{"slug": "stats-perform", "name": "Stats Perform / Opta", "type": "b2b_feed", "description": "Enterprise sports data and AI company behind Opta, supplying stats, event data, predictions and betting content to media and operators through APIs and feeds.", "website": "https://statsperform.com", "country": null, "sports": ["multi", "soccer"], "data_types": ["historical", "odds", "player-stats", "predictions", "stats", "xg"], "protocols": [], "free_tier": null, "trial_days": null, "demo": null, "contact_sales_only": true, "min_price": null, "plans_count": 1, "commercial_use": null, "betting_use": null, "redistribution": null, "rights_basis": "contract", "customer_types": [], "live_in_play": null, "sentiment": "mixed", "discussions": 16, "github_repos": 22, "priority": 7.94, "logo": null, "logo_tone": null, "docs_url": "https://developers.statsperform.com/", "pricing_url": "https://www.statsperform.com/faqs/stats-perform-faqs-pricing-licensing/", "status_page_url": null, "founded_year": null, "product": {"name": "Opta APIs", "formats": [], "auth_methods": [], "sdk_languages": [], "openapi_url": null, "history_depth": null, "update_frequency": null, "claimed_latency_ms": null}, "plans": [{"name": "Enterprise", "price": null, "currency": null, "period": null, "request_limit": null, "request_period": null, "is_free": false, "is_enterprise": true, "summary": "Enterprise licensing, pricing tailored per deal", "source_url": "https://www.statsperform.com/faqs/stats-perform-faqs-pricing-licensing/", "verified_at": "2026-11-04"}], "access": {"restricted_countries": null, "available_only_in": null, "customer_types": null, "kyc_required": null, "odds_regions": null, "bookmakers_count": null, "notes": null, "source_url": null}, "usage_rights": {"commercial_use": null, "betting_use": null, "redistribution": null, "storage": null, "attribution_required": null, "media_included": null, "terms_url": null, "source_url": "https://www.statsperform.com/faqs/stats-perform-faqs-pricing-licensing/", "basis": "contract"}, "data_source": {"official_partners": [], "collection_methods": null, "source_url": null}, "support": {"sla_uptime": null, "channels": null, "sandbox": null, "changelog_url": null, "certifications": [], "payment_methods": null, "min_contract": null, "source_url": null}, "coverage": {"competitions_count": null, "key_leagues": [], "womens": null, "live_in_play": null, "markets": null, "languages": null, "id_mapping": null, "source_url": null}, "community": {"summary": "Opta data from Stats Perform is regarded as the gold standard for football event data and fast feeds, but discussions mostly describe it as enterprise-only: opaque pricing, out of reach for hobbyists and small startups, who turn to cheaper providers (API-Football, Sportmonks, StatsBomb open data). Little direct hands-on API feedback; few GitHub repos use it.", "sentiment": "mixed", "topics": ["data_quality", "pricing", "alternatives", "latency"], "pros": ["Seen as the professional gold standard for soccer data", "Fast, detailed event data"], "cons": ["Enterprise pricing not transparent", "Out of reach for indie developers", "Hard to get access or historical data"], "evidence": ["https://www.reddit.com/r/algobetting/comments/1jvw2tp/", "https://www.reddit.com/r/webdev/comments/1jp64vw/", "https://www.reddit.com/r/algobetting/comments/1h0tflj/", "https://www.reddit.com/r/sportsanalytics/comments/1sfns5l/", "https://www.reddit.com/r/algobetting/comments/1h7aj6k/"]}, "discussions_list": [{"platform": "reddit", "title": "Data Sourcing Tip for Algo Betting: Pay for Feeds When Free Data Takes Too Long", "url": "https://www.reddit.com/r/algobetting/comments/1jvw2tp/", "date": "2025-04-10", "score": 13.0, "where": "r/algobetting"}, {"platform": "reddit", "title": "Business of analytics", "url": "https://www.reddit.com/r/sportsanalytics/comments/1qs33xa/", "date": "2026-01-31", "score": 13.0, "where": "r/sportsanalytics"}, {"platform": "reddit", "title": "How do you actually enter football/basketball analytics as a beginner? (Data sources, projects, career steps?)", "url": "https://www.reddit.com/r/sportsanalytics/comments/1oznluo/", "date": "2025-11-17", "score": 