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Dynamic visual acuity in athletes, 43 studies: two tests under one name, only one well validated, an athlete advantage with no proven link to play.
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In brief. In the 43 studies analyzed, dynamic visual acuity refers to two measurements: reading a moving target, or reading a fixed target while the head turns. Only the second has well-documented reliability in athletes. Athletes often do better than non-athletes, with no established link to playing level. Updated November 3, 2026.
Hello to you, the movement professional,
A small circle with a gap, the Landolt ring, races across a screen, and you have to say which side the gap opens on. The baseball players tested by Uchida's team at Waseda University did better than non-athletes as long as their eyes could follow the ring. With gaze locked on a fixed point, the difference disappeared (Uchida et al., 2012). For the authors, this advantage came mainly from the way the eyes accompanied the ring, rather than from a better perception of the image sliding across the retina.
Your athlete takes a "dynamic visual acuity" test: depending on the device, they will track a letter crossing the screen or read a still letter while turning the head at 150 degrees per second, and both scores will carry the same name. Some of these tests have known reliability, others do not, and none has shown that it predicts match performance. What, then, is the number you write down worth?
In the first family, the head stays still and the target moves. The aim is to find the highest speed at which the athlete can still read the gap, in degrees per second (Rouse et al., 1988; Ishigaki and Miyao, 1993), or the smallest target that can be read at a fixed speed. The eye then works in smooth pursuit to keep the image at the center of the retina, with catch-up saccades. In 23 university baseball players, the best scores went with smoother pursuit and fewer backward saccades (Palidis et al., 2017), which the article on the batter's pursuit and saccades details.
In the second, the target is fixed and the head turns, between 150 and 200 degrees per second depending on the protocol. Acuity with the head still and with the head moving is compared in logMAR, the logarithm of the smallest readable angle: the lower the number, the smaller the letter read. The loss between the two mainly informs on the vestibulo-ocular reflex, detailed in the article on keeping the gaze stable when everything moves. Many of these studies come from tracking head impacts, outside the scope of this article: we keep only the measurements of healthy athletes. When an assessment reports a "dynamic visual acuity," which of the two did it record?
Study | Population (n) | Type of test | What was measured | Result | Level of evidence |
|---|---|---|---|---|---|
50 American football players, high school and university | Head moving, 150 to 200 °/s; gaze stabilization | Test-retest reliability, two administrations over two weeks | ICC 0.770 (horizontal) and 0.725 (vertical); minimal detectable change 0.16 and 0.21 logMAR; gaze stabilization ICC 0.634 and 0.411 | Moderate | |
28 healthy university athletes, exertion or rest assigned at random | Head moving | Acuity loss before, just after and 10 min after 20 min of exertion | No effect of exertion; ICC from 0.4 to 0.74 | Low | |
37 university athletes (22 rugby, 15 wrestling) | Head moving | Before and after a high-intensity intermittent running test | Dynamic acuity reduced after exertion, increased dizziness | Low, case series | |
60 recreational athletes aged 14 to 24 | Not stated in the abstract | Relationships among four visual and vestibular tests | Correlations of 0.14 to 0.20 between tests; reliability of 0.79 to 0.97 | Low | |
67 Division I university American football players | Head moving, 150 °/s | Static and dynamic acuity at the start of the season | Static -0.232 logMAR; mean loss of 0.227 (horizontal) and 0.317 (vertical) | Low | |
124 Division I athletes (American football, soccer, cheerleading) | Head moving; gaze stabilization | Values in percentiles | Median 0 logMAR (interquartile range 0.17); stabilization 145 and 150 °/s, faster in cheerleaders; no effect of sex | Low to moderate | |
134 professional baseball players | Computerized gaze stabilization | Reference measurements, retrospective review of records | All above general-population norms | Low | |
22 mixed martial arts fighters, no reported symptoms | Head moving | Gap between static and dynamic acuity | -0.173 logMAR at rest, 0.196 (horizontal) and 0.283 (vertical) with the head moving, beyond normal values | Low, no control group |
The head-moving version is the best documented. In 50 American football players tested twice over two weeks, the intraclass correlation coefficient, which tells whether each person keeps their place in the group, reaches 0.770 for horizontal rotation and 0.725 for vertical (Kaufman et al., 2014). Below 0.16 logMAR horizontally and 0.21 vertically, that is more than a line and a half of a chart where each line is worth 0.1, a variation may come down to measurement noise. The gaze stabilization test (the maximum head speed at which the letter stays readable) repeats less well.
