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Influence of surface properties on soccer ball trajectories  †.

1. Introduction

2. experimental methods and discussion, 3. meta-analysis, 4. surface influences on ball trajectory, 5. conclusions.

• Goff, J.E.; Asai, T.; Hong, S. A comparison of Jabulani and Brazuca non-spin aerodynamics. J. Sports Eng. Tech. 2014 , 228 , 1881–1894. [ Google Scholar ] [ CrossRef ]
• Goff, J.E.; Hobson, C.H.; Asai, T. Wind-tunnel experiments and trajectory analyses for five nonspinning soccer balls. Proc. Eng. 2016 , 147 , 32–37. [ Google Scholar ] [ CrossRef ]
• Goff, J.E.; Hong, S.; Asai, T. Aerodynamic and surface comparisons between Telstar 18 and Brazuca. J. Sports Eng. Tech. 2018 , 232 , 342–348. [ Google Scholar ] [ CrossRef ]
• Hong, S.; Goff, J.E.; Asai, T. Effect of a soccer ball’s surface texture on its aerodynamics and trajectory. J. Sports Eng. Tech. 2019 , 233 , 67–74. [ Google Scholar ] [ CrossRef ]
• Goff, J.E.; Hong, S.; Asai, T. Effect of a soccer ball’s seam geometry on its aerodynamics and trajectory. J. Sports Eng. Tech. 2019 . [ Google Scholar ] [ CrossRef ]
• Naito, K.; Hong, S.; Koido, M.; Nakayama, M.; Sakamoto, K.; Asai, T. Effect of seam characteristics on critical Reynolds number in footballs. Mech. Eng. J. 2018 , 5 , 17–00369. [ Google Scholar ] [ CrossRef ]
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• Ward, M.; Passmore, M.; Spencer, A.; Tuplin, S.; Harland, A. Characterization of football trajectories for assessing flight performance. J. Sports Eng. Tech. 2019 , 233 , 16–26. [ Google Scholar ]
• Achenbach, E. The effects of surface roughness and tunnel blockage on the flow past spheres. J. Fluid Mech. 1974 , 65 , 113–125. [ Google Scholar ] [ CrossRef ]
• Goff, J.E.; Carré, M.J. Trajectory analysis of a soccer ball. Am. J. Phys. 2009 , 77 , 1020–1027. [ Google Scholar ] [ CrossRef ]

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Goff, J.E.; Hong, S.; Asai, T. Influence of Surface Properties on Soccer Ball Trajectories. Proceedings 2020 , 49 , 143. https://doi.org/10.3390/proceedings2020049143

Goff JE, Hong S, Asai T. Influence of Surface Properties on Soccer Ball Trajectories. Proceedings . 2020; 49(1):143. https://doi.org/10.3390/proceedings2020049143

Goff, John Eric, Sungchan Hong, and Takeshi Asai. 2020. "Influence of Surface Properties on Soccer Ball Trajectories" Proceedings 49, no. 1: 143. https://doi.org/10.3390/proceedings2020049143

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July 1, 2010

Study explains science of soccer

by American Institute of Physics

With the attention of sports fans worldwide focused on South Africa and the 2010 FIFA World Cup, U.S. scientist John Eric Goff has made the aerodynamics of the soccer ball a focus of his research.

In an article appearing in the magazine Physics Today this month, Goff examines the science of soccer and explains how the world's greatest players are able to make a soccer ball do things that would seem to defy the forces of nature.

Goff's article looks at the ball's changing design and how its surface roughness and asymmetric air forces contribute to its path once it leaves a player's foot. His analysis leads to an understanding of how reduced air density in games played at higher altitudes -- like those in South Africa -- can contribute to some of the jaw-dropping ball trajectories already seen in some of this year's matches.

"The ball is moving a little faster than what some of the players are used to," says Goff, who is a professor of physics at Lynchburg College in Virginia and an expert in sports science.

For Goff, soccer is a sport that offers more than non-stop action -- it is a living laboratory where physics equations are continuously expressed. On the fields of worldwide competition, the balls maneuver according to complicated formulae, he says, but these can be explained in terms the average viewer can easily understand. And the outcomes of miraculous plays can be explained simply in terms of the underlying physics.

Goff also is the author of the recently published book, "Gold Medal Physics : The Science of Sports," which uncovers the mechanisms behind some of the greatest moments in sports history, including:

• How did Cal beat Stanford in the last seconds with five lateral passes as the Stanford marching band was coming on to the field?
• How did Doug Flutie complete his "Hail Mary" touchdown pass that enabled Boston College to beat Miami?
• How did Lance Armstrong cycle to a world-beating seven Tour de France victories?
• How did Olympic greats Bob Beamon (long jump), Greg Louganis (diving) and Katarina Witt (figure skating) achieve their record-setting Olympic gold?

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Motion Analysis of Soccer Ball

Dynamics Modeling, Optimization Design and Virtual Simulation

• © 2022

Houston, USA

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• Lays a foundation for the full dynamic simulation of soccer ball motion using classic mechanics
• Introduces a numerical validation method to validate the dynamics models of soccer ball
• Combines dynamics, mathematics and sports engineering from a multidisciplinary design optimization towards soccer ball

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Similar content being viewed by others, free kick goals in football: an unlikely success between failure and embarrassment.

