We extract live scores, team news, betting odds, injury reports, and fantasy projections from Bleacher Report. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for News Articles objects from bleacherreport.com. All fields typed and schema-versioned.
"url": "https://bleacherreport.com/articles/1234567-nba-trade-rumours", "headline": "Lakers Exploring Trade Options for Veteran Guard", "author": "Chris Haynes", "publish_date": "2026-02-14T18:30:00Z", "sport_category": "NBA", "team_tags": "['Los Angeles Lakers', 'NBA']", "comment_count": 412, "share_count": 1205
| # | url | headline | author | publish_date | team_tags | sport_category |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Live Scores objects from bleacherreport.com. All fields typed and schema-versioned.
"match_id": "nba_20260214_LAL_BOS", "home_team": "Boston Celtics", "away_team": "Los Angeles Lakers", "status": "IN_PROGRESS", "home_score": 88, "away_score": 82, "period": "Q3", "clock": "04:12", "sport": "NBA"
| # | match_id | home_team | away_team | status | home_score | away_score |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Betting Odds objects from bleacherreport.com. All fields typed and schema-versioned.
"match_id": "nfl_20260910_KC_BAL", "sportsbook": "DraftKings", "home_spread": -3.5, "away_spread": 3.5, "home_moneyline": -175, "away_moneyline": 150, "over_under": 48.5, "timestamp": "2026-09-08T12:00:00Z"
| # | match_id | sportsbook | home_spread | away_spread | home_moneyline | away_moneyline |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Injury Reports objects from bleacherreport.com. All fields typed and schema-versioned.
"player_name": "Joe Burrow", "team": "Cincinnati Bengals", "position": "QB", "injury_type": "Calf", "status": "Questionable", "expected_return": "2026-09-17", "updated_at": "2026-09-15T09:45:00Z"
| # | player_name | team | position | injury_type | status | expected_return |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Fantasy Projections objects from bleacherreport.com. All fields typed and schema-versioned.
"player_name": "Christian McCaffrey", "team": "San Francisco 49ers", "sport": "NFL", "position": "RB", "projected_points": 22.4, "ownership_pct": 34.2, "salary": 9200, "matchup": "vs LAR", "updated_at": "2026-10-02T14:10:00Z"
| # | player_name | team | sport | position | projected_points | ownership_pct |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our pipeline handles the complexities of modern sports media platforms: heavy JavaScript hydration, live polling limits, embedded odds widgets, and rapidly changing state during live matches.
Poll match endpoints for real-time score updates, clock changes, and period transitions across all major leagues.
Parse full article bodies, author metadata, publish timestamps, and team-specific tags for media monitoring.
Track moneyline, spread, and totals across supported sportsbooks embedded within match previews and articles.
Monitor player status changes, expected return dates, and practice participation metrics.
Extract player projections, DFS salaries, and matchup difficulty metrics for fantasy sports applications.
Filter extraction pipelines by specific NFL, NBA, MLB, or Premier League franchises to isolate relevant updates.
Scrape mock drafts, prospect rankings, combine metrics, and scouting reports during the offseason.
Track publication frequency, engagement metrics, and sentiment per journalist or content creator.
Push critical updates like final scores, lead changes, or breaking injury news instantly to your endpoints.
Brief in. Clean data out.
Provide target leagues, team tags, or data types. We design the extraction schema together.
We configure Scrapy and Playwright crawlers, manage polling rates, and handle dynamic widget hydration.
Schema validation, null-rate checks, and latency testing during live matches before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Bleacher Report relies on dynamic content delivery and third-party integrations. Here is how we maintain reliable data flow during peak traffic events.
Bleacher Report scoreboards and odds widgets are heavily JavaScript-rendered. We run full Playwright browser sessions to trigger lazy-loading and hydrate dynamic data that headless HTTP clients miss entirely.
Live sports require sub-minute polling. We distribute requests across vast residential proxy pools to prevent rate-limiting while capturing rapid state changes like clock updates and lead changes.
Betting odds are often embedded via third-party iframes or API calls. Our network interception layer captures the raw JSON payloads powering these widgets before they hit the DOM.
Layouts shift drastically during the Super Bowl or NBA Draft. Our selector strategy uses multiple fallback chains so custom event templates do not break your data pipeline.
For live score feeds, we maintain a state cache. Subsequent runs only emit payloads when the score, clock, or period changes, reducing downstream processing load.
Quantitative analysts feed proprietary models with real-time spreads, injury reports, and weather updates.
DFS tools and season-long platforms populate their interfaces with aggregated projections and breaking news.
Agencies track narrative shifts, team coverage volume, and sentiment across major sports publishers.
Machine learning teams train outcome prediction models on historical play-by-play data and score progressions.
Rival sports publishers track Bleacher Report content velocity, author output, and trending topics.
Secondary sports applications populate their interfaces with team-specific news feeds and live score widgets.
"Bleacher Report aggregates the most critical real-time signals in sports. Extracting those signals during live games requires sub-second pipeline execution."
Most teams fail at live sports scraping because they rely on static HTML parsers. Bleacher Report relies heavily on JavaScript hydration, third-party odds integrations, and rapid state changes. DataFlirt manages the residential proxies, browser sessions, and polling logic so you receive structured JSON without the infrastructure overhead.
Everything supported by our bleacherreport.com scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy handles crawl orchestration and deduplication. Playwright handles JavaScript rendering and dynamic widget hydration. Combined via middleware for optimal performance.
Redis-backed state management allows sub-minute polling of live endpoints. We detect changes in score or clock state and trigger immediate downstream Webhooks.
Pipelines run on AWS Lambda for burst scaling during major events. Airflow handles scheduling, dependency management, and SLA alerting.
Data delivered to where your team already works — no new tooling required.
About bleacherreport.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available factual data like sports scores, injury reports, and published news headlines is generally permissible under fair use and public data doctrines. We do not extract authenticated user data or bypass DRM protections. Clients must ensure their downstream use complies with copyright law.
Our live polling engine can achieve sub-minute latency. Changes to the score, clock, or period are pushed immediately via Webhook to your endpoints.
Yes. We extract spreads, moneylines, and totals from the odds widgets embedded within Bleacher Report articles and match previews.
Yes. Pipelines can be configured to target specific team tags, leagues, or sports categories to minimise irrelevant data delivery.
We deploy multi-layer fallback selectors. If a custom Super Bowl layout breaks the primary CSS selector, the pipeline falls back to XPath or embedded JSON-LD extraction.
No. Our extraction targets the web application. Content or community features exclusive to the mobile application are not supported.
Our minimum engagement covers daily historical news extraction or weekend live-score polling for a single major league. Contact us for a scoped quote.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need historical article archives or sub-minute live score feeds, we scope, build, and operate the infrastructure. Tell us your requirements.
