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Basketball Data Analytics Jobs (NOW HIRING)

Swish Analytics

Sports Data Analyst

San Francisco, CA · On-site +1

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 ...

Rose Quarter

Senior Basketball Researcher

Tualatin, OR · On-site

... drive data-informed decisions. DAY-TO-DAY: * Design, develop, and validate analysis systems ... Have strong intellectual curiosity and basketball acumen, with the ability to connect analytical ...

CSU

Director, Basketball Sports Performance

Campus, IL · On-site

Ability to analyze and solve problems and deal effectively with short notice change and competing ... Ability to compile data and information and prepare reports. * Proficient in Microsoft Office Suite ...

Simpson University

Assistant Basketball Coach

Redding, CA · On-site

$16.90 - $20/hr

Maintain the confidentiality of information, data and records * Properly exercise tact, diplomacy ... Analysis of Physical Demands to Perform Essential Functions: Key (Based on typical week): N=Never R ...

Tamus

Assistant Men's Basketball Coach

Commerce, TX

Job Title Assistant Men's Basketball Coach Agency East Texas A&M University Department Athletics ... data entry related tasks, creates and maintains files and creates and provides statistical analysis.

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How much do basketball data analytics jobs pay per year?

As of Jun 25, 2026, the average yearly pay for basketball data analytics in the United States is $81,518.00, according to ZipRecruiter salary data. Most workers in this role earn between $59,500.00 and $96,500.00 per year, depending on experience, location, and employer.

How is data analytics used in basketball?

Basketball data analytics involves collecting and analyzing game data such as player performance, shot efficiency, and team strategies to inform decision-making. Data analysts in this field use statistical tools and software to identify patterns, improve team tactics, and enhance player development. Skills in data visualization and knowledge of basketball metrics are essential for this role.

What are the key skills and qualifications needed to thrive as a Basketball Data Analyst, and why are they important?

To thrive as a Basketball Data Analyst, you need strong statistical analysis, data interpretation, and basketball-specific knowledge, often supported by a degree in statistics, mathematics, or a related field. Proficiency with analytics software and programming languages such as Python, R, SQL, and visualization tools like Tableau is typically required. Attention to detail, critical thinking, and effective communication are vital soft skills for turning complex data into actionable insights for coaches and teams. These abilities are essential for informing strategic decisions, enhancing team performance, and providing a competitive edge in basketball operations.

What is basketball data analytics?

Basketball data analytics refers to the use of statistical and computational methods to collect, analyze, and interpret data related to basketball performance. Analysts use data from games, player tracking systems, and historical records to identify patterns, evaluate player performance, and inform coaching strategies. This field helps teams gain a competitive edge by making evidence-based decisions regarding player acquisitions, game tactics, and player development. It combines knowledge of basketball with expertise in statistics, programming, and data visualization.

How much do basketball data analysts make?

Basketball data analysts typically earn between $50,000 and $100,000 annually, depending on experience, education, and the level of the organization. Entry-level roles may start lower, while those with advanced skills in statistical software and sports analytics can earn higher salaries, especially in professional or major college programs.

What does a basketball data analyst do?

A basketball data analyst collects, analyzes, and interprets game and player data to identify patterns and improve team performance. They use statistical tools and software to create reports, track metrics, and support strategic decisions for teams or organizations.

What is the difference between Basketball Data Analytics vs Basketball Operations Analyst?

AspectBasketball Data AnalyticsBasketball Operations Analyst
Primary FocusAnalyzing data to inform team strategies and player performanceOverseeing day-to-day team operations and logistics
Required SkillsData analysis, statistics, programming, visualizationTeam management, communication, organizational skills
Work EnvironmentData centers, offices, sports analytics departmentsTeam facilities, arenas, administrative offices
Common EmployersNBA teams, sports analytics firms, consulting agenciesNBA teams, sports organizations, management firms

Basketball Data Analytics primarily focuses on analyzing data to improve team performance, while Basketball Operations Analysts handle the broader operational aspects of team management. Both roles often collaborate but differ in their core responsibilities and skill sets.

How to get a job in basketball analytics?

To get a job in basketball analytics, develop strong skills in data analysis, statistics, and programming languages like Python or R. Gain experience with sports data, learn to use visualization tools, and build a portfolio of projects or internships to demonstrate your expertise to potential employers.

How do professionals in Basketball Data Analytics typically collaborate with coaches and players to influence team strategies?

Professionals in Basketball Data Analytics work closely with coaches and, at times, directly with players to translate complex data into actionable insights. They often attend team meetings, present analytical findings in understandable formats, and provide real-time data during games or practices. Effective communication is key, as analysts must bridge the gap between statistical outputs and on-court tactics, helping coaches adjust strategies and optimize player performance based on data-driven recommendations. This collaboration fosters a culture of innovation and can directly impact game outcomes and player development.
More about Basketball Data Analytics jobs
What states have the most Basketball Data Analytics jobs? States with the most job openings for Basketball Data Analytics jobs include:
What job categories do people searching Basketball Data Analytics jobs look for? The top searched job categories for Basketball Data Analytics jobs are:
Basketball Data Analytics jobs near you
Infographic showing various Basketball Data Analytics job openings in the United States as of June 2026, with employment types broken down into 4% As Needed, 86% Full Time, 3% Part Time, 3% Temporary, 2% Contract, and 2% Nights. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $81,518 per year, or $39.2 per hour.
Sports Data Analyst

Sports Data Analyst

Swish Analytics

San Francisco, CA • On-site, Remote

Full-time

Posted 29 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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