A review of tennis racket performance parameters

Biomechanical Measurement Methods to Analyze the Mechanisms of Sport Injuries

• Soccer ball
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• Numerical validation
• Kinematics and dynamics
• Predicting trajectory
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Table of contents (7 chapters)

Front matter, introduction, dynamics modeling and numerical validation of soccer ball projectile motion, spatial kinematics and dynamics simulation of soccer ball projectile motion, optimization design of soccer ball flight trajectory, modeling and simulation of soccer ball free kick, modeling and simulation of soccer ball corner kick, contributions and conclusions, authors and affiliations, about the author, bibliographic information.

Book Title : Motion Analysis of Soccer Ball

Book Subtitle : Dynamics Modeling, Optimization Design and Virtual Simulation

Authors : Ying Li

Series Title : SpringerBriefs in Applied Sciences and Technology

DOI : https://doi.org/10.1007/978-981-16-8652-8

Publisher : Springer Singapore

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Softcover ISBN : 978-981-16-8651-1 Published: 21 January 2022

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Number of Pages : XI, 105

Number of Illustrations : 9 b/w illustrations, 67 illustrations in colour

Topics : Mathematical and Computational Engineering , Sport Science , Classical Mechanics , Simulation and Modeling , Theoretical, Mathematical and Computational Physics , Computational Mathematics and Numerical Analysis

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The physics of football

• Published 1990

14 Citations

The biomechanics of kicking in soccer: a review.

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Evaluating the efficacy of UEFA’s home-grown rule in European football

• 18 Excerpts

The paradox of the tight spiral pass in American football: A simple resolution

Optimization and aerodynamic design of a soccer ball using numerical analysis, aerodynamic design considerations for a soccer ball, three-dimensional linear and angular kinematics of a spinning cricket ball, erratum to: a review of recent research into aerodynamics of sport projectiles, determination of the drag coefficient by analysing the trajectory of a football, ijsrd-international journal for scientific research & development| vol. 2, issue 12, 2015 | issn (online): 2321-0613, football in flight: a study of the math and physics of the trajectory of a kicked football, related papers.

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Peer-reviewed

Research Article

Six different football shoes, one playing surface and the weather; Assessing variation in shoe-surface traction over one season of elite football

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Supervision, Visualization, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliations Aspetar Orthopaedic and Sports Medicine Hospital, Doha, Qatar, University of Ulster, Jordanstown, County Antrim, United Kingdom

Roles Data curation, Formal analysis, Visualization, Writing – original draft, Writing – review & editing

Affiliation Aspetar Orthopaedic and Sports Medicine Hospital, Doha, Qatar

Roles Project administration, Supervision, Writing – original draft, Writing – review & editing

Roles Data curation, Investigation, Supervision, Writing – original draft, Writing – review & editing

Affiliations University of Ulster, Jordanstown, County Antrim, United Kingdom, High Point University, High Point, NC, United States of America

• Athol Thomson, 
• Rodney Whiteley, 
• Mathew Wilson, 
• Chris Bleakley

• Published: April 30, 2019
• https://doi.org/10.1371/journal.pone.0216364
• Reader Comments

19 Jun 2019: Thomson A, Whiteley R, Wilson M, Bleakley C (2019) Correction: Six different football shoes, one playing surface and the weather; Assessing variation in shoe-surface traction over one season of elite football. PLOS ONE 14(6): e0218865. https://doi.org/10.1371/journal.pone.0218865 View correction

Introduction

An optimal range of shoe-surface traction (grip) exists to improve performance and minimise injury risk. Little information exists regarding the magnitude of traction forces at shoe-surface interface across a full season of elite football (soccer) using common football shoes.

To assess variation in shoe-surface traction of six different football shoe models throughout a full playing season in Qatar encompassing climatic and grass species variations.

Football shoes were loaded onto a portable shoe-surface traction testing machine at five individual testing time points to collect traction data (rotational and translational) on a soccer playing surface across one season. Surface mechanical properties (surface hardness, soil moisture) and climate data (temperature and humidity) were collected at each testing time point.

Peak rotational traction was significantly different across shoe models (F = 218, df = 5, p <0.0001), shoe outsole groups (F = 316.2, df = 2, p < .0001), and grass species (F = 202.8, df = 4, p < 0.0001). No main effect for shoe model was found for translational traction (F = 2.392, p = 0.07).

Conclusions

The rotational (but not translational) traction varied substantially across different shoe types, outsole groups, and grass species. Highest rotational traction values were seen with soft ground outsole (screw-in metal studs) shoes tested on warm season grass. This objective data allows more informed footwear choices for football played in warm/hot climates on sand-based elite football playing surfaces. Further research is required to confirm if these findings extend across other football shoe brands.

Citation: Thomson A, Whiteley R, Wilson M, Bleakley C (2019) Six different football shoes, one playing surface and the weather; Assessing variation in shoe-surface traction over one season of elite football. PLoS ONE 14(4): e0216364. https://doi.org/10.1371/journal.pone.0216364

Editor: Nathan Schilaty, Mayo Clinic Rochester, UNITED STATES

Received: December 30, 2018; Accepted: April 18, 2019; Published: April 30, 2019

Copyright: © 2019 Thomson et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the manuscript and supplementary files.

