Evidence map›Paper›PMID 40650426›Full record

ArticleEuropean journal of sport science2025

Tackle Height and Tackle Success-An Analysis of 52,204 Tackle Events.

S Hendricks, K Till, S Scantlebury, N Dalton-Barron, S den Hollander, N Gill, S Kemp, A Kilding, M Lambert, P Mackreth and 12 more

Abstract read
In one paragraph

Article in European journal of sport science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

22 authors.

S HendricksDivision of Physiological Sciences and Health Through Physical Activity, Lifestyle and Sport Research Centre, Department of Human Biology, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa.ORCID https://orcid.org/0000-0002-3416-6266
K TillCarnegie Applied Rugby Research (CARR) Centre, Carnegie School of Sport, Leeds Beckett University, Leeds, UK.
S ScantleburyCarnegie Applied Rugby Research (CARR) Centre, Carnegie School of Sport, Leeds Beckett University, Leeds, UK.
N Dalton-BarronCarnegie Applied Rugby Research (CARR) Centre, Carnegie School of Sport, Leeds Beckett University, Leeds, UK.
S den HollanderDivision of Physiological Sciences and Health Through Physical Activity, Lifestyle and Sport Research Centre, Department of Human Biology, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa.ORCID https://orcid.org/0000-0002-6064-038X
N GillDivision of Health, Engineering, Computing and Science, Te Huataki Waiora School of Health, University of Waikato, Tauranga, New Zealand.
S KempRugby Football Union, London, UK.
A KildingSports Performance Research Institute New Zealand, Auckland University of Technology, Auckland, New Zealand.
M LambertDivision of Physiological Sciences and Health Through Physical Activity, Lifestyle and Sport Research Centre, Department of Human Biology, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa.
P MackrethCarnegie Applied Rugby Research (CARR) Centre, Carnegie School of Sport, Leeds Beckett University, Leeds, UK.
J O'ReillyDepartment of Sports Science and Physical Education, The Chinese University of Hong Kong, Shatin, Hong Kong.
C OwenCarnegie Applied Rugby Research (CARR) Centre, Carnegie School of Sport, Leeds Beckett University, Leeds, UK.
K SpencerSports Performance Research Institute New Zealand, Auckland University of Technology, Auckland, New Zealand.
K StokesRugby Football Union, London, UK.
J TeeCarnegie Applied Rugby Research (CARR) Centre, Carnegie School of Sport, Leeds Beckett University, Leeds, UK.
R TuckerWorld Rugby, Dublin, Ireland.
L VazResearch Center in Sports Sciences, Health Sciences and Human Development (CIDESD), University of Trás-os-Montes and Alto Douro, Vila Real, Portugal.
D WeavingCarnegie Applied Rugby Research (CARR) Centre, Carnegie School of Sport, Leeds Beckett University, Leeds, UK.
S W WestCentre for Health, Injury and Illness Prevention in Sport, University of Bath, Bath, UK.ORCID https://orcid.org/0000-0001-5800-7000
K DaneSport Injury Prevention Research Centre, Faculty of Kinesiology, University of Calgary, Calgary, Canada.ORCID https://orcid.org/0000-0001-8083-6278
F McKnightDivision of Physiological Sciences and Health Through Physical Activity, Lifestyle and Sport Research Centre, Department of Human Biology, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa.ORCID https://orcid.org/0009-0003-9405-8800
B JonesDivision of Physiological Sciences and Health Through Physical Activity, Lifestyle and Sport Research Centre, Department of Human Biology, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa.ORCID https://orcid.org/0000-0002-4274-6236

Funding

World Rugby
6 · The paper itself

Abstract

To compare the probability of tackle success (the tackler preventing the ball-carrier and ball from progressing towards the tackler try-line) when contacting the ball-carrier at different heights (shoulder, mid-torso and legs) for different types of tackles (active, passive, smother and arm) while accounting for other tackler situational factors within seven playing levels. Video footage of 271 male rugby union matches were analysed across seven playing groups (Under [U] 12, n = 25 matches; U14, n = 35; U16, n = 39; U18 Amateur n = 39; U18 Elite n = 38; Senior Amateur, n = 40 and Senior Elite, n = 50) across England, New Zealand, South Africa, Portugal and USA (a total of 51,106 tackles). A multi-level logistic regression model with tackle success as the outcome variable and first point of contact and type of tackle as the explanatory variables were computed. Included in the model as cofounders were the situational variables tackle direction, tackle sequence, number of players in the tackle and attacker intention. Post-estimation marginal effects were used to calculate the probabilities (expressed as a percentage %) of tackle success for each interaction between tackle type (active shoulder, smother, passive shoulder and arm) and the first point of contact (shoulder, mid-torso and legs). The probability of tackle success in relation to where the ball-carrier is contacted varied by tackle type and within each age group. The probabilities (Pr) for contacting the shoulder versus mid-torso at the senior levels (elite and amateur) did not differ in relation to tackle success (for instance, for active shoulder tackles within senior elite; shoulder Pr 86% 95% CI 82-89 and mid-torso Pr 82% 95% CI 77-86), whereas at the junior levels, contacting the shoulder had a higher probability than other points of contact. Active shoulder tackles had the highest probability of tackle success across the different playing levels across the different contact heights, whereas arm tackles had the lowest probability (for instance, for mid-torso tackles within senior elite, active Pr 82% 95% CI 77-86 vs. arm Pr 69% 95% CI 64-75). Coaches and practitioners can use this information to improve tackle training design and planning within the different age groups and facilitate player development.

Indexed as

Athletic PerformanceCompetitive BehaviorFootballHumansLogistic ModelsMaleShoulderVideo Recordinggame analysisinjury and preventionperformanceskillteam sport

Identifiers

PMID40650426
PMCPMC12254575

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.