Advanced Sports Analysis Using Opta Course


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Register for this course

We are proud to offer this course in a variety of training formats to suit your needs. We use the highest quality learning facilities to make sure your experience is as comfortable as possible. Our face to face calendar allows you to choose any classroom course of your choice to be delivered at any venue of your choice - offering you the ultimate in convenience and value for money.


June 2024

Code Date Duration Location Fee Action
ASO101 24 Jun 2024 - 5 Jul 2024 10 days Kisumu, Kenya KES 165,000 | $2,200 Register
ASO101 17 Jun 2024 - 28 Jun 2024 10 days Kampala, Uganda $3,300 Register
ASO101 24 Jun 2024 - 5 Jul 2024 10 days Pretoria, South Africa $4,400 Register
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June 2024

Code Date Duration Mode Fee Action
ASO101 17 Jun 2024 - 28 Jun 2024 10 days Half-day KES 120,000 | USD 1,398 Register
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June 2024

Date
Duration
Location
Fee
Action
24 Jun - 5 Jul 2024
10 days
Kisumu
KES 165,000 $2,200
17 Jun - 28 Jun 2024
10 days
Kampala
$3,300
24 Jun - 5 Jul 2024
10 days
Pretoria
$4,400
I Want To See More Dates...

June 2024

Code Date Duration Mode Fee Action
ASO101 17 Jun 2024 - 28 Jun 2024 10 days Half-day KES 120,000 | USD 1,398 Register
I Want To See More Dates...

Introduction

Welcome to the Advanced Sports Analysis course with Opta! This course will take you on a journey into the world of sports analysis using Opta's comprehensive data. Whether you're a sports analyst, coach, or simply passionate about sports, this course will equip you with the skills to extract valuable insights and make data-driven decisions.

Throughout the course, you will learn how to collect, preprocess, and analyze Opta data to uncover patterns, trends, and performance indicators. We will also explore statistical analysis techniques and visualization tools to present your findings effectively.

Additionally, we will delve into the exciting realm of predictive modeling, enabling you to build models that forecast sports outcomes and give you a competitive edge.

Ethical considerations will be emphasized throughout the course, ensuring responsible data analysis and respect for privacy and security.

Join us as we unlock the power of Opta data and elevate our sports analysis skills to new heights. Get ready to gain deeper insights into sports performance and enhance your understanding of the game.

Duration

10 Days

Who should attend?

  • Sports Analysts
  • Coaches and Team Managers
  • Sports Scientists
  • Data Analysts and Data Scientists
  • Sports Enthusiasts

Course Level:
  • Understanding Opta: Participants will gain a thorough understanding of the features, functionalities, and capabilities of the Opta. They will learn how to navigate the software interface, access relevant data, and utilize various tools and modules for sports analysis.
  • Data Collection and Management: Participants will learn techniques for collecting, organizing, and managing sports data within the Opta. They will explore different data sources, including APIs, databases, and external files, and understand how to import, clean, and preprocess data for analysis.
  • Advanced Statistical Analysis: The course will cover advanced statistical analysis techniques specific to sports analytics. Participants will learn how to apply statistical models, regression analysis, and data visualization methods to extract meaningful insights from sports data using the Opta.
  • Performance Analysis: Participants will delve into performance analysis by examining key performance indicators (KPIs) and metrics in sports. They will learn how to use the Opta to evaluate player performance, team dynamics, and tactical strategies through video analysis, tracking data, and other relevant sources.
  • Predictive Modeling and Machine Learning: The course will introduce participants to predictive modeling and machine learning algorithms within the context of sports analysis. They will explore how to build predictive models, forecast outcomes, and identify patterns and trends using the Opta
  • Reporting and Visualization: Participants will learn how to effectively communicate their analysis findings through comprehensive reports and visually appealing visualizations. They will explore the reporting capabilities of the Opta and develop skills in creating insightful dashboards and presentations.
  • Practical Application and Case Studies: Throughout the course, participants will engage in hands-on exercises, practical assignments, and real-world case studies to apply their knowledge and skills in sports analysis using the Opta. They will have the opportunity to analyze various sports datasets and tackle challenging analytical problems.

Module 1: Introduction to Opta Sports Data

  • Understanding the Opta sports data provider
  • Exploring the types of data available through Opta
  • Familiarizing with data formats and structures

Module 2: Data Collection and Preprocessing

  • Techniques for collecting Opta sports data
  • Cleaning and preprocessing data for analysis
  • Handling missing or inconsistent data

Module 3: Statistical Analysis in Sports

  • Applying statistical analysis techniques to Opta data
  • Analyzing player performance and team dynamics
  • Exploring correlations and patterns in sports data

Module 4: Advanced Metrics and Performance Analysis

  • Evaluating performance using advanced metrics
  • Analyzing player and team contributions
  • Identifying key performance indicators (KPIs)

Module 5: Tactical Analysis and Visualization

  • Visualizing Opta data for tactical analysis
  • Identifying patterns and trends in team strategies
  • Using visualizations to communicate insights

Module 6: Predictive Modeling in Sports

  • Introduction to predictive modeling using Opta data
  • Building predictive models for sports outcomes
  • Evaluating model performance and accuracy

Module 7: Case Studies and Practical Application

  • Applying Opta data analysis to real-world sports scenarios
  • Analyzing specific sports events or matches
  • Presenting findings and insights through reports and presentations

Module 8: Ethical Considerations in Sports Analysis

  • Understanding the ethical implications of sports data analysis
  • Ensuring data privacy and security
  • Addressing potential biases and limitations in analysis

Module 9: Future Trends in Sports Analysis

  • Exploring emerging technologies and trends in sports analysis
  • Discussing the impact of AI and machine learning in sports
  • Considering the future of Opta data and its applications

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Course Administration Details:

METHODOLOGY

The instructor-led training is delivered using a blended learning approach and comprises of presentations, guided sessions of practical exercise, web-based tutorials and group work. Our facilitators are seasoned industry experts with years of experience, working as professional and trainers in these fields.

All facilitation and course materials will be offered in English. The participants should be reasonably proficient in English.

ACCREDITATION

Upon successful completion of this training, participants will be issued with an Indepth Research Institute (IRES) certificate certified by the National Industrial Training Authority (NITA).

TRAINING VENUE

The training will be held at IRES Training Centre. The course fee covers the course tuition, training materials, two break refreshments and lunch.

All participants will additionally cater for their, travel expenses, visa application, insurance, and other personal expenses.

ACCOMMODATION AND AIRPORT PICKUP

Accommodation and airport pickup are arranged upon request. For reservations contact the Training Officer.

Email:[email protected].  

Mob: +254 715 077 817

TAILOR- MADE

This training can also be customized to suit the needs of your institution upon request. You can have it delivered in our IRES Training Centre or at a convenient location.

For further inquiries, please contact us on Tel: +254 715 077 817.

Mob: +254 792516000+254 792516010 or mail [email protected]

PAYMENT

Payment should be transferred to IRES account through bank before the course start date

Send proof of payment to [email protected]


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