Return to Sport: Why the Calendar Isn't the Criteria

Summary

It is understandable that professionals provide indicative timelines when athletes go down with a common lower limb injury. These timelines are grounded in real experience, but they are also averages, and averages hide the individual.

It is understandable that professionals provide indicative timelines when athletes go down with a common lower limb injury. Six weeks for this, three months for that. These timelines are grounded in real experience, but they are also averages, and averages hide the individual. Some athletes return quicker. Some take considerably longer. The honest answer to "when will they be back" has never really been a number of weeks, it has been a judgment call about when acceptable levels of function and performance can be observed. Often that judgment is subjective, made under pressure, with a coach and a club wanting a date.

As professionals, we should be aiming higher than that. We should be building objective, measurable, criteria-based progressions that run from the point of injury, through surgery where required, to the point of return. The technology to do this in the field, rather than only in a lab, now exists.

The baseline problem

Every return-to-sport decision is a comparison against something. The trouble is that most practitioners are comparing the injured athlete against a population average, a textbook range, or their own gut feel, because they never captured what that individual athlete's own output looked like before the injury happened.

Friction-resistance sled data changes that, provided it is collected before the injury, not after. If an athlete has been training on the DynaSled as part of normal programming, their pre-injury horizontal force output already exists as a personal reference point, not an estimate, not a population norm, their own number. If that data does not exist because the injury happened before the athlete was in the programme, we build the baseline from the uninjured limb and from position- and body-mass-matched norms instead. Neither approach is exotic. Both simply require deciding, in advance, that this data is worth collecting as a matter of course rather than only once someone gets hurt.

Walking, marching, sprinting: a progression we can now measure

For running-based athletes, the return-to-run progression has always followed a natural sequence: resisted walking, then marching, then sprinting. What has changed is our ability to load and measure each step of that sequence with the same tool, under the same friction resistance, producing directly comparable numbers throughout.

Ten metres of resisted walking at around 30% body weight. Ten metres of resisted marching, still no flight phase but meaningfully faster, at a similar load. Ten metres of resisted sprinting from a standardised stationary start at a lighter load, around 15% body weight. Each stage produces horizontal force data on the same scale as the last, so progression through rehab becomes a continuous, comparable curve rather than three disconnected tests using three different tools.

Programming by percentage, not by week

The shift this enables is straightforward to state and easy to under-value: programme by percentage of baseline, not by week of rehab. A session in week three might target 60% of the athlete's peak horizontal force at reduced velocity. Week six might push to 75%. These numbers are not arbitrary, they represent what the tissue can tolerate at that point in recovery, expressed in terms the tissue actually experiences, rather than in terms a calendar imposes on it.

This matters because friction-based resistance behaves differently to the alternatives. A motorised treadmill or a bungee-assisted rig can mask a propulsive deficit by contributing force the athlete did not produce. Friction resistance cannot do that. Every newton recorded is athlete-generated, which is precisely why the data stays clean enough to programme load increments as tightly as 10% of peak horizontal force per week through the mid-rehab phase. Confidence recovers faster than tissue does. The numbers are there to keep those two curves from getting confused with each other.

What we should actually be watching

Three outputs, tracked together, tell the real story: peak horizontal force, Symmetry Index, and rate of force development in early stance.

Peak force climbing without a corresponding improvement in symmetry usually means the athlete has found a compensation strategy on the uninjured limb rather than genuinely restoring capacity on the injured one. It looks like progress on one graph and hides a problem on another. RFD is the variable most likely to be ignored, and the one that predicts trouble when it is. An athlete can reach 90% of baseline peak force while still taking meaningfully longer to reach that peak than they did before the injury. In the first steps of a sprint, where propulsive demand peaks earliest and fastest, that lag is exactly the mechanical condition under which reinjury happens.

What objective clearance actually looks like

Clearance should never be one metric crossing a line. It is a profile, and every part of that profile has to hold up, not just most of it:

• Symmetry Index at or above 90%, across two consecutive sessions at least seven days apart
• Peak horizontal force within 5% of pre-injury baseline, or the contralateral limb average
• RFD in early stance within 10% of baseline and trending upward, not flat
• No pain or apprehension during maximal-intensity efforts
• A subjective confidence score of 7 or above on the ACL-RSI scale, where applicable

All five, not four of five. The one criterion an athlete hasn't cleared is, by definition, the one most likely to fail them first under sport-speed conditions.

The point of all this

None of this replaces clinical judgment. It replaces the guesswork that clinical judgment has too often been asked to carry alone, without the data to back it. When the athlete clears the profile above, the record of how they got there becomes two things at once: your protection, and the baseline for whatever comes next. Return to sport was never really the end of the story. With the right data behind it, it is the start of the next chapter in that athlete's force profile.

References

Paterno, M.V., Rauh, M.J., Schmitt, L.C., Ford, K.R., & Hewett, T.E. (2012). Incidence of contralateral and ipsilateral anterior cruciate ligament (ACL) injury after primary ACL reconstruction and return to sport. Clinical Journal of Sport Medicine, 22(2), 116-121.

Wiggins, A.J., Grandhi, R.K., Schneider, D.K., Stanfield, D., Webster, K.E., & Myer, G.D. (2016). Risk of secondary injury in younger athletes after anterior cruciate ligament reconstruction: A systematic review and meta-analysis. American Journal of Sports Medicine, 44(7), 1861-1876.

Morin, J.B., & Samozino, P. (2016). Interpreting power-force-velocity profiles for individualized and specific training. International Journal of Sports Physiology and Performance, 11(2), 267-272.