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Sport Performance Analytic Methods

Sport Performance Analytic Methods

9781718217911
585,90 zł
556,60 zł Zniżka 29,30 zł Brutto
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Opis
In todays sports world, decision makers, coaches, trainers, and athletes readily embrace sport performance analytics (SPA) and expect decisions to be based on such analyses. Organizations adept at collecting data, analyzing data, and applying findings enjoy a competitive advantage on the field—and a positive impact on the bottom line. For sport management students with a passion for sports and an aptitude for analytics, SPA presents an enticing career choice—one in high demand.

Sport Performance Analytic Methods With HKPropel Access not only introduces students to the field of sport performance analytics but also walks them through the entire SPA process. This unparalleled approach equips students to employ SPA tools and techniques to make informed decisions affecting organization performance and success.

The content of the book is driven by the SPA model, a seven-step process providing a guided pathway for conducting SPA analyses::
  • Establish what you want to know
  • Define the data you will collect
  • Determine the data collection process and collect data
  • Analyze the data
  • Interpret the results
  • Present the results
  • Make data-based decisions
The opening chapter emphasizes the importance of establishing the SPA objectives. The focus then shifts to understanding foundational data concepts, with discussions on quantitative and qualitative data, types and scale of variables, temporal aspects of data, process and product data, and validity and reliability of data. Methods and tools for collecting data are explored next, including technology-assisted data acquisition tools such as wearable devices and biometric sensing devices.

Students will then examine quantitative statistical concepts that can be used to analyze data and even help make predictions about future player or team performance. Key concepts include descriptive statistics, data sets, inferential statistics, group comparisons, and linear regressions.

The text also addresses techniques for collecting and analyzing qualitative data—including observation, content, narrative, discourse, thematic, and grounded theory analyses—ensuring that all forms of data are considered to produce successful outcomes.

Finally, the text demonstrates how to present SPA data in a format useful to apply in decision making. Students learn how coaches and performance data analysts use data to inform pre- and postcompetition strategic and tactical plans, make in-game decisions, evaluate team and individual performance, and make decisions for teams, players, and organizations.

Related online resources, delivered via HKPropel, provide students with hands-on learning tools. In addition to descriptions of the primary SPA software packages, included are eight learning modules that allow students to go through various statistical procedures step by step, inputting results, checking for accuracy, and improving performance.

With Sport Performance Analytic Methods, students will gain a solid understanding of the principles made famous by Moneyball, and they will learn to use sport analytics to improve sport performance outcomes.

Note:: A code for accessing HKPropel is included with all new print books.
Szczegóły produktu
Human Kinetics
100697
9781718217911
9781718217911

Opis

Rok wydania
2024
Numer wydania
1
Oprawa
miękka foliowana
Liczba stron
224
  • Chapter 1. Introduction to Sport Performance Analytics
    Historical Foundations of Sport Performance Analytics
    Steps in the SPA Process
    Scope of Sport Performance Analytics
    Limitations of Sport Performance Analytics

    Chapter 2. Understanding Data
    Data Categories
    Variables
    Unit of Analysis
    Depth of Data
    Validity and Reliability of Data

    Chapter 3. Data Collection
    Measurement Tools
    Collecting Qualitative Data
    Instrument Quality
    Process Approval
    Organizing and Preparing Data
    Data Entry

    Chapter 4. Descriptive Statistics
    Frequency Distributions
    Normal Distribution
    Measures of Central Tendency
    Data Variation

    Chapter 5. Inferential Statistics for Group Comparisons
    Concepts of Hypothesis Testing
    Parametric and Non-Parametric Statistics
    Correlation Coefficient
    t-Test
    Analysis of Variance (ANOVA)
    Multiple Analysis of Variance (MANOVA)
    Analysis of Covariance (ANCOVA)

    Chapter 6. Predictive Statistics
    Simple Linear Regression
    Multiple Linear Regression
    Logistic Regression

    Chapter 7. Qualitative Data Analysis
    Framework and Systematic Observation Analysis
    Content Analysis
    Narrative Analysis
    Discourse Analysis
    Thematic Analysis
    Grounded Theory

    Chapter 8. Data Presentation
    Data Reduction
    Presentation Styles
    Dynamic Data Presentation
    Augmented and Static Data Presentation
    Group and Individual Data Presentation

    Chapter 9. Data-Based Decision Making
    Technical Performance Decisions
    Physiology-Based Decisions
    Safety-Based Decisions
    Strategic and Tactical Decisions
    Dynamic Tactical Decisions
    Prediction-Based Decisions
    Organizational Strategic Data-Based Decisions
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