was my best triathlon season so far, as everything from training, nutrition and race performance fell almost perfectly together. My new Low Carb nutrition approach was the major breakthrough for me in 2013, as I managed to implement it successfully in training and recovery. Consequently, my general well-being was better than in previous years, which resulted in optimal foundations for great race performance. The 2nd place in AG at Hawaiian Ironman was therefore confirmation of the correct approach and hard work.

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Tracking nutrient intake

This is one of the most frequent questions I received since starting this blog. It’s really quite simple, it only takes few ounces of effort per day for benefits that are quite substantial and greatly outweigh the extra labor. As of now, I have a complete list of everything I ate from 25th of November 2012, which is over a year worth of nutrition data. When this information is coupled with my training dairy, I can really evaluate the impact of nutrition on my performance and recovery, body composition and body weight…

Basically everything you need for successful nutrient tracking is a kitchen scale and spreadsheet application. And a bit of tips & tricks to minimize the time consumption. But first, the #1 used appliance in my home:

Kitchen scale

Kitchen scale, pre-printed paper note, pencil. And 190g tomato (5g carbs, 2g protein, 0g fat, 34 kCal)

Kitchen scale, pre-printed paper note, pencil. And 190g tomato (5g carbs, 2g protein, 0g fat, 34 kCal)

Nothing fancy, approx. €15 investment with a great cost-effectiveness ratio. Digital is of course better and besides, it’s harder to get analogue scale anyway. Just be prepared to change batteries often 😉

Being the most used item in my kitchen, it stands in the middle of my kitchen counter, so it is no problem to scale everything that goes into the dishes or directly into my mouth. Somewhere near are also a pencil and a block of paper for writing down the qualitative and quantitative composition of meals. This is the time for a tip that I foundnd very useful. I preprint small notes with usual foods I eat for breakfasts, snacks or launches, so when I weight things, I only need to put down the quantity. It might not seem much of an improvement, but when you think how many “macadamia”, “cottage cheese” and other long words it saves, it’s a big time saver on a cumulative scale. Along with food items and quantities I also note the time of meal consumption.

Although I eat vast majority of my meals are at home, there are inevitably some situations that prevent me the use of my kitchen scale, i.e. dinning out situations. The composition of those meals is of course less accurate, due to estimation quantities, but when you weight your every food for about a week, you quickly get a hang of quantities remarkably accurately. Let alone if you weight your food for a couple of months, this estimation is really no problem at all. I often even “play” with my assessment capabilities in the kitchen, estimating the weight of items before actually weighting them. And surprisingly, I am not far away in estimates for the items that I use the most.

Spreadsheet application

As described before in my blog, I developed my own spreadsheet for tracking nutrient intake in Microsoft Excel. Fundamentally, all you need is a list of foods with nutrient composition (carbs, protein, fat, kCal…) and a list of food that you ate. Linking them with a simple VLOOKUP functions and then summing data with a couple of array formulas then gives me summarized nutrition information for specific day, week or month. Just basic Excel formulas, no macros or visual basic programming needed. I only threw in some fancy conditional formatting and graphs that allow me easier analysis and interpretation of data. Additionally, I also implemented tracking various categories of foods (i.e. dairy, dairy products, vegetables, fruits, meat, fishes…), mostly just out of curiosity for how much of specific food groups I eat. I keep this spreadsheet in my Dropbox cloud, so I can access it from everywhere.

As far as nutrient composition of food goes, I get most of the information from Wikipedia, National Nutrient Database for Standard Reference, Wolfram alpha and food labels on food products. If everything above fails, then Google usually comes to the rescue.

Below are some screenshots from the spreadsheet I use.

Master index of food with nutrient composition

Master index of food with nutrient composition

Daily individual food intake, where I note only the date, time, food item and quantity. Nutrient composition is calculated via VLOOKUP function, and conditional formatting automatically separates the days and meals with borders

Daily individual food intake, where I note only the date, time, food item and quantity. Nutrient composition is calculated via VLOOKUP function, and conditional formatting automatically separates the days and meals with borders

Daily summary view, where the data on kCal, carb, protein and fat consumption per day along with some other information is shown

Daily summary view, where the data on kCal, carb, protein and fat consumption per day along with some other information is shown

Weekly summary view, where the data on kCal, carb, protein and fat consumption per week along with some other information is shown

Weekly summary view, where the data on kCal, carb, protein and fat consumption per week along with some other information is shown

Monthly summary view, where the data on kCal, carb, protein and fat consumption per month along with some other information is shown

Monthly summary view, where the data on kCal, carb, protein and fat consumption per month along with some other information is shown

All in all, I would estimate that additional labor for tracking nutrient intake takes me less than 5 minutes per day. I do not find this extra work troublesome as it has become a part of my daily routine. Basically, it’s the same thing as with every other “investment” in our lives: it’s not hard to do something if the benefits outweigh the effort.

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