10.0, "where": "r/sportsanalytics"}, {"platform": "reddit", "title": "Building an open-source, data-driven alternative to Transfermarkt (Algorithm-based player valuations) — Looking for Devs & Data Scientists!", "url": "https://www.reddit.com/r/sportsanalytics/comments/1w55fjs/", "date": "2026-09-02", "score": 7.0, "where": "r/sportsanalytics"}, {"platform": "reddit", "title": "Been tracking AI prediction accuracy across football/soccer platforms for 8 months — here's what i found", "url": "https://www.reddit.com/r/sportsanalytics/comments/1sfns5l/", "date": "2026-04-08", "score": 3.0, "where": "r/sportsanalytics"}, {"platform": "reddit", "title": "Which APIs offer paid/free in-match stats post match?", "url": "https://www.reddit.com/r/sportsanalytics/comments/1wy4k1i/", "date": "2026-10-05", "score": 2.0, "where": "r/sportsanalytics"}, {"platform": "reddit", "title": "Suggestions for the fastest and most accurate soccer APIs", "url": "https://www.reddit.com/r/algobetting/comments/1iav8wd/", "date": "2025-01-27", "score": 1.0, "where": "r/algobetting"}, {"platform": "reddit", "title": "Looking for partner with Betfair Api account", "url": "https://www.reddit.com/r/algobetting/comments/1te5fyu/", "date": "2026-05-15", "score": 1.0, "where": "r/algobetting"}, {"platform": "reddit", "title": "Looking for Opta historical data", "url": "https://www.reddit.com/r/algobetting/comments/1mt1ugy/", "date": "2025-08-17", "score": 1.0, "where": "r/algobetting"}, {"platform": "reddit", "title": "Granular football match event data", "url": "https://www.reddit.com/r/algobetting/comments/1h7aj6k/", "date": "2024-12-05", "score": 1.0, "where": "r/algobetting"}, {"platform": "reddit", "title": "Building and deploying as a full time employee and father of two - ScoreSageAI", "url": "https://www.reddit.com/r/SaaS/comments/1qyb1a3/", "date": "2026-02-07", "score": 1.0, "where": "r/SaaS"}, {"platform": "reddit", "title": "Extracting granular match stats (xG, lineups, player ratings) from FotMob into Pandas DataFrames [Python/Apify]", "url": "https://www.reddit.com/r/sportsanalytics/comments/1w9yavn/", "date": "2026-09-07", "score": 1.0, "where": "r/sportsanalytics"}], "repos": [{"platform": "github", "title": "albizup/Line-Breaking-Passes-Algorithm", "url": "https://github.com/albizup/Line-Breaking-Passes-Algorithm", "date": "2022-09-16", "score": 9.0, "where": null}, {"platform": "github", "title": "juanisil/Player2Vec", "url": "https://github.com/juanisil/Player2Vec", "date": "2025-03-13", "score": 4.0, "where": null}, {"platform": "github", "title": "AlpinAPI/sofascore-api", "url": "https://github.com/AlpinAPI/sofascore-api", "date": "2026-03-28", "score": 1.0, "where": null}, {"platform": "github", "title": "camkerk18/chicago-cubs-2023-offseason-analysis", "url": "https://github.com/camkerk18/chicago-cubs-2023-offseason-analysis", "date": "2024-09-15", "score": 1.0, "where": null}, {"platform": "github", "title": "tompysqlpbi/Data-sources", "url": "https://github.com/tompysqlpbi/Data-sources", "date": "2021-03-13", "score": 1.0, "where": null}, {"platform": "github", "title": "nimberledge/akm-xg", "url": "https://github.com/nimberledge/akm-xg", "date": "2023-02-20", "score": 1.0, "where": null}], "videos": [{"title": "Ken Pomeroy on College Basketball Data and Fan Engagement", "url": "https://www.youtube.com/watch?v=CBLlgTxplQ8", "channel": "Stats Perform", "date": "2021-10-13"}], "notes": "No pre-crawled pages; relied on web search snippets only. Pricing FAQ says enterprise-level, sales-led. Protocols and formats not confirmed.", "checked_at": "2026-11-04", "alternatives": ["sportmonks", "sportradar", "the-stats-api", "qiuxiaoce-football", "data-golf"], "fit": {"best_for": null, "not_for": null, "use_cases": ["Media statistics content", "Betting operator data supply"], "limitations": ["Quote-only pricing through sales, aimed at organisations", "Licence terms set per contract (competition, country, data level)"], "source_urls": ["https://www.statsperform.com/faqs/stats-perform-faqs-pricing-licensing/"]}, "score": {"overall": 44, "popularity": 55, "community": 54, "transparency": 35, "developer": 23, "confidence": "medium", "reliability_flags": [], "rank": 95}}