Funding: The author(s) received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

Association football (soccer) is an invasion game involving multiple bouts of intermittent sprinting and directional changes. Elite footballers undertake 1500–3100 metres of high intensity running per match [ 1 , 2 ], with accelerations contributing 7–10% of the total player load, and decelerations contributing 5–7% [ 3 ]. A recent systematic review examining activity demands of team sports found that the highest volume of cutting movements occur in football, with players performing up to 800 cuts per game [ 4 ].

A player’s ability to accelerate, decelerate, and change direction is largely influenced by the available traction between the football shoe and playing surface [ 5 , 6 ]. Two important components of traction exist: translational traction which is the horizontal force required to overcome the resistance between the shoe outsole (studs) and playing surface; and rotational traction which is the rotational force required to release the studs through the playing surface in a rotational manner. Although increases in translational traction (straight line or side-to-side) are linked to improved performance (e.g., time to complete an agility course or acceleration task) [ 5 , 6 ], higher levels of rotational traction are linked to greater risk of lower limb injury [ 7 – 11 ].

Optimal shoe-surface conditions should therefore attenuate rotational resistance whilst maintaining translational traction or playing performance (no slipping for players) [ 7 , 10 ]. This is sometimes difficult to achieve as traction varies according to shoe outsole, stud/cleat configuration [ 12 ], and the characteristics of the playing surface [ 13 , 14 ], among other factors [ 5 ]. Further challenges arise based on the wide array of outsole designs currently on the market and intermittent changes in playing surface throughout a playing season [ 11 , 15 ].

Mechanical properties of natural grass playing surfaces are moderated by climatic factors such as. temperature and soil moisture. Surface hardness and subsequent penetration of the studs on the surface ultimately alters traction [ 11 , 16 – 20 ]. Varied shoe-surface interface conditions change a players muscle recruitment patterns [ 21 ], movement strategies [ 22 ], and injury risk [ 11 , 23 ].

Importantly, varied climatic conditions means certain geographical regions support certain species of grass. Moreover, different grass species have different mechanical properties [ 11 , 15 ]. For example, drought resistant warm season grass species are associated with increased risk of anterior cruciate ligament injury compared to other cool season grass species in Australian rules football [ 24 ]. This is attributed to higher shoe-surface traction with warm season grass species.

Portable testing devices can now be used to objectively measure mechanical properties of playing surfaces and quantify their interaction with shoe outsoles. These data could help to streamline decision making concerning the suitability of football shoe outsoles, allowing players to tailor their selection for given climatic or surface conditions. Our primary aim is to assess variation in shoe surface traction of different football shoes on one football playing surface throughout a season in Qatar. As a secondary objective, any moderating effects of temperature, humidity, soil moisture, and surface hardness are examined.

Playing surface

One natural grass football pitch (Qatar national team outdoor training pitch) with a sand rootzone and no hybrid reinforcement was tested at five time points over a single football season in Doha, Qatar (November 2017, January, March, April and May 2018).

The climatic conditions in Qatar mean that grass type consistently changes during a playing season: ranging from natural warm-season C 4 grass ( Paspalum vaginatum ‘Paspalum’) in summer months; to warm-season grass over-seeded with cool-season C 3 grass ( Lolium perenne ‘Perennial Rye’) in transition cooler months; to predominantly cool season (Perennial Rye) grass in the coldest month (January 2018). Warm season grasses are more heat and drought tolerant but become dormant at lower temperatures, thus the need to over-sow with cool-season grass [ 15 ].

Ground staff maintained 100% grass coverage with grass length at 25mm on the day of each test. Surface hardness was assessed using a 2.25kg Clegg hammer dropped from 450mm (SD instrumentation, England). Soil moisture (Delta-t ML2X/ML3 thetaprobe, England) and temperature/humidity (Kestrel 4400 heat stress tracker, USA) were also recorded. These surface tests were carried out in five different pitch locations and repeated five times in each location (moving to untested/unaffected grass for each test).

Football shoe models

Six different football shoes manufactured by Nike (Beverton, Oregon USA) were tested. These consisted of one artificial grass (AG) outsole (Nike Tiempo legend VII Pro AG), four firm ground (FG) outsoles (Mercurial vapor XI FG, Magista obra II Elite FG, Tiempo legend VII FG, and Hypervenom Phantom III FG), and one soft ground (SG) outsole (Tiempo legend VII Pro SG) ( Fig 1 ). According to a worldwide professional football shoe database (Footballbootsdb.com), our sample shoes included four of the six most used football shoes in the world.

• PPT PowerPoint slide
• PNG larger image
• TIFF original image

AG = artificial grass. FG = firm ground. SG = soft ground.

https://doi.org/10.1371/journal.pone.0216364.g001

Outsole types

Shoes were grouped according to their outsole type for further analysis. Shoes are marketed and sold in these “silos” with players expected to select an outsole type that best suits the surface and climate conditions they will play on. Soft ground (SG) shoes have fewer, longer, conical (or tapered) metal “screw-in” studs for wet, muddy, or low surface traction conditions. Firm ground (FG) shoes have moulded cleats, blades, or round studs (not screw-in) that are generally used on firm, dry surfaces. Artificial grass (AG) shoes have several small, short, round moulded studs that are generally used on artificial turf.

