Every published program and every pro routine is built around an average. Averages are useful for designing a starting point, yet no athlete is actually average. This article explains how wide the range of responses really is and what drives it, including how to tell a true non-responder from a kid who just had a bad testing day.

How different can responses to the same training be?

Very. In one of the largest studies of its kind, 585 adults did the same 12-week progressive strength program for the elbow flexors of one arm. One-rep max gains ranged from 0 to 250 percent. Muscle size changes ranged from a 2 percent loss to a 59 percent gain [1]. Same program, wildly different results.

The spread of results from one identical strength program. One-rep max gains ran from zero to 250 percent, and muscle size from a 2 percent loss to a 59 percent gain. Source: [1] Hubal 2005

Endurance training shows the same pattern. In the HERITAGE Family Study, 481 previously sedentary adults trained for 20 weeks. The average aerobic capacity gain was about 400 mL per minute, but some people gained little or nothing while others gained more than a liter per minute. The researchers estimated that up to 47 percent of the variation in response was heritable [7].

Up to 47 percent of the differences in how much aerobic capacity people gained from the same 20-week program was estimated to be heritable. Source: [7] Bouchard 1999

No study has measured this spread for pitching velocity specifically, but there is no reason to expect throwing to be the exception. Driveline reports something similar from its own athletes: after overload-ball training, some threw the regulation ball faster and others slower, with results they describe as fairly split [9].

Why do athletes respond differently?

A review by Mann, Lamberts and Lambert pulls together the main reasons [2]. It focuses on endurance training, but the factors apply broadly:

  • Genetics, which influence both where you start and how much you adapt.
  • Starting point. An untrained 14-year-old has more room to improve than a pitcher who has lifted for four years.
  • Relative dose. The same absolute program is a bigger relative stress for some athletes than others, so they effectively get a different stimulus. Twenty-five throws at 150 feet is a modest day for a strong 18-year-old and a big one for a 13-year-old who rarely throws past 90.
  • Recovery and lifestyle, including sleep, psychological stress, nutrition and everyday activity, which decide how much of each session turns into adaptation.

Bondarchuk saw individual differences in timing as well. After a program change, some of his athletes improved first, some held steady and some temporarily lost form, and they peaked on different days after rest [10].

Some "non-responders" are just noise

The review above adds one more factor, and it is the one parents should remember most: measurement error [2]. Statisticians have shown that day-to-day variation and testing noise can make individual differences look much larger than they are, sometimes accounting for all of the apparent spread [3, 4]. True individual differences can only be shown against the variability of a control group or with repeated testing.

For a pitcher, that means a single radar session after a program cannot label him a responder or a non-responder. A cold day, a poor night of sleep, a different device or a different drill can all move a reading by a mile or two an hour. Trends across several sessions on the same drill are what count.

Illustrative: one pitcher's readings over eight sessions. A single reading can swing a mile or two an hour, so session 5 alone would mislabel him. The trend across sessions shows the real direction. Source: [3] Atkinson 2015, [4] Hecksteden 2015

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Why birthday age misleads

Bompa bases how much training an athlete can tolerate on biological age (maturation) rather than calendar age, along with training age, health, recovery and outside stress such as exams [5]. He also notes that younger athletes tolerate higher volume at moderate loads better than high intensity [5].

Two 14-year-olds can be years apart physically. One may be through his growth spurt with a man's frame, the other still waiting for his. Putting them on the same intensity targets asks very different things of each. Our article on bio-banding in youth baseball explains how maturity shapes performance, and velocity by age shows how wide the normal range is at each age.

Champions are not average

Zatsiorsky warns that copying a champion's program has failed countless times, and offers a blunt reason: "champions are not average" [6]. The useful move is to borrow the principles behind elite programs and set the numbers for the athlete in front of you. Kiely makes a related case from the research side: because responses vary so widely, plans should respond to the athlete rather than be fixed months in advance [8]. In practice, the program is a hypothesis about what this athlete needs, and the data from the next few weeks either supports it or tells you to adjust.