Twenty minutes of exertion do not change the acuity loss of 28 university athletes (Patterson et al., 2017), whereas a high-intensity intermittent running test degrades it in 37 rugby and wrestling athletes, in a case series without a control group (Jasinovic et al., 2021).
In 60 recreational athletes, four tests of vestibular function and vision repeat very well while barely correlating with each other: each measures something different (Heick et al., 2017). On the moving-target side, reliability is rarely published, and a review was already calling in 2011 for a standardized test: "The development of a standardized dynamic visual acuity test is needed" (Zimmerman et al., 2011).
Tested at the start of the season at 150 degrees per second, 67 American football players go from -0.232 logMAR with the head still to -0.007 in horizontal rotation and 0.0845 in vertical rotation (Marquez et al., 2017). In 124 Division I university athletes, the median with the head moving is 0 logMAR, with no difference between men and women (Quintana et al., 2020). In 22 active mixed martial arts fighters, the loss exceeds normal values, and the authors call for caution for lack of a control group (Landers et al., 2017). In Marquez as in Landers, the loss is greater in vertical rotation.
A norm depends on the device and the imposed speed as much as on the population: that of a university American football player does not automatically apply to a 15-year-old tennis player, and two teams consider useful a baseline measurement specific to each athlete, which then serves as the reference (Marquez et al., 2017; Brancaleone et al., 2025).
In 40 professional soccer players, dynamic acuity moderately tracks the static acuity of each eye (r = 0.524 and 0.553), and it is lower in those whose distance depth perception is poorer or whose astigmatism is more marked (Jorge and Jorge, 2024), a point taken up in the athlete's binocular vision. In 55 professionals in soccer, basketball and water polo, the link between the two acuities changes with the contrast of the target (Quevedo-Junyent and Argilés, 2024). With comparable static acuity and refraction, 15 athletes nevertheless read a target at 30 degrees per second better than a control group (Yee et al., 2021).
Dynamic acuity varies neither with vision correction in 73 young soft tennis players (Chang et al., 2015), nor with tinted lenses (Kohmura et al., 2013). "Kinetic" acuity, measured on a target that approaches, would be impossible to predict from static acuity according to a review from Juntendo University (Sawaki et al., 2022), whereas a study from the same university finds them strongly correlated (r = 0.75) in 106 participants (Kudo et al., 2021). Static acuity explains part of dynamic acuity, without replacing it.
