Evidence map›Paper›PMID 42257757›Full record

SynthesisSports medicine - open2026

The Impact of Football Boot Design on Lower Limb Injury Risk: A Systematic Review.

Fan Yang, Jingxuan Huang, Qiang Wei, Liang Jiang, Dong Liang

Abstract readSystematic Review
In one paragraph

Synthesis in Sports medicine - open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Fan Yang *Li Ning Sports Science Application Research Center, Li Ning (China) Sports Goods Company Limited, Beijing, People's Republic of China.
Jingxuan Huang *China Football College of Beijing Sport University, Beijing, People's Republic of China.
Qiang WeiDepartment of Physical Education, Tangshan Normal University, Tangshan, People's Republic of China.
Liang JiangLi Ning Sports Science Application Research Center, Li Ning (China) Sports Goods Company Limited, Beijing, People's Republic of China. jiangliang2@li-ning.com.cn.
Dong LiangChina Football College of Beijing Sport University, Beijing, People's Republic of China. 869994796@qq.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFootball boots-serving as the critical interface between the player and the playing surface-play a decisive role in modulating the risk of non‑contact lower‑limb injuries. Although numerous studies have investigated the effects of stud configuration, sole‑plate stiffness, and boot-foot-surface interaction on lower‑limb biomechanics, an integrated evaluation of their injury implications remains lacking.

methodsFollowing PRISMA 2020 guidelines, a systematic search (2005-2025) was conducted across Elsevier, EBSCO, Web of Science, PubMed Central, and Footwear Science. Thirty‑two studies met the inclusion criteria after dual‑reviewer screening, and methodological quality was assessed using the PEDro scale.

resultsEvidence was triangulated to identify biomechanical mechanisms underpinning injury risk as influenced by boot design. Five principal findings emerged: 1. Stud pattern governs rotational traction. Screw-in (Soft Ground (SG)) and bladed studs generate supra-physiological rotational torque on both natural and artificial turf, producing a "foot-lock" phenomenon that elevates the incidence of anterior cruciate ligament (ACL) rupture, ankle sprain, and metatarsal stress fracture. 2. Sole-plate stiffness shows a U-shaped relationship with injury risk. Excessive rigidity restricts first-ray dorsiflexion and precipitates focal plantar pressures, whereas excessive compliance amplifies ankle dorsiflexion/inversion and knee-valgus angles, thereby increasing ACL loading. 3. Boot-foot-surface mismatch (undersized lasts, stud-surface incompatibility, sex-specific traction overload) redistributes plantar pressure and alters joint moment arms, fostering over-use injuries. 4. Collar height augments ankle stability but induces compensatory knee torsion, shifting the failure locus proximally and raising the likelihood of knee-ligament trauma. 5. High-risk mechanical loading often occurs below athletes' perceptual thresholds, suggesting that asymptomatic microdamage may accumulate over time.

conclusionsCollectively, football‑boot architecture represents a modifiable determinant of non‑contact lower‑limb injury. Establishing standardized testing frameworks that calibrate stud geometry, sole‑plate stiffness, and last morphology-while accounting for surface type, sex, and playing level-will enable optimization of high‑performance yet low‑injury boot design.

Indexed as

Ankle injuryFootball boot designFoot injuryKnee-joint injuryLower-limb injury

Identifiers

PMID42257757
PMCPMC13246976

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.