Shoe-surface traction testing

Traction between the shoe and surface was measured using a commercially available portable traction testing device (S2T2, Exeter Research USA). The device consists of a prosthetic foot-form (size 10.5 US), on which shoes are fitted and positioned at 20° of plantar flexion to ensure only the forefoot studs are in contact with the surface [ 25 , 26 ]. The foot can be rotated to measure peak rotational traction or locked into a linear position along the long axis of the shoe and then dragged forward across the surface to measure translational traction [ 10 , 26 ]. The floating foot-mass ensures the vertical load (added barbell weight plates) is applied through the shoe to the playing surface and not the supporting frame. Wheels allow for movement across multiple testing locations on the playing surface ( Fig 2 ). Measurements were taken manually by a single operator (AT) for all pilot validation tests and within study tests. Each shoe model was tested at twelve separate locations on the playing surface during the five individual time points (November 2017, January, March, April and May 2018) for rotational traction and six separate playing surface locations for translational traction.

(S2T2, Exeter research, USA).

https://doi.org/10.1371/journal.pone.0216364.g002

For rotational traction a vertical load of 580N (59.1kg) was applied and the test foot rotated through 90° at a speed of approximately 90°/s. Two operators who had a combined mass of 163kg stood on each end of the frame to stabilise during tests. Peak rotational traction was recorded in newton meters (Nm) for both internal rotation and external rotation directions by a digital torque wrench sampling at 500Hz (ETW-PR-100, Checkline, NY, USA) with an accuracy of ± 1% of indicated measurement in a range of 10-100Nm. Rotational traction and vertical load displayed a linear relationship during our pilot work with the S2T2 tester on this natural grass playing surface as previously reported [ 26 ]. Thus, 580N was deemed to cause an acceptable amount of damage for grounds-staff to manage on a high use football surface and is a vertical load used for previous studies in American football [ 10 , 26 ].

For translational traction a vertical load of 300N (30.6kg) was applied to the test foot while a digital force gauge (Chatillon DFE2-500, Ametek, USA) sampling at 7000Hz with an accuracy of ±0.25% of indicated measurement, measured peak horizontal force (Newtons) resisting linear motion between the shoe and surface. The translational traction coefficient was calculated as a ratio of peak horizontal force divided by vertical force. This gives an indication of the horizontal force required to overcome the resistance between the shoe and surface as the shoe is dragged across the surface in a linear movement. During pilot work several speeds and vertical loads were used for translation traction testing with ground-staff present to assess damage to the playing surface. 300N of vertical load and approximately 200mm/s allowed surface damage acceptable to ground staff.

Reliability and validity of shoe-surface traction tester

A test-retest protocol comprising 528 measurements of a single football pitch was conducted for internal rotation, external rotation, and translational traction, prior to commencing data collection for the current study. Intra-class correlation coefficients with 95% confidence intervals, standard error of measurement (SEM), and minimal detectable change (MDC) are presented in Table 1 .

ICC values were classified as follows; ≥0.9 as excellent, ≥0.8 as good, ≥0.7 as acceptable, ≥0.6 as questionable, ≥0.5 as poor and <0.5 as unacceptable [ 27 ].

https://doi.org/10.1371/journal.pone.0216364.t001

Statistical analysis

The dependent variable was rotational traction. A 2-way analysis of variance, was conducted using two factors: month/surface (5 levels) and shoe model (6 levels). Bonferoni post hoc tests were performed when indicated. This analysis was repeated to further examine the effect of month / surface (5 levels) and outsole pattern (3 levels). We also undertook a series of ANCOVAs. This was to compare main and interaction effects after controlling each of the following covariates which were dichotimsed using medians of temperature, humidity and ground hardness. All statistical tests were undertaken using SPSS (Version 25, IBM, Chicago, Illinois) with significance was set at P < .05 in all analyses.

Rotational traction

Table 2 summarizes the mean rotational traction in newton meters (Nm) for individual shoe models at each testing time point with grass type in bold. Peak rotational traction was significantly different across shoe models (F = 218, df = 5, p <0.0001). Consistently lower rotational traction was recorded with the Tiempo AG shoe across all months. Post hoc testing found significant differences between the Tiempo SG and all other models, with the largest difference occurring between the Tiempo SG (metal screw-in studs) and Tiempo AG (small round moulded studs) shoes (Mean difference 17.5 Nm, t = 13.3, p<0.0001). Consistently higher rotational traction was recorded for the Tiempo SG shoe across all months.

