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Football Data Analyst Jobs (NOW HIRING)

Swish Analytics

Sports Data Analyst

San Francisco, CA · On-site +1

Minimum of 1 year of experience in football data analysis * Deep knowledge of football, basketball or baseball; including roster compositions of professional and college teams, general gameplay ...

SumerSports LLC

Sr. Football Data Scientist

Build and implement analytical football models, providing valuable insights to enhance our football analytics offerings. Conduct comprehensive data analysis to extract actionable insights. * Model ...

Bay Football Club

Head of Data & Analytics

San Jose, CA · On-site

$140K/yr

While our community is our foundation, our love of football is our reason for being. We have the ... Position Summary The Head of Data & Analytics will lead the execution and adoption of Bay FC's data ...

SumerSports LLC

Product Manager

Position Summary We're a small but mighty group of Product Managers that work with our in-house experts and customers to build this next generation of Football Data Analytics and AI experiences for ...

SumerSports LLC

Sr. Product Manager

$129K - $170K/yr

Position Summary We're a small but mighty group of Product Managers that work with our in-house experts and customers to build this next generation of Football Data Analytics and AI experiences for ...

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Football Data Analyst information

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$34K

$82.6K

$136K

How much do football data analyst jobs pay per year?

As of Jul 11, 2026, the average yearly pay for football data analyst in the United States is $82,640.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,500.00 and $97,000.00 per year, depending on experience, location, and employer.

How much money does a football analyst make?

Football data analysts typically earn between $40,000 and $80,000 annually, depending on experience, location, and the level of the organization. Senior analysts or those working with top-tier teams can earn higher salaries, often exceeding $100,000 with additional bonuses or benefits.

How to become a data analyst in football?

To become a football data analyst, you typically need a degree in a relevant field such as statistics, data science, or sports management. Developing skills in data analysis tools like Excel, SQL, and programming languages such as Python or R is essential, along with knowledge of football tactics and performance metrics. Gaining experience through internships or entry-level roles in sports organizations can also improve job prospects.

What are the key skills and qualifications needed to thrive in the Football Data Analyst position, and why are they important?

To thrive as a Football Data Analyst, you need strong statistical analysis skills, expertise in football tactics, and usually a degree in mathematics, statistics, sports science, or a related field. Proficiency in data analysis tools like Python, R, SQL, and sports analytics platforms such as Opta or Wyscout is commonly required, along with certifications in data analysis or relevant software. Attention to detail, effective communication, and teamwork are vital soft skills for conveying insights to coaches and collaborating with diverse teams. These skills enable the analyst to accurately interpret data, support performance improvements, and drive informed decision-making within a competitive sports environment.

How much do NFL data analysts make?

NFL data analysts typically earn between $50,000 and $100,000 annually, depending on experience, education, and the level of responsibility. Entry-level positions may start lower, while experienced analysts with advanced skills in data visualization and statistical software can earn higher salaries, especially with additional certifications or specialized knowledge.

What are some typical daily responsibilities of a Football Data Analyst?

A Football Data Analyst typically spends their day collecting and processing match or training data, conducting statistical analyses to identify trends, and preparing reports or visualizations for coaches and management. They often attend team meetings to discuss insights and collaborate closely with coaching staff and other performance professionals. The role also involves staying updated on the latest analytical tools and methods, ensuring the team leverages cutting-edge techniques. Effective communication and adaptability are essential, as priorities can shift quickly based on match schedules or management needs.

Do NFL teams hire data analysts?

Yes, NFL teams often hire data analysts to evaluate player performance, develop strategies, and improve decision-making using statistical tools and data analysis techniques. These roles typically require knowledge of sports analytics, programming skills, and familiarity with data visualization software. Data analysts in sports may work closely with coaching staff and management to enhance team performance.

What is a Football Data Analyst job?

A Football Data Analyst collects, processes, and interprets football-related data to provide insights for teams, coaches, and scouts. They use statistical analysis, tracking data, and performance metrics to evaluate players, tactics, and opposition strategies. Their work helps improve team performance, recruitment decisions, and match preparation. Analysts often use software, coding languages, and data visualization tools to present findings effectively.

More about Football Data Analyst jobs
What cities are hiring for Football Data Analyst jobs? Cities with the most Football Data Analyst job openings:
What are the most commonly searched types of Football Data Analyst jobs? The most popular types of Football Data Analyst jobs are:
What states have the most Football Data Analyst jobs? States with the most job openings for Football Data Analyst jobs include:
What job categories do people searching Football Data Analyst jobs look for? The top searched job categories for Football Data Analyst jobs are:
Football Data Analyst jobs near you
Infographic showing various Football Data Analyst job openings in the United States as of July 2026, with employment types broken down into 1% Locum Tenens, 1% Internship, 86% Full Time, 6% Part Time, 1% Temporary, and 5% Contract. Highlights an 82% Physical, 5% Hybrid, and 13% Remote job distribution, with an average salary of $82,640 per year, or $39.7 per hour.
Sports Data Analyst

Sports Data Analyst

Swish Analytics

San Francisco, CA • On-site, Remote

Full-time

Re-posted 15 days ago

Job description

Company Description
Swish Analytics is a sports analytics, betting and fantasy startup building the next generation of predictive sports analytics data products. We believe that oddsmaking is a challenge rooted in engineering, mathematics, and sports betting expertise; not intuition. We're looking for team-oriented individuals with an authentic passion for accurate and predictive real-time data who can execute in a fast-paced, creative, and continually-evolving environment without sacrificing technical excellence. Our challenges are unique, so we hope you are comfortable in uncharted territory and passionate about building systems to support products across a variety of industries and consumer/enterprise clients.
Duties:
  • Work closely with Data Scientists and Engineers to diagnose and treat data pipeline integrity issues
  • Detect data inaccuracies such as missing, out of range or otherwise incorrect on-field data
  • Source origins of data inaccuracies through data pipeline dependencies and python code base
  • Define data validation tests to flag future game errors
  • Research accurate roster active statuses, primary positions and game participation
  • Validate data changes after logic updates
  • Production model feature deep dives to explain project market lines
  • Clearly document findings
  • Develop intimate familiarity with existing databases and construct metadata references
  • With guidance, support lead Data Scientists in feature development and model analysis

Requirements:
  • Bachelor's Degree in Computer Science, Data Science or similar major
  • Minimum of 1 year of experience in football data analysis
  • Deep knowledge of football, basketball or baseball; including roster compositions of professional and college teams, general gameplay strategies, and typical in-game scenarios
  • Data Extraction, Wrangling and Analysis in Python
  • Strong SQL querying skills
  • Attention to detail

Preferred:
  • Strong Python data management programming skills
  • Data Visualization experience with a user application like Streamlit
  • Deep knowledge of a second sport including football, basketball, baseball, hockey or tennis
  • Exposure to the data science process and tech stack
  • Anomaly Detection Techniques

Swish Analytics is an Equal Opportunity Employer. All candidates who meet the qualifications will be considered without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, pregnancy status, genetic, military, veteran status, marital status, or any other characteristic protected by law. The position responsibilities are not limited to the responsibilities outlined above and are subject to change. At the employer's discretion, this position may require successful completion of background and reference checks.
Department Data Science Role NFL Team Locations San Francisco, CA - Remote Remote status Fully Remote

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