Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Estimation of the Physical Quantities01:05

Estimation of the Physical Quantities

8.7K
On many occasions, physicists, other scientists, and engineers need to make estimates of a particular quantity. These are sometimes referred to as guesstimates, order-of-magnitude approximations, back-of-the-envelope calculations, or Fermi calculations. The physicist Enrico Fermi was famous for his ability to estimate various kinds of data with surprising precision. Estimating does not mean guessing a number or a formula at random. Instead, estimation means using prior experience and sound...
8.7K
Motion of a Projectile01:23

Motion of a Projectile

3.8K
Projectile motion becomes evident when a player kicks the ball into the air. The launch angle, or the angle at which the ball is kicked, plays a crucial role in determining the trajectory of the projectile. As the ball soars through the air, influenced solely by gravity, its motion can be dissected into two independent velocity components: the horizontal and the vertical.
Horizontal motion, governed by the initial kick, maintains a constant velocity throughout the flight of the soccer ball.
3.8K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Acute psychological responses to formal and small-sided volleyball games in male youth athletes: an exploratory repeated-measures study.

Frontiers in psychology·2026
Same author

Acute Impact of Cold Compression Therapy Across Diverse Age Groups and Physical Conditioning Status: A Randomized Crossover Study.

Journal of sports science & medicine·2026
Same author

Comparative Effects Of 1V1 Vs 3V3 Small-Sided Basketball Training On Body Anthropometric-Related Outcomes And Physical Fitness In Sedentary Female College Students: An 8-Week Randomized Controlled Trial.

Journal of sports science & medicine·2026
Same author

Teaching games for understanding in school handball: a controlled pre-post study with intact Brazilian physical education classes.

Frontiers in psychology·2026
Same author

Physical Fitness and External Training Load Represent Distinct Dimensions of Performance in Female Football Players During the Pre-Season.

Sports (Basel, Switzerland)·2026
Same author

Comparison of Anthropometric and Physical Performance Profiles in Elite Judo and Jiu-Jitsu Athletes.

Sports (Basel, Switzerland)·2026
Same journal

Practice (Doesn´t) Make Perfect Shooters: The Influence of Experience on Penalty Execution in Elite Soccer.

Journal of human kinetics·2026
Same journal

Level of Effort: A Practical Approach for Resistance Training Monitoring and Prescription.

Journal of human kinetics·2026
Same journal

Objective Accuracy in Estimating Repetitions in Reserve in the Back Squat: An Analysis between Experienced vs. Novice Subjects.

Journal of human kinetics·2026
Same journal

Effects of Surface Stability on Muscle Activation during Plank Exercise.

Journal of human kinetics·2026
Same journal

A Correlational Analysis between the Rate of Force Development among the Arm Stroke, the Leg Kick, the Full Stroke and Short Distance Front Crawl Speed in Highly Trained Swimmers.

Journal of human kinetics·2026
Same journal

How Different Physical Qualities Influence Repeated Sprint Ability Tests in Elite Youth Soccer Players?

Journal of human kinetics·2026
See all related articles

Related Experiment Video

Updated: Apr 12, 2026

An Inertial Measurement Unit Based Method to Estimate Hip and Knee Joint Kinematics in Team Sport Athletes on the Field
06:52

An Inertial Measurement Unit Based Method to Estimate Hip and Knee Joint Kinematics in Team Sport Athletes on the Field

Published on: May 26, 2020

8.8K

Using network metrics in soccer: a macro-analysis.

Filipe Manuel Clemente1, Micael Santos Couceiro2, Fernando Manuel Lourenço Martins3

  • 1Polytechnic Institute of Coimbra, Coimbra College of Education, Department of Education, Portugal. ; Faculty of Sport Sciences and Physical Education - University of Coimbra, Portugal.

Journal of Human Kinetics
|May 13, 2015
PubMed
Summary
This summary is machine-generated.

Network analysis reveals team dynamics, showing player connections and participation levels. These metrics help coaches understand team properties and improve training strategies based on match analysis.

Keywords:
game analysismetricsnetworksoccer

More Related Videos

Effects of a Novel Neuromuscular Training Intervention on Jump, Sprint, and Change of Direction in Adult Female Soccer Players
10:08

Effects of a Novel Neuromuscular Training Intervention on Jump, Sprint, and Change of Direction in Adult Female Soccer Players

Published on: June 10, 2025

1.7K
In Vivo Protocol of Controlled Subconcussive Head Impacts for the Validation of Field Study Data
06:14

In Vivo Protocol of Controlled Subconcussive Head Impacts for the Validation of Field Study Data

Published on: April 18, 2019

7.0K

Related Experiment Videos

Last Updated: Apr 12, 2026

An Inertial Measurement Unit Based Method to Estimate Hip and Knee Joint Kinematics in Team Sport Athletes on the Field
06:52

An Inertial Measurement Unit Based Method to Estimate Hip and Knee Joint Kinematics in Team Sport Athletes on the Field

Published on: May 26, 2020

8.8K
Effects of a Novel Neuromuscular Training Intervention on Jump, Sprint, and Change of Direction in Adult Female Soccer Players
10:08

Effects of a Novel Neuromuscular Training Intervention on Jump, Sprint, and Change of Direction in Adult Female Soccer Players

Published on: June 10, 2025

1.7K
In Vivo Protocol of Controlled Subconcussive Head Impacts for the Validation of Field Study Data
06:14

In Vivo Protocol of Controlled Subconcussive Head Impacts for the Validation of Field Study Data

Published on: April 18, 2019

7.0K

Area of Science:

  • Sports Science
  • Network Analysis
  • Team Performance Analytics

Background:

  • Understanding team dynamics is crucial for optimizing sports performance.
  • Traditional analysis methods often overlook intricate player interactions.
  • Network analysis offers a novel approach to quantify team properties.

Purpose of the Study:

  • To propose network methods for measuring specific team properties.
  • To organize these metrics at macro-analysis levels.
  • To analyze player interactions during offensive plays.

Main Methods:

  • Collected interaction data from 577 offensive plays across five matches.
  • Applied network density, heterogeneity coefficient, and centralization metrics.
  • Analyzed data at different stages of the match (1st half, 2nd half, whole match).

Main Results:

  • Network density decreased in the 2nd half (0.32) compared to the 1st half (0.48).
  • Heterogeneity coefficient increased in the 2nd half, indicating shifts in connectivity.
  • Centralization values suggested an even player connectivity, avoiding a 'star topology', especially in the 1st half.

Conclusions:

  • Network metrics effectively identify player connections, their nature, and strength.
  • These metrics provide insights into team cohesion and individual player roles.
  • Network analysis is a powerful tool for coaches to enhance decision-making and training processes.