WS = warm season grass. CS = Cool season grass. WS/CS = warm season grass over-sown with cool season grass. Outsole type groups AG = artificial grass, FG = firm ground and SG = Soft ground. Conditional formatting shows the minimum (green) and maximum (red) rotational traction shoe-surface combinations with the highest (dark red) being Tiempo SG shoe tested in May on warm season grass. Winter is December-February in Qatar hence the cool season grass and Tiempo AG shoe combination in January showed the lowest mean rotational traction (dark green).

https://doi.org/10.1371/journal.pone.0216364.t002

Peak rotational traction was also significantly affected by grass type (F = 202.8, df = 4, p < 0.0001). Colder season grass (January) was associated with the lowest rotational traction. Conversely, the highest values were reported when testing on warm season grass (during either November or May testing). The largest mean differences occurred when comparing May warm season grass (WS) vs. January cool season grass (CS) (Mean difference 13.2 Nm, t = 10.9, p<0.001). ( Table 2 and S1 Fig ). Large differences in rotational data were also reported when comparing January CS with November WS (Mean difference 11.7 Nm, t = 9.7, p<0.001). We also found a significant interaction between the two factors (month*shoe type) (F = 5.4, DF = 20, p <0.0001).

Findings were similar when analyses were repeated using outsole classification (rather than shoe model). Again, we found significant main effects for outsole (F = 316.2, df = 2, p < .0001), grass type (F = 87.1, df = 4, p < .0001) and significant interaction effects (outsole*grass type) (F = 2.7, df = 8, p < .007). The largest mean difference for rotational traction was reported in November (warm season grass) between the SG and AG outsoles– 20.6Nm ( 17 . 3–23 . 8 95%CI) with very large effect size (ES = 5.4). See Table 3 and Fig 3 .

WS = warm season grass. CS = Cool season grass. WS/CS = warm season grass over-sown with cool season grass. The box represents 50% of the dataset, ends of the box show the 1st and 3rd quartiles, whiskers extend to the furthest data point within 1.5*IQR from the 1st and 3rd quartiles. ‘X’ within box = mean. Horizontal line within box = median. Whiskers of artificial ground (AG) blue outsole never cross that of the Soft ground (SG) grey outsole type for the entire season. Note the relative drop in rotational traction for all outsole groups in January with the cool season grass playing surface.

https://doi.org/10.1371/journal.pone.0216364.g003

WS = warm season grass. CS = Cool season grass. WS/CS = warm season grass over-sown with cool season grass. Note the consistently large mean differences with very large effect size between the soft ground (SG) and artificial ground (AG) outsoles across the entire season.

https://doi.org/10.1371/journal.pone.0216364.t003

Table 4 shows the average values for climate and surface tests. Exploratory analyses (ANCOVA) found trends that lower humidity (B = -2.4, t = -1.9, p = .06) and greater ground hardness (B = 2.5, t = 1.9, p = .052) were associated with higher rotational traction. Higher temperatures were also associated with higher levels of rotational traction (B = 3.18, t = 2.5, p = .012). There was still a significant effect of shoe type and shoe*grass interaction, on levels of rotational traction after controlling for each of these covariates. Temperature was not included as a covariate when assessing the main effects of grass type due to the high level of correlation between these two variables. (r = .88, p < .0001).

https://doi.org/10.1371/journal.pone.0216364.t004

Translation traction

No main effect by shoe model was found for translational traction (F = 2.392, p = 0.07). However, there was a main effect for grass type (F = 3.861, p = 0.01) with the largest difference being warm season grass and Tiempo SG combination (translational traction coefficient mean μ = 2.5±0.2) vs the cool season grass and Tiempo AG combination (translational traction coefficient mean μ = 1.9 ±0.1). The translational traction coefficient was calculated as a ratio of peak horizontal force divided by vertical force.

Large variations in the magnitude of shoe-surface traction are evident throughout one season of elite football played in a warm/hot climate. Shoe type, outsole group, and grass species significantly affected rotational traction which has been linked to increased lower extremity injury [ 8 – 11 , 18 ]. Implications for footwear selection will interest players, medical and sports science staff working in football played in warm climate zones, particularly when it is vital to minimise rotational traction for given playing surfaces and climate conditions (e.g. return to on-field rehabilitation in football shoes after ACL injury).

The major strengths of this study include data collection of different shoe outsole designs, grass species, surface mechanical properties, and climate data at multiple time points on a playing surface maintained for elite football (not a turf farm or laboratory setting).

Why is shoe-surface traction important?

While performance may be augmented with higher available traction at the shoe-surface interface, some concerning alterations to player movement can occur. Lower knee flexion angle, higher external knee valgus moments, increased knee joint loading, and increased distance from the plant foot to the centre of mass during cutting manoeuvres are some of the changes under higher traction conditions at the shoe-surface interface [ 7 , 12 , 22 ]. These movement strategies, along with increased loading, have been implicated in anterior cruciate ligament (ACL) injury and other lower extremity injuries. This is corroborated with evidence from prospective studies showing a significant increase in lower limb injury risk associated with high levels of rotational traction [ 8 – 11 ]. Importantly, higher rotational traction, as opposed to translational traction, has been found to be a significant predictor of peak ACL force during a maximal change of direction task [ 28 ].

What can players do to modulate rotational traction?

Parameters that are somewhat set once the player arrives to train or play a match include the climate, surface hardness, surface traction, and grass type etc. Pitch preparation and climate are also out of the athlete’s control. Shoe outsole selection is one of the few immediately modifiable factors that can allow a player to modulate the traction experienced at the shoe-surface interface [ 5 ]. Objective data on the surface should be made available to the athlete and medical or sport science teams so that footwear selection can be made with these parameters in mind. Significant differences for rotational traction were found at the shoe-surface interface for different grass species ( Table 2 ), shoe types ( Table 2 , S1 Fig ), and shoe outsoles ( Fig 3 ).

