In an infographic.


Advances in the exercise sciences have had a profound influence on the way athletes train and prepare for competition. Scientific enquiry, however, has made only a modest contribution to our mastery of programming. Shrouded in mystique, this intricate craft has long been the domain of coaches, guided by experience, anecdotes and often dogma. Such a shortfall of the exercise sciences is hardly surprising; the complexity of the training process does not lend itself well to rigorous investigation. Nonetheless, there is one aspect of programming that has received quite extensive attention in the literature, apparently unbeknown to most coaches, and that is the taper.

It is actually relatively simple to track group of athletes’ fitness during a period of reduced training - that is, compared to analysing an annual training program, for example. The data and models generated by these studies have provided some quite unambiguous guidelines for tapering protocols, though these don’t seem to have reached the frontline of athletic training1. I’ve compiled the salient points from this research into the short infographic below. In addition, the graphic also addresses some pre-competition nutritional considerations, which are integral to any effective tapering strategy. Further information/elaboration can be found in the footnotes. You can view and/or download a high-resolution version HERE.

an infographic guide to tapering


Additional considerations for quantifying (total) training load

  • “Intensity”, as a measure of metabolic stress, does not increase linearly with output measures of “intensity” (i.e. HR, watts, pace…)5. If we assume that metabolic stress is well represented by blood lactate5, then clearly “stress” increases exponentially with “intensity” (at least beyond the lactate threshold). In order to correct for this a weighting factor (Y) should be introduced to the calculation of session load.

how to calculate training load accounting for nonlinearity of metabolic stress

  • Ideally, athletes should also factor in a gauge of “recovery”. While this may be somewhat considered under “frequency” (i.e. sessions/week = mean recovery period between sessions); in reality the recovery period between sessions will vary, and this can have a pronounced effect on the cumulative training load19.

summary of optimal pacing strategies An alternative summary of optimal tapering strategies from Mujika & Padilla (2003)

  • For simplicity’s sake, the infographic suggests that frequency merely be maintained. A more conservative recommendation, however, would be the one above: don’t reduce frequency any more than 80%. For example, Banister et al.5 reduced training frequency by 20% during the second week of a 2 wk taper.
  • The suggested load reduction of 40–60% was based largely on swimmers3, the optimum range for runners & cyclists might fall anywhere between 20-60% 3.

Individualising protocols

  • Including an overload period prior to a taper indicates both a longer taper period and a larger reduction in training load20 (in order to dissipate the additional fatigue).
  • Taper duration and (average) load reduction should be varied concurrently: that is, a shorter taper period warrants a greater load reduction, and vice versa20.

effect of prior training on the optimal tapering strategy

To rest or not to rest?

Modelled performances suggest that a day of complete rest prior to competition is not harmful to athletes5. However, I quote, “…the negative effects of complete inactivity are readily apparent in athletes”4. There is good physiological rationale behind this claim — most notably the rapid effects of inactivity on blood volume6. Furthermore, as described above, there is some (also model-based) evidence of enhanced performance following an increased training load immediately prior to competition9. Thus, at this stage, athletes are advised to experiment and find their own preference.


  1. Le Meur Y, Hausswirth C, Mujika I. Tapering for competition: A review. Science & Sports. 2012. doi: 10.1016/j.scispo.2011.06.013.
  2. Wenger HA, Bell GJ. The interactions of intensity, frequency and duration of exercise training in altering cardiorespiratory fitness. Sports Med. 3: 346–356, 1986.
  3. Bosquet L, Montpetit J, Arvisais D, Mujika I. Effects of tapering on performance: a meta-analysis. Med. Sci. Sports Exerc. 39: 1358–1365, 2007.
  4. Mujika I, PADILLA S. Scientific bases for precompetition tapering strategies. Med. Sci. Sports Exerc. 35: 1182–1187, 2003.
  5. Banister EW, Carter JB, Zarkadas PC. Training theory and taper: validation in triathlon athletes. Eur. J. Appl. Physiol. Occup. Physiol. 79: 182–191, 1999.
  6. Mujika DI, Padilla S. Detraining: Loss of Training-Induced Physiological and Performance Adaptations. Part I. Sports Med. 30: 79–87, 2000.
  7. Mujika I, Goya A, Ruiz E, Grijalba A, Santisteban J, Padilla S. Physiological and performance responses to a 6-day taper in middle-distance runners: influence of training frequency. Int. J. Sports Med. 23: 367–373, 2002.
  8. Hickson RC, Foster C, Pollock ML, Galassi TM, Rich S. Reduced training intensities and loss of aerobic power, endurance, and cardiac growth. J. Appl. Physiol. 58: 492–499, 1985.
  9. Thomas L, Mujika I, Busso T. Computer Simulations Assessing the Potential Performance Benefit of a Final Increase in Training During Pre-Event Taper. J. Strength Cond. Res. 23: 1729–1736, 2009.
  10. Hawley JA, Schabort EJ, Noakes TD, Dennis SC. Carbohydrate-Loading and Exercise Performance. Sports Med. 24: 73–81, 1997.
  11. Bergstrom J, Hermansen L, Hultman E, Saltin B. Diet, muscle glycogen and physical performance. Acta Physiol. Scand. 71: 140–150, 1967.
  12. Bussau VA, Fairchild TJ, Rao A, Steele P, Fournier PA. Carbohydrate loading in human muscle: an improved 1 day protocol. Eur. J. Appl. Physiol. 87: 290–295, 2002.
  13. Sherman WM, Costill DL, Fink WJ, Miller JM. Effect of exercise-diet manipulation on muscle glycogen and its subsequent utilization during performance. Int. J. Sports Med. 2: 114–118, 1981.
  14. Burke LM, Hawley JA, Schabort EJ. Carbohydrate loading failed to improve 100-km cycling performance in a placebo-controlled trial. J. Appl. Physiol. 88: 1284–1290, 2000.
  15. Karlsson J, Saltin B. Diet, muscle glycogen, and endurance performance. J. Appl. Physiol. 31: 203–206, 1971.
  16. Olsson KE, Saltin B. Variation in total body water with muscle glycogen changes in man. Acta Physiol. Scand. 80: 11–18, 1970.
  17. Oliveira Pires F, Silva A, Gagliardi J. Characterization of the blood lactate curve and applicability of the Dmax model in a progressive protocol on treadmill. Rev. Bras. Med. Esporte. 12: 61–65, 2006.
  18. Morton RH, Fitz-Clarke JR, Banister EW. Modeling human performance in running. J. Appl. Physiol. 69: 1171–1177, 1990.
  19. Stanley J, Peake JM, Buchheit M. Cardiac parasympathetic reactivation following exercise: implications for training prescription. Sports Med. 43: 1259–1277, 2013.
  20. Thomas L, Busso T. A theoretical study of taper characteristics to optimize performance. Med. Sci. Sports Exerc. 2005. doi: 10.1249/01.mss.0000177461.94156.4b.