Study | Population (n) | Type of test | Result | Level of evidence |
|---|---|---|---|---|
17 university baseball players, 25 students | Moving target, 10 to 110 °/s | Limit reading speed: 82.35 versus 69.90 °/s | Low | |
53 university athletes, 46 non-athlete students | Moving target, from 300 °/s | Athlete advantage on small gaps (14' and 8'), none on large ones | Low | |
32 softball players, 16 experienced and 16 not | Not stated in the abstract | Better in the experienced; weak correlation with coincidence-anticipation timing | Low | |
Baseball players and non-athletes (n not stated in the abstract) | Moving target, eyes free or fixating | Player advantage with eyes free, none with fixation | Low | |
Baseball players and non-players (n not stated in the abstract) | Moving target, eye recording | Faster and earlier eye movements in players; perception of the moving image identical | Low | |
23 university baseball players | Moving target, eye recording | Low position error, smooth pursuit and few reverse saccades go with the best scores | Low, correlational | |
46: 15 athletes, 11 action video game players, 20 controls | Moving target, 5 to 30 °/s, predictable or random | Athletes better than controls at 30 °/s; difference unrelated to static acuity, refraction or pursuit gain | Low, preregistered | |
Skilled cricket players and non-players (n not stated in the abstract) | Moving target, horizontal or vertical | Better in players, less degraded by speed | Low | |
Elite and sub-elite water polo players, sedentary students (n not stated in the abstract) | Moving target, 2 speeds, 3 trajectories, 2 contrasts | Elite better than sedentary in all conditions; no difference between elite and sub-elite according to a truncated abstract | Low | |
Young and older judokas and karatekas, non-athletes of the same age (n not stated in the abstract) | Moving target, 3 speeds, 3 contrasts | Athlete advantage; at high speed, young karatekas and older practitioners above their controls | Low | |
39 young adults, athletes or not according to a questionnaire | Head moving | Better dynamic acuity and better standing stability with the head rotating in athletes, no difference in quiet stance | Low | |
Professional baseball players and age-matched controls (n not stated in the abstract) | Active head moving; video head impulse test | Players better in static, horizontal and vertical; larger reflex gain gap between usual and high speed | Low | |
16 university athletes, 17 active students | Moving target at 30 °/s, seated, standing and walking | Random trajectory: athletes improve standing and walking, students decline (f = 0.51); horizontal trajectory: no difference | Low | |
19 deaf Deaflympics athletes, 25 hearing young adults | Not stated in the abstract | Better in the deaf athletes | Low | |
38 deaf or hard-of-hearing athletes, 38 hearing athletes | Head moving, horizontal rotation | No difference | Low | |
19 sport students, 10 in team sports and 9 in individual sports | Düsseldorf dynamic vision test, two administrations | No difference | Low | |
102 professional baseball players split into three levels | Static, kinetic and dynamic acuities | No difference between levels | Moderate | |
41 kendo practitioners, 65 people with no physical activity | Eight Japanese sports vision tests | Groups separated by static acuity, kinetic acuity and eye-hand coordination, without dynamic acuity in the abstract; dynamic acuity correlated with eye-hand coordination (r = -0.66) | Low to moderate | |
11 experienced clay target shooters, 12 novices | Standardized test battery | Novices better in dynamic acuity; all within norms | Low | |
52 athletes aged 18 to 37, federated or not | Computerized sports vision battery | No difference between federated and non-federated; dynamic acuity associated with training hours | Low |
The advantage over non-athletes comes back in most comparisons, and almost always fades between athletes: no difference between three levels in 102 professional baseball players (Hoshina et al., 2013), none between elite and sub-elite water polo according to a truncated abstract (Quevedo-Junyent et al., 2011), and novice clay target shooters do better than experienced ones (Abernethy and Neal, 1999). Millslagle's (2000) experienced softball players are the exception.
For Uchida's team, the advantage comes from eye tracking, faster and earlier in players (Uchida et al., 2013); in Yee, however, it persists at equal pursuit gain, without static acuity explaining it. The task matters too: on a random trajectory, Mitchell's athletes read better standing and walking than seated whereas the active students read worse, and the difference disappears on a horizontal trajectory (Mitchell et al., 2026). None of these comparisons says whether sport builds this acuity or retains those who already have it.