Overall, choosing a shoe with lower rotational traction that results in no consequent detriment to performance (high translational traction) is recommended, assuming the injury risk from other sports extends to soccer [ 7 – 10 , 29 ]. Table 2 , S1 Fig , and Fig 3 can be used to help inform footwear selection for players in warm climate zones.

Stud/cleat shape and surface conditions

Players deem optimal performance and/or risk of lower extremity injury to be intrinsically related to certain playing surface characteristics. Ninety-one percent of players from a worldwide cohort of elite footballers (n = 1129) think the type or condition of a playing surface increases the likelihood of injury with excessive hardness and traction ranked high on the list of concerns [ 30 ].

Optimum penetration of the stud/cleat into the surface is paramount in achieving the maximum traction [ 19 ] (which is beneficial to performance) as all studs ‘sink’ into the surface to the outsole plate. Surface hardness therefore affects traction and comfort for the player depending on the type of shoe outsoles used. Ground staff kept the soil moisture and surface hardness within a small range of variation across each individual testing point in this study ( Table 4 ). The SG outsole had the highest values for both rotational and translational traction over the season. Conical, tapered metal screw-in studs 11mm in length at the forefoot of the SG outsole allow for full penetration in the playing surface and significantly increase traction. This is evident in May with high surface hardness, high temperature, warm season grass, and the SG outsole combined to give the highest mean peak rotational traction for the season (59Nm). Some of the FG shoes with bladed cleats had a larger cross-sectional area than the tapered conical studs of the SG shoe ( Fig 1 ) and may not have penetrated completely to the outsole plate of the shoe and therefore demonstrated lower rotational traction values. However, the penetration depth of studs was not measured in this study.

Effect of grass type on rotational traction

Warm season (Paspalum) grass showed higher rotational and translational traction particularly when coupled with the SG outsole. Cool season (Rye) grass showed lower rotational traction across all shoes highlighted by the relative “dip” in rotational traction values for all outsole types in January ( Fig 3 ) compared to other months where there is either warm season grass or warm season grass over-sown with cool season grass. Our findings add a mechanically plausible explanation to those of Orchard et al . (2005) [ 24 ] in which male Australian rules football players suffered less ACL injuries on cool season Rye grass than warm season (Bermuda) grass.

Considerations for return to field specific rehabilitation following injury

Rotational traction for the AG outsole was consistently lower regardless of grass type, climate, and mechanical properties (e.g. hardness) of the pitch ( Fig 3 ). We suggest this should be the outsole of choice for those players returning to on-field sports specific rehabilitation following ACL, syndesmosis or other lower extremity injuries where it is vital to minimise rotational traction forces. Conversely, SG metal screw-in studs consistently showed high rotational traction and should ideally be avoided during early stage field specific rehabilitation.

Lambson et al . (1996) [ 8 ] investigated the effect of cleat design on ACL injury risk in American football. Large cleats located along the edge of the forefoot in American football shoes were shown to have higher rotational traction (average 31Nm). Subsequently, 3.4 times more ACL injuries occurred with this cleat design than other stud or cleat designs that had lower rotational traction values (average 24Nm). Comparisons are difficult as we tested with higher vertical load, on surfaces with different characteristics, and used a commercially available traction-testing machine. Wannop et al (2013) [ 10 ] used the same vertical load as our study (580N or 60kg) on a more sophisticated traction testing machine to investigate the effect footwear traction has on lower extremity injury in American football. Non-contact lower extremity injuries peaked at 19.2/1000 game exposures in the high rotational traction group (39–54.9Nm) of male American football players compared to 4.2 injuries per 1000 games exposures in the low rotational traction group (15–30.9Nm). Prospective studies are of course required to see if these findings extend to soccer.

Translational traction testing on natural grass playing surfaces

Remarkably, only grass type affected translational traction. There was no main effect relating to translational traction seen for shoe type or outsole type. This was a surprising finding as there was considerable damage to the playing surface with each test. Previous research on the coefficient of translational traction tested on artificial playing surfaces suggests vertical loads of over 888N (approx. 90kg) are required to see meaningful differences between shoe outsole designs when a horizontal force is applied [ 31 ]. Our findings suggest the vertical load of 300N used here was not sensitive enough to see differences between the shoes tested on two species of natural grass. It was not feasible to test at higher loads due to the amount of damage incurred to the playing surface with each test. The playing surface examined was the Qatar national team’s main training pitch which saw high traffic over the duration of the study. Speed of the horizontal translation (which was manually driven) may also have influenced the results [ 26 ]. It is suggested that improved and more sensitive methods for testing translational traction need to be developed if it is to be implemented into regular monitoring at elite football clubs and federations.

Does mechanical traction testing equal traction utilised by a player?

In January cool season grass average peak rotational traction for the AG outsole slipped down to 28Nm compared to 36Nm and 45Nm for the FG and SG groups respectively ( Table 3 ). Further biomechanical and perception testing of players performing football specific tasks are required to ascertain if performance decreases with this lower magnitude of rotational traction [ 5 ].