How to individualize a pitching program without guessing

Individualizing starts from good defaults and lets the athlete's own data steer. Nobody needs to invent a program from scratch for every kid. A simple process (our framing, built from the research above):

  1. Start from a solid template matched to the pitcher's biological age and training age.
  2. Pick a few repeatable measures: velocity on a fixed drill, loads on one or two main lifts, morning bodyweight and a short daily readiness check.
  3. Retest on a schedule, under the same conditions, and judge the trend across several sessions.
  4. Respond to the trend. Progressing: keep the block. Stalled for two to three weeks: change the load first, then the exercises. Regressing with fatigue signs: unload.

Part 7 of this series covers exactly what to measure and how. Parts 2 and 5 explain how to change the load and change the exercises when the trend stalls.

For parents: my kid did not gain velocity

Before deciding a program "doesn't work" for your son or daughter, check the basics. Is the pitcher sleeping eight to ten hours? Eating enough to grow and train? In the middle of a growth spurt? Carrying extra stress from school? Then look at several measurements rather than one. Kids grow in bursts, and velocity often follows the same pattern. A flat stretch during rapid growth is common and usually temporary. Our youth pitcher development guide covers what patience looks like in practice.

What to do this week

Choose your two or three key measures and record a baseline this week under consistent conditions: same drill, same warm-up, same device and a similar time of day. Put the next retest on the calendar three or four weeks out. Until then, judge the program by how the athlete is recovering and let single readings go.

Frequently asked questions

Why does my teammate gain velocity on the same program and I do not?

People respond very differently to identical training because of genetics, starting point, the relative size of the dose, and recovery factors like sleep and stress [1, 2]. Measurement noise can also make a real gain look like no gain.

Are some pitchers non-responders to training?

Some athletes respond less to a given program, but a single test can falsely label someone a non-responder. Only repeated measurements or comparison with a control group can separate real differences from noise [3, 4].

Should young pitchers be trained by age or by maturity?

Bompa recommends basing training tolerance on biological age and training age rather than birthday age alone, since two athletes of the same age can be years apart physically [5].

Should I copy a pro pitcher’s program?

Borrow the principles and build your own numbers. Zatsiorsky notes that copying champions’ programs has failed repeatedly because champions are not average athletes [6].

Individualize with data

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Pitch AI tracks your workload and can pull back volume when your Wellness Check-In says you're not fresh. It also tracks your peak velocity trend and logs every strength session, so you can judge progress by trends instead of single days.

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References

  1. Hubal MJ, Gordish-Dressman H, Thompson PD, et al. (2005). Variability in muscle size and strength gain after unilateral resistance training. Medicine and Science in Sports and Exercise, 37(6), 964-972. https://pubmed.ncbi.nlm.nih.gov/15947721/
  2. Mann TN, Lamberts RP, Lambert MI (2014). High responders and low responders: factors associated with individual variation in response to standardized training. Sports Medicine, 44(8), 1113-1124. https://doi.org/10.1007/s40279-014-0197-3
  3. Atkinson G, Batterham AM (2015). True and false interindividual differences in the physiological response to an intervention. Experimental Physiology, 100(6), 577-588. https://doi.org/10.1113/EP085070
  4. Hecksteden A, Kraushaar J, Scharhag-Rosenberger F, et al. (2015). Individual response to exercise training: a statistical perspective. Journal of Applied Physiology, 118(12), 1450-1459. https://doi.org/10.1152/japplphysiol.00714.2014
  5. Bompa TO, Haff GG (2009). Periodization: Theory and Methodology of Training, 5th ed. Human Kinetics.
  6. Zatsiorsky VM, Kraemer WJ (2006). Science and Practice of Strength Training, 2nd ed. Human Kinetics.
  7. Bouchard C, An P, Rice T, et al. (1999). Familial aggregation of VO2max response to exercise training: results from the HERITAGE Family Study. Journal of Applied Physiology, 87(3), 1003-1008. https://doi.org/10.1152/jappl.1999.87.3.1003
  8. Kiely J (2012). Periodization paradigms in the 21st century: evidence-led or tradition-driven? International Journal of Sports Physiology and Performance, 7(3), 242-250. https://doi.org/10.1123/ijspp.7.3.242
  9. Boddy K, Daniels M (2017). Hacking the Kinetic Chain: Advanced Pitching. Driveline Baseball.
  10. Bondarchuk AP (2010). Transfer of Training in Sports, Vol. II. Trans. Yessis M. Ultimate Athlete Concepts.

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