Study | Sport, population (n) | Published protocol | Measurement | Result | Transfer to the field | Level of evidence |
|---|---|---|---|---|---|---|
Basketball, 30 elite club players aged 18 to 24, assigned at random | 4 weeks, 6 sessions per week of oculomotor exercises, content not detailed in the abstract; control: usual training | Dynamic acuity (slideshow test), overall stability index | Dynamic acuity from 29.73 to 56.20 (p < 0.001), higher than the control | Not measured | Low to moderate, described as quasi-experimental | |
Table tennis, 50 players, 25 versus 25 assigned at random | 6 weeks, oculomotor exercises with gaze stabilization twice a day, sent by messaging app, in addition to training | Eye-hand coordination, reaction time, tracing test, dynamic acuity (slideshow) | Trained group improved on all measures | Not measured | Low | |
Soccer, 24 players from a professional club (under 18, under 23, women's first team), assigned at random | 6 weeks, 2 sessions of 30 min per week of soccer drills under modulated lighting; control: same drills in normal light | Dynamic acuity, recognition and reaction time, peripheral identification, stereopsis, anticipation | Dynamic acuity, recognition and reaction time, peripheral identification accuracy improved; stereopsis, peripheral identification speed and anticipation unchanged | Not measured | Low to moderate | |
Baseball and softball, 32 university players, double-blind versus placebo | 3 weeks, 3 sessions of 20 min per week of a digital program targeting dynamic acuity and depth | Acuity, stereoacuity, contrast, depth, dynamic acuity, reaction | No difference from placebo, just after or a month later; 15 placebo subjects out of 16 thought they were in the active group | Not measured; null visual measurement | Moderate | |
Liu 2020 (outside PubMed) | Baseball, 24 university players assigned at random versus placebo | 8.5 hours of training on average, called "dynamic vision": strobe, anticipation timing, eye speed | Visuomotor battery, batting in practice, game statistics | Battery and game unchanged; angle (d = 0.74) and distance of hit (d = 0.70) improved in practice, in 14 players | Intermediate positive; game null | Low, preregistered pilot study |
Three trials report increased dynamic acuity after four to six weeks, two of them with a slideshow test of unknown reliability, impossible to compare with Kaufman's minimal detectable change. The only double-blind placebo-controlled trial finds no difference, despite effect sizes of at least 0.5 on four measures including dynamic acuity (Shekar et al., 2021). No trial links dynamic acuity to play. The "dynamic vision" of Liu et al. (2020), made of strobe and timing, changes neither the visuomotor battery nor the game statistics: a program's name does not say which measurement it improves. Modulated lighting has its own article, on the athlete's peripheral vision.
Study A | Relation | Study B |
|---|---|---|
Kaufman 2014 (reliability in American football players) | same laboratory, in Las Vegas (Landers co-authors both), as | Landers 2017, which reads the acuity loss of fighters against normal values |
Patterson 2017 (no effect of 20 min of exertion) | apparently contradicts | Jasinovic 2021 (drop after a high-intensity test): different intensities and designs |
Uchida 2012 | same team and same paradigm as | Uchida 2013: two publications from the same program, not two independent replications |
Uchida 2012 and 2013 (eye tracking explains the advantage), Palidis 2017 (pursuit quality goes with the best scores) | qualified by | Yee 2021 (difference not explained by pursuit gain) |
Kudo 2021 (static and kinetic strongly correlated) | contradicts | Sawaki 2022 (kinetic acuity not predictable from static acuity), a review from the same university |
Jorge 2024 (link with static acuity) | partly joins | Quevedo-Junyent 2024 (link that varies with contrast) |
Jorge 2024 (variation between athletes, linked to static acuity) | does not contradict | Yee 2021 (athlete advantage at equal static acuity): one compares individuals, the other groups |
Jorge 2019 | same laboratory as | Jorge 2024: two cohorts of professionals, 2015 to 2017 then 2022 |
Quevedo-Junyent 2011 (elite equal to sub-elite) | joins | Hoshina 2013, Lüder 2011, Sánchez-Tena 2023: no difference between athletes |
Abernethy 1999 (novices better) and Hoshina 2013 | contrast with | Millslagle 2000 (experienced better) |
Nakajima 2012 (deaf athletes better than hearing people not described as athletes) | does not contradict | Brancaleone 2025 (no difference between deaf and hearing athletes) |
Shekar 2021 (null versus placebo) | contrasts with | Minoonejad 2019 and Altuncu 2024 (positive versus a control without placebo) |
Zimmerman 2011, Hodges 2021, Fogt 2023 (cricket players close to the general population, except for colors and perhaps near depth perception and dynamic acuity), Stine 1982 | frame | the whole: frequent athlete advantage, link with field performance not established |
Hodges et al. (2021) place dynamic acuity among general skills, detached from the sporting context, in a field with often discordant results. Stine et al. (1982) already judged the two studies cited in favor of a transfer to performance to be poorly designed. Two studies declare a conflict of interest: the corresponding author of Yee 2021 co-invented the measurement software used, not commercialized at the time, and two authors of Rodrigues 2025 are linked to the company that sells the lighting tested.