Our results suggest mechanical testing for traction at the shoe-surface interface is more sensitive to changes in the rotational component of traction compared to the translational component for the methods used here.

Limitations

Although portable testing devices facilitate tracking of surface properties over time and between different surfaces or different football shoes, they do not provide an accurate representation of forces experienced by players when they are actually playing sport. It is suggested that a functional traction course and traction perception rating be used alongside mechanical testing to allow players’ intuition and perception of optimal traction to aid footwear selection [ 5 ].

All shoes tested here are from one manufacturer. Future research should test across all football shoe manufacturers.

Impact of our findings

After ground staff have prepared a playing surface and the prevailing climatic conditions are known close to kick-off, thereafter players can only control the type of shoe outsole (e.g. soft ground outsole, firm ground outsole etc) by choosing the shoe that best suits these primary factors to modulate the amount of traction experienced by the player. The current data shows that the variability within a single season is large enough to warrant tailoring across different months.

Further research

It is likely that the optimal level of traction may change based on sport or even playing position. It is also pragmatic to suggest even lower levels of rotational traction when players are returning to field specific rehabilitation or training following a significant injury (eg ACL). Future research should examine several playing surfaces, soil types, and grass species to get a more complete understanding of shoe-surface traction.

The rotational (but not translational) traction varied substantially across different months of the year, different grass species, and with different shoe outsole types. Warm season grass tested with the soft ground shoe (screw-in metal studs) showed the highest magnitude of rotational traction while cool season grass tested with an artificial ground shoe (small round moulded studs) showed the lowest. These objective data should allow for more informed footwear choices for football played in warm/hot climates. Further research is required to confirm if these findings extend across other football shoe brands.

Practical implications

Objective data presented here can help tailor footwear selection (from one manufacturer) across a season of elite football in warm/hot climate zones. The authors suggest a universally accepted (commercially available) portable shoe-surface traction device should be agreed upon to allow new footwear outsole designs to be tested on various playing surfaces and climate zones.

Supporting information

S1 fig. rotational traction for each shoe at each testing time point and grass type..

WS = warm season grass. CS = Cool season grass. WS/CS = warm season grass over-sown with cool season grass. The box represents 50% of the dataset, ends of the box show the 1st and 3rd quartiles, whiskers extend to the furthest data point within 1.5*IQR from the 1st and 3rd quartiles. ‘X’within box = mean. Horizontal line within box = median.

https://doi.org/10.1371/journal.pone.0216364.s001

S1 File. Dataset of shoe-surface traction tests.

https://doi.org/10.1371/journal.pone.0216364.s002

Acknowledgments

We thank Mr Wayne Holmes, Ewen Hodge and Rod Rayner from Aspire Sports Turf, Ned Frederick of Exeter Research, and Dany Baghdan of Aspetar for their expertise, patience and guidance throughout this study. The authors also thank Nike Inc. for suppling the football footwear. Nike Inc. had no role in the design, analysis, interpretation of data or final manuscript approval.

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Physical and Energetic Demand of Soccer: A Brief Review

Dolci, Filippo MSc 1 ; Hart, Nicolas H. PhD 2,3,4 ; Kilding, Andrew E. PhD 5 ; Chivers, Paola PhD 3,4 ; Piggott, Ben MSc 1 ; Spiteri, Tania PhD 2

1 School of Health Science, University of Notre Dame, Fremantle, Australia;

2 School of Medical and Health Science, Edith Cowan University, Perth, Australia;

3 Institute for Health Research, University of Notre Dame, Fremantle, Australia;

4 Exercise Medicine Research Institute, Edith Cowan University, Perth, Australia; and

5 Sports Performance Research Institute New Zealand, AUT University, Auckland, New Zealand

Address correspondence to Filippo Dolci, MSc, [email protected] .

Conflicts of Interest and Source of Funding: The authors report no conflicts of interest and no source of funding.

Soccer is a complex and exhaustive team-sport requiring a high level of tactical, technical, and physical ability to succeed. During a competitive match, a random combination of explosive and powerful activities, together with technical and tactical gestures, is performed in an intermittent manner over a 90-minute game. This review presents a detailed analysis and up-to-date synthesis of the literature describing activities and energy system contribution during soccer to provide to strength and conditioning coaches a clear understanding of soccer players' physical needs during competition.

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Strength and conditioning for soccer players, a testing battery for the assessment of fitness in soccer players, effects of plyometric training on sports performance, periodization in college soccer, monitoring athlete load: data collection methods and practical recommendations.

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The physics of football : discover the science of bone-crunching hits, soaring field goals, and awe-inspiring passes

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The Influence of Soccer Shoe Design on Player Performance and Injuries

• Research in Sports Medicine An International Journal 19(3):186-201
• 19(3):186-201

• Queensland University of Technology

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Magnetic fields on the sun could solve longstanding solar heating mystery

When you buy through links on our articles, Future and its syndication partners may earn a commission.

Scientists have long wondered why the hot soup of charged particles in our sun's atmosphere gets hotter moving away from the surface of the sun.

New research may have the answer, finding the super-hot nature of the sun's outer atmosphere or " corona " could be due to the intriguing behavior of small-scale waves in this nebulous plasma. These waves, known to scientists as "kinetic Alfvén waves" or "KAWs," are wave-like vibrations of magnetic fields manifested by motions in the sun's photosphere.

