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Freelance Sports Data Collection Jobs (NOW HIRING)

Swish Analytics

Data Engineer

San Francisco, CA · On-site +1

$145K/yr

Architect low-latency, real-time analytics systems including raw data collection, feature development and endpoint production * Build new sports betting data products and predictions offerings

Swish Analytics

Data Engineer

San Francisco, CA · On-site +1

$160K/yr

Architect low-latency, real-time analytics systems including raw data collection, feature development and endpoint production * Build new sports betting data products and predictions offerings

Swish Analytics

Data Engineer

San Francisco, CA · Remote

$160K/yr

Architect low-latency, real-time analytics systems including raw data collection, feature development and endpoint production * Build new sports betting data products and predictions offerings

Swish Analytics

Data Engineer

San Francisco, CA · Remote

$145K/yr

Architect low-latency, real-time analytics systems including raw data collection, feature development and endpoint production * Build new sports betting data products and predictions offerings

Maxinsights

Data Partnership Manager

Santa Clara, CA · On-site

Participate in building and operating the data collection "crowdsourcing model," assisting in the management of a diverse supply chain of data collectors (e.g., community residents, freelancers ...

Doist

AI Engineer

Manhattan, NY · On-site

$170 - $200/hr

... collection * Work with messy, multimodal sports data from tracking systems, video and computer vision outputs, audio, commentary, text, and structured feeds, including imperfect labels and ambiguous ...

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Freelance Sports Data Collection information

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$14

$47

$132

How much do freelance sports data collection jobs pay per hour?

As of Aug 23, 2026, the average hourly pay for freelance sports data collection in the United States is $47.71, according to ZipRecruiter salary data. Most workers in this role earn between $24.28 and $61.78 per hour, depending on experience, location, and employer.

What is freelance sports data collection?

Freelance sports data collection involves gathering and recording statistics and information about sports events on a contract or per-project basis. Freelancers may attend games in person or collect data remotely, depending on the assignment. The data can include scores, player statistics, play-by-play actions, and other relevant metrics that are valuable to sports organizations, media outlets, and analytics companies. This work requires attention to detail, a strong understanding of the sport, and the ability to work independently. Freelance sports data collectors often use specialized software or platforms to submit their data in real time.

What are the key skills and qualifications needed to thrive as a freelance sports data collector?

To thrive as a Freelance Sports Data Collector, you need strong attention to detail, knowledge of sports rules and statistics, and often a background in data entry or sports analytics. Familiarity with mobile data collection apps, statistical software, and sometimes official accreditation from sports organizations is typically required. Excellent observational skills, reliability, and the ability to work independently under tight deadlines help individuals stand out in this role. These skills ensure accurate, timely data collection, which is critical for sports analytics, reporting, and betting industries.

What are some common challenges faced by freelance sports data collectors, and how can they be addressed?

Freelance sports data collectors often face challenges such as working irregular hours, dealing with fast-paced environments during live events, and ensuring data accuracy under pressure. To address these challenges, it's important to develop strong time-management skills, familiarize yourself with the sport’s rules, and practice using data entry tools before events. Building a network with other data collectors can also provide support and tips for handling tricky situations. Being adaptable and proactive in communicating with event coordinators can further help ensure smooth data collection.

What is the difference between Freelance Sports Data Collection vs Freelance Sports Writer?

AspectFreelance Sports Data CollectionFreelance Sports Writer
CredentialsBasic knowledge of sports statistics, data entry skillsWriting skills, sports knowledge, possibly journalism background
Work EnvironmentRemote, data-focused tasks, often using specialized softwareRemote or on-site, writing articles, blogs, or reports
Employer & Industry UsageSports analytics companies, media outlets, betting firmsMedia outlets, sports websites, magazines

Freelance Sports Data Collection involves gathering and inputting sports statistics, focusing on accuracy and data management. Freelance Sports Writers create content, articles, and reports about sports events. While both roles require sports knowledge, data collection emphasizes technical skills, whereas writing emphasizes communication and storytelling.

More about Freelance Sports Data Collection jobs

What cities are hiring for Freelance Sports Data Collection jobs?

Cities with the most Freelance Sports Data Collection job openings:

What are the most commonly searched types of Sports Data Collection jobs?

The most popular types of Sports Data Collection jobs are:

What states have the most Freelance Sports Data Collection jobs?

States with the most job openings for Freelance Sports Data Collection jobs include:

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The top searched job categories for Freelance Sports Data Collection jobs are:

Freelance Sports Data Collection jobs near you
Infographic showing various Freelance Sports Data Collection job openings in the United States as of August 2026, with employment types broken down into 50% Full Time, and 50% Part Time. Highlights an 100% In-person job distribution, with an average salary of $99,230 per year, or $47.7 per hour.

Data Engineer

Swish Analytics

San Francisco, CA • On-site, Remote

$145K/yr

Full-time

Re-posted 2 days ago

Job description

Company Overview
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.
Job Description
The Swish Analytics team is seeking Data Engineers based in Europe to have a direct impact on the infrastructure and delivery of our core consumer and enterprise data offerings as well as helping support our coverage of non-US sports. We're a team passionate about accurate predictions and real-time data, and hope you find satisfaction in building new products with the latest and greatest technologies. This is a remote position.
Duties
  • Support production systems and help triage issues during live sporting events
  • Architect low-latency, real-time analytics systems including raw data collection, feature development and endpoint production
  • Build new sports betting data products and predictions offerings
  • Integrate large and complex real-time datasets into new consumer and enterprise products
  • Develop production-level predictive analytics into enterprise-grade APIs
  • Contribute to the design and implementation of new, fully-automated sports data delivery frameworks

Requirements
  • BS/BA degree in Mathematics, Computer Science, or related STEM field
  • Minimum of 4+ years of demonstrated experience writing production level code (Python)
  • Proficiency in Python and SQL (preferably MySQL) Demonstrated experience with Airflow
  • Demonstrated experience with Kubernetes
  • Experience building end-to-end ETL pipelines
  • Experience utilizing REST APIs
  • Experience with version control (git), continuous integration and deployment, shell scripting, and cloud-computing infrastructures (AWS)
  • Experience with web scraping and cleaning unstructured data
  • Knowledge of data science and machine learning concepts
  • Professional working experience with MLB or NBA data

Salary: Starting at $145,000 - DOE
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 Engineering Locations San Francisco, CA - Remote Remote status Fully Remote

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