Established, on modest samples: the head-moving test keeps the athletes' ranking from one session to the next, with noise of 0.16 to 0.21 logMAR; acuity drops when the head turns fast, especially in vertical rotation; athletes often read a moving target better than non-athletes. Debated: the share of selection and training in this advantage, the role of pursuit, the effect of very intense exertion, that of programs (positive versus a control without placebo, null versus placebo). Extrapolation: that a better dynamic acuity makes a better player, when it does not even separate three levels of professional baseball players.
The most favorable idea can be tested: take 200 professional players from the same sport, measured at the start of the season with a head-moving test and a moving-target test of known reliability. If, at equal position, neither measurement predicts the season's game statistics, dynamic visual acuity no longer holds up as a performance marker in that sport.
In 147 professional soccer players, only a quarter of those who needed a correction to play wore it, and forwards, more often myopic, had the lowest dynamic acuity (Jorge and Fernandes, 2019). If your athlete reports double vision, blur that persists, headaches during exertion or dizziness, visual training waits. They first see an ophthalmologist, then an orthoptist in France, or an optometrist in Switzerland or the United States. LabO RNP is neither medical nor paramedical, and is added as a complement to a care pathway, never in its place. LabO RNP works with optometrists; the curriculum was built with them.
The eyes are an entry point: LabO RNP teaches movement professionals the sensory aspects of movement and the whole sensorimotor loop, what the athlete perceives and what they do with it. In Koide, the athletic group reads better with the head rotating and also stands better during that rotation, a link between gaze and postural control described without an established cause. The oculomotor exercises in the warm-up have their article, and the map of the evidence in sports vision places dynamic acuity among the other visual functions.
The ability to read a fine detail in motion. Studies measure it in two ways: a target that moves in front of a still head, or a fixed target read while the head turns. The first mainly engages smooth pursuit, the second mainly the vestibulo-ocular reflex.
The head-moving version, between 150 and 200 degrees per second, has published reliability in 50 American football players: below 0.16 logMAR horizontally and 0.21 vertically, a difference may be measurement noise (Kaufman et al., 2014). Moving-target tests vary from one study to another and rarely publish their reliability.
Three trials report a gain after four to six weeks of oculomotor exercises or modulated lighting (Minoonejad et al., 2019; Altuncu and Aras Bayram, 2024; Rodrigues et al., 2025). The only double-blind trial, in 32 baseball and softball players, finds no difference from a placebo (Shekar et al., 2021). None measures play.
Yes, as soon as double vision, persistent blur, headaches during exertion or dizziness appear: ophthalmologist first, then orthoptist in France or optometrist in Switzerland and the United States. LabO RNP is neither medical nor paramedical, and is added as a complement to a care pathway, never in its place.
Before comparing two dynamic visual acuity scores, check that they come from the same test and that the difference exceeds the noise of the measurement.
👉 I want to understand what my athlete sees when their head moves.
By the LabO RNP team
Method. Selection of November 3, 2026 from the LabO RNP inventory of studies on athlete vision: 50 studies identified, 7 excluded (follow-up after a head impact, no abstract or data, unreviewed work, other measurement, duplicate), 43 analyzed (33 measurement or comparison studies, 5 reviews, 5 trials). PMIDs verified on PubMed the same day; Altuncu 2024 and Liu 2020, absent from PubMed, are cited by their DOI verified with Crossref.
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Kudo D, Hiratsuka Y, Nakamura M, Uchida Y, Ono S, Murakami A (2021). Optimal methods for estimating sports vision in kendo athletes. Sci Rep, 11(1), 315. PMID 33431981. doi:10.1038/s41598-020-79534-1
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30 studies in gymnastics, trampoline, dance and skating: where the rotation expert looks, what the vestibulo-ocular reflex does, how good spotting is.
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Read the articleThe RNP system is meant to be read, targeted and tested from your next assessment. Start with the member space, for free.