Why Most Sprint Testing Is Producing Garbage Data (And What to Do About It)

Mark Fisher

⏱ 6 min read

Summary

Timing gates, radar guns, and timing systems are more common than ever. The protocols for using them correctly are not. Here's why most sprint test data is less reliable than coaches think—and how to fix it.

More coaches are timing their athletes than at any previous point in history. Timing gates are accessible. Radar guns are affordable. Apps measure split times on phones. This democratisation of timing technology is genuinely useful — but it has created a proliferation of sprint data that is far less reliable than the people interpreting it believe.

Protocol is the most controllable variable — and the most commonly neglected. But hardware quality also varies more than most coaches realise, and the two interact. Even the best protocol cannot fully compensate for a sensor that triggers inconsistently. Understanding both is necessary to produce data you can actually act on.

The Reliability Problem

Haugen et al. (2012) published a comprehensive analysis of sprint timing reliability across different equipment and protocols, and the findings should make any coach uncomfortable with their current data collection practices. The key result: fully automatic timing (FAT) systems produce dramatically less variability than hand-timing or gate-based systems with poor start protocols — but even gate-based systems can achieve acceptable reliability when used correctly.

The coefficient of variation (CV) for 10 m split times in poorly controlled conditions can exceed 5%. A 5% CV on a 1.7-second 10 m split is about 85 ms — far larger than the performance difference between well-trained and elite-level athletes. You are not measuring what you think you are measuring.

Not All Timing Gate Hardware Is Equal

The timing gate market is not homogeneous. The sensor at the heart of a timing gate determines how consistently and accurately it detects an athlete passing through the beam — and the approaches differ substantially in their engineering.

Most commercially available timing gates use a COTS (commercial off-the-shelf) photoelectric switch: a simple infrared break-beam sensor that triggers when the beam is interrupted. These sensors are inexpensive, proven in industrial applications, and adequate for many uses — but they are susceptible to false triggers from ambient light variation, vibration, and temperature-dependent drift in trigger threshold. Their performance degrades in variable outdoor lighting conditions, which is exactly where most sports testing happens.

Some systems use a simple laser pointer rather than an infrared LED. This improves beam directionality and reduces ambient light interference, but the trigger electronics are often still basic, and beam alignment sensitivity can introduce variability in real-world field conditions.

A more recent approach uses Time-of-Flight (TOF) laser chips, which measure distance to the target rather than relying on a reflector or receiver unit. This simplifies setup — no reflector pole required — and has potential advantages in some environments. Whether TOF systems match or exceed the timing accuracy of well-engineered traditional systems in sport timing applications is not yet established in peer-reviewed literature.

Swift Performance's G4 timing gates take a different approach: an optically and electronically filtered sensor system. The optical filter narrows the wavelength sensitivity of the detector, reducing susceptibility to ambient light. The electronic filtering stage further conditions the signal before triggering, reducing noise-induced false triggers. The result is a sensor designed specifically for the variable conditions of field sport testing rather than a repurposed industrial component.

It is worth being transparent here: published head-to-head research comparing timing gate hardware accuracy directly — across sensor technologies, under sport-specific field conditions — does not currently exist to the author's knowledge. The engineering rationale for dual filtering is sound, and it addresses known failure modes of simpler sensors, but comparative validation studies would strengthen the evidence base. Coaches selecting timing equipment should be aware that hardware specifications matter, and that 'timing gate' is not a single category of device.

The Biggest Sources of Error

Assuming you are working with quality hardware, protocol discipline becomes the dominant variable. The most common failures:

Inconsistent starting position relative to the first gate: If the athlete can start wherever they choose — one inch further back this week than last week — the first split time is contaminated. Standardise the starting distance to within 1 cm and enforce it every session.

Reaction time variability: Gate-based systems that require the athlete to move through the first gate to start timing mean the athlete starts timing themselves. If some athletes start within the gate zone and others clear it completely before timing begins, you have systematic between-athlete error. Use a separate trigger (remote start, coach-triggered) or position the first gate 0.3–0.5 m ahead of the starting position so clearing it is unavoidable.

Wind: A 2 m/s tailwind changes a 10 m sprint time by approximately 0.04 seconds — a magnitude similar to the performance difference between athletes you are trying to distinguish. Test indoors where possible, or record wind speed and consider conditions when comparing sessions.

Surface variation: Different surfaces, different footwear, different grass lengths (for outdoor testing) all affect times. Use the same surface, same footwear, same conditions every time.

What Acceptable Reliability Looks Like

For intraday reliability within a well-controlled protocol: 10 m CV ≤ 2.5%, 20 m CV ≤ 1.5%, 40 m CV ≤ 1.0%. If your data consistently exceeds these thresholds despite good protocol, hardware quality may be a contributing factor.

How to Improve Your Sprint Testing

1. Mark the starting position precisely — tape on the ground, measured from the gate. 2. Use a consistent start procedure — on command, same countdown, same push-off foot. 3. Allow adequate recovery — 4–5 minutes between trials at full effort. 4. Run trials in the same direction — wind becomes a consistent rather than random factor. 5. Use at least 3 trials per session — discard outliers, average the remaining. 6. Record the conditions — time of day, temperature, wind, surface — for context.

Good data is the foundation. Without it, you are making training decisions based on noise — and the quality of that foundation depends on both the equipment you choose and the discipline with which you use it.

References

Haugen, T.A. et al. (2012). Sprint running performance monitoring: methodological and practical considerations. Int J Sports Physiol Perform, 7(3), 282–292.
Morin, J.B. & Samozino, P. (2016). Interpreting power-force-velocity profiles for individualized and specific training. Int J Sports Physiol Perform, 11(2), 267–272.

Mark Fisher

Founder, Swift Performance

Mark Fisher is the founder of Swift Performance and has spent 30 years designing and building athlete testing equipment used by elite sport programmes and universities worldwide. He has worked alongside researchers and PhD candidates across biomechanics, sprint mechanics, and strength science — developing the hardware and software they use to collect and analyse performance data. His writing comes from three decades at the intersection of applied sport science and precision measurement technology.