The findings could provide an important clue to decoding the seemingly physics-defying " coronal heating mystery " of why the corona is hundreds of times hotter than the visible solar "surface" or photosphere that radiates all the light we see from the sun.

The team behind this research, led by Syed Ayaz, a researcher at the University of Alabama in Huntsville, theorizes that as KAWs propagate, they dissipate and heat the sun's corona. Thus they serve as an important, albeit small-scale, mechanism by which energy is transferred within the sun's plasma.

Related: Watch a colossal X-class solar flare erupt from Earth-facing sunspot (video)

Ayaz said this phenomenon could explain why the sun's visible surface is around 10,000 degrees Fahrenheit (5,500 degrees Celsius) while the corona, which marks the uppermost part of the sun's atmosphere, is over 2 million degrees Fahrenheit (1.1 million degrees Celsius).

"For decades, Alfvén waves have been proven to be the best candidates for transporting energy from one place to another," Ayaz said in a recent statement . "So far, no solar spacecraft mission has provided predictions regarding these phenomena close to the sun."

How the corona heating mystery defies physics

The majority of the sun's energy comes from its core, where nuclear fusion occurs. That means the sun  should  get hotter as one moves deeper within it. Most of the layers of our star obey this principle. However, the corona, despite being millions of miles further away from the solar core than the sun's surface, is still vastly hotter than the photosphere.

Ayaz and his colleagues studied the influence of KAWs in the plasma floating up to an altitude equal to 10 times the sun's radius. At such distances, when the waves interact with the sun's charged plasma, which is packed with "ions," atoms that have been stripped of their electrons, they "rapidly dissipate, completely transferring their energy to plasma particles in the form of heating," Ayaz said.

The team's findings suggest energy from the waves can reach the corona and heat it, although just how much they contribute to the temperature of the corona remains to be seen.

This new research "offers important insights into the critical problem of how energy in a magnetic field is transformed to heat a plasma comprising charged particles like protons and electrons," said Gary Zank, director of the Center For Space Plasma And Aeronomic Research at the University of Alabama who was not involved with work.

The findings of the latest study are strengthened by data from the European Space Agency's Solar Orbiter and NASA's Solar Dynamics Observatory (SDO). The SDO previously found that another kind of high-frequency, arch-like magnetic wave propagating through the corona can also dump large amounts of energy into the outer atmosphere of the sun over time, contributing to the heating of the million-degree-hot layer.

Similar processes that supply heat to the sun's corona were the focus of a recent NASA sounding rocket mission. The mission, named MaGIXS-2 —short for the second flight of the Marshall Grazing Incidence X-ray Spectrometer, was launched into space for a few minutes in mid-July to collect X-rays from the sun.

Those rays are particularly telling of how often bursts of energy are released within our star, which may help scientists unveil more about how the corona is heated.

Related stories:

— How Solar Orbiter is decoding the sun's mysterious miniflares: 'What we see is just the tip of the iceberg'

— Solar storm forecasts could soon get a big boost. Here's how.

— The sun's next solar cycle has begun, 'starquakes' suggest

Even as scientists continue to piece together the puzzle of how the sun's corona gets so hot, other heating mechanisms related to the sun's magnetic field are being ruled out. For instance, scientists suspected certain S-shaped bends in the sun's magnetic field packed a lot of magnetic energy that is released into the surrounding plasma, heating it up and accelerating storm-sparking solar winds.

However, an analysis of Parker Solar Probe's first 14 laps around the sun reported in a separate paper published on Monday in The Astrophysical Journal Letters found no evidence of the sought-after feature inside the corona.

Mojtaba Akhavan-Tafti, a research scientist at the University of Michigan who led the study, noted in a statement that the Parker Solar Probe's upcoming trips into the sun, likely as soon as December this year, could reveal more insights into the decades-old mystery.

The team's study was published last week in The Astrophysical Journal.

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Physicist Rosemary Fowler honoured 75 years after discovering the kaon particle

The physicist Rosemary Fowler has had to wait three quarters of a century to be honoured for her role in discovering a subatomic particle.

Fowler was doing a PhD at the University of Bristol in 1948 under the supervision of physicist Cecil Powell when she stumbled upon the particle.

The then 22-year-old physicist spotted unusual particle tracks in photographic emulsions that had been exposed to cosmic rays at high altitude in Switzerland.

She discovered a particle that decayed into three pions and labelled the track ‘k’, with the particle now known as the K-meson or “kaon”.

“I knew at once that it was new and would be very important,” Fowler noted . “We were seeing things that hadn’t been seen before – that’s what research in particle physics was. It was very exciting.”

The results were published in two papers in Nature with Fowler (née Brown) as first author. She then decided to leave university and married fellow Bristol physicist Peter Fowler – the grandson of Ernest Rutherford – in 1949. They had three children, all of whom went on to study science. Peter died in 1996.

This week Fowler, who is 98, was finally honoured for her work. She received an honorary doctorate from Bristol University in a private graduation ceremony held near her Cambridge home.

Fowler said she felt “very honoured” by the doctorate, but added humbly that she hadn’t “done anything since to deserve special respect”.

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