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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 ...

Simpson University

Head Flag Football Coach

Redding, CA · On-site

Description The Head Women's Flag Football Coach primary responsibility is to lead the flag ... Analysis of Physical Demands to Perform Essential Functions: Key (Based on typical week): N=Never R ...

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How much do football analytics jobs pay per month?

As of May 29, 2026, the average monthly pay for football analytics in the United States is $6,290.58, according to ZipRecruiter salary data. Most workers in this role earn between $5,708.33 and $6,708.33 per month, depending on experience, location, and employer.

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

To excel in Football Analytics, you need a strong background in statistics, mathematics, and data analysis, often supported by a relevant degree in data science, statistics, or sports management. Familiarity with programming languages like Python or R, experience with data visualization tools, and knowledge of sports analytics platforms such as Opta or Wyscout are typically required. Strong communication, critical thinking, and problem-solving skills help you turn complex data into actionable insights for coaches and teams. These capabilities are crucial for driving data-informed decision-making and gaining a competitive edge in the football industry.

How does a Football Analytics professional typically collaborate with coaches and players to influence game strategy?

Football Analytics professionals work closely with coaching staff to translate complex data into actionable insights that can enhance team performance. They often attend team meetings, present analytical findings, and provide real-time feedback during games or training sessions. Their role involves not just analyzing player performance and opposition tendencies, but also communicating these insights effectively to coaches and sometimes directly to players. This collaboration ensures that analytical recommendations are practical and can be seamlessly integrated into game plans and player development.

What is football analytics?

Football analytics refers to the use of data analysis and statistical methods to evaluate and improve performance in football (soccer or American football). Analysts collect and interpret data on players, teams, matches, and tactics to support decision-making by coaches, scouts, and management. The field covers areas such as player recruitment, in-game strategy, injury prevention, and opponent analysis. With the rise of technology and advanced metrics, football analytics is increasingly shaping how teams gain a competitive edge.

What is the difference between Football Analytics vs Football Data Analyst?

AspectFootball AnalyticsFootball Data Analyst
Required CredentialsDegree in Sports Science, Data Science, or related fields; knowledge of statistics and programmingSimilar credentials; often includes experience with data analysis tools and sports knowledge
Work EnvironmentSports teams, analytics firms, or media companies focusing on performance analysisSports teams, analytics departments, or consulting firms analyzing game data
Industry UsageUsed for strategic decision-making, player evaluation, and performance optimizationUsed for reporting, data interpretation, and supporting coaching staff

Football Analytics and Football Data Analyst roles share similar educational backgrounds and work environments. While Football Analytics often involves developing models and strategic insights, Football Data Analysts focus more on interpreting data for reports and coaching support. Both roles are essential in the sports industry for enhancing team performance and decision-making.

More about Football Analytics jobs
What cities are hiring for Football Analytics jobs? Cities with the most Football Analytics job openings:
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What job categories do people searching Football Analytics jobs look for? The top searched job categories for Football Analytics jobs are:
Football Analytics jobs near you
Infographic showing various Football Analytics job openings in the United States as of May 2026, with employment types broken down into 4% Internship, 38% Full Time, 20% Part Time, 2% Temporary, and 36% Contract. Highlights an 30% Physical, and 70% Remote job distribution, with an average salary of $75,487 per year, or $36.3 per hour.

Sr. Football Data Scientist

SumerSports LLC

Remote

Full-time

Medical, Retirement

Posted 6 days ago

Job description

SumerSports is a leading football intelligence technology company that specializes in providing an innovative suite of products for football fans and NFL clubs. We are a collection of executives, engineers, data scientists, and visionaries from NFL clubs, technology startups, finance, and academia.
Our data-driven platform empowers teams with insights and tools to make informed decisions within salary cap constraints. The platform also serves the NCAA, offering insights around the transfer portal and more.
What sets us apart is our unique blend of big tech talent, data scientists, and former NFL personnel, who have a combined 600+ years of NFL experience. Our domain knowledge is augmented by AI and machine learning technologies to create a unique view into many aspects of Football.
We are seeking a motivated and skilled Senior Data Scientist to join our analytics team. You will be responsible for building, deploying, and refining a variety of football-focused analytical models, working with complex real-world datasets. You'll collaborate closely with other data scientists and engineers, ensuring our analytical products are accurate, robust, and impactful. The ideal candidate will demonstrate both strong technical skills and a proactive mindset, capable of independently taking projects from concept to deployment.
Responsibilities
  • Model Development and Analysis: Build and implement analytical football models, providing valuable insights to enhance our football analytics offerings. Conduct comprehensive data analysis to extract actionable insights.
  • Model Productionization: Ensure seamless deployment of machine learning and statistical models using Python, Databricks, and Spark. You will work on converting existing R models to Python as part of your initial responsibilities.
  • Large Dataset Management: Handle large datasets efficiently using Spark and Databricks, ensuring data integrity and performance optimization.
  • Collaboration: Work closely with other data scientists, analysts, and stakeholders to understand their needs and deliver high-quality analytical solutions.
  • Innovation: Identify and implement new tools, techniques, and best practices to enhance our data analytics capabilities.

Qualifications
Education: Advanced degree (Masters or PhD) in a quantitative discipline, or equivalent professional experience.
Experience: 4+ years of experience in data science, preferably in a sports analytics environment. (level commensurate with experience)
Technical Skills:
  • Proficiency in Python and experience with Databricks.
  • Strong programming skills in Python, including experience deploying models beyond exploratory notebooks.
  • Documented experience in football analytics, demonstrated through industry experience, public content, or
    significant independent projects. Examples would include working for an NFL or NCAA analytics department, working for a third party analytics provider, achievement in events such as the Big Data Bowl, or original football analytics Github repos.
  • Solid foundation in statistical modeling and machine learning methodologies.
  • Proven ability to independently identify and resolve data-related challenges in real-world datasets.
  • Effective communication skills, with experience explaining technical concepts clearly

Benefits
  • Competitive Salary and Bonus Plan
  • Comprehensive health insurance plan
  • Retirement savings plan (401k) with company match
  • Remote working environment
  • A flexible, unlimited time off policy
  • Generous paid holiday schedule - 13 in total including Monday after the Super Bowl

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