{"id":19176563,"url":"https://github.com/jldbc/sports-econometrics","last_synced_at":"2026-02-20T22:39:55.849Z","repository":{"id":100931423,"uuid":"50885533","full_name":"jldbc/Sports-Econometrics","owner":"jldbc","description":"Analytics Projects from Sports Econometrics (EC3700) -- a course on advanced methods in cross-sectional econometrics with a focus on sports data","archived":false,"fork":false,"pushed_at":"2016-07-01T06:20:04.000Z","size":38240,"stargazers_count":5,"open_issues_count":0,"forks_count":1,"subscribers_count":2,"default_branch":"master","last_synced_at":"2025-10-24T11:47:22.970Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Stata","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/jldbc.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2016-02-02T01:40:48.000Z","updated_at":"2023-05-27T10:57:13.000Z","dependencies_parsed_at":"2023-06-10T22:15:20.202Z","dependency_job_id":null,"html_url":"https://github.com/jldbc/Sports-Econometrics","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/jldbc/Sports-Econometrics","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jldbc%2FSports-Econometrics","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jldbc%2FSports-Econometrics/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jldbc%2FSports-Econometrics/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jldbc%2FSports-Econometrics/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/jldbc","download_url":"https://codeload.github.com/jldbc/Sports-Econometrics/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jldbc%2FSports-Econometrics/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":29667093,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-02-20T19:49:36.704Z","status":"ssl_error","status_checked_at":"2026-02-20T19:44:05.372Z","response_time":59,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.6:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-11-09T10:29:01.885Z","updated_at":"2026-02-20T22:39:55.797Z","avatar_url":"https://github.com/jldbc.png","language":"Stata","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Sports-Econometrics\nAnalytics Projects from Sports Econometrics (EC3700) -- a course on advanced methods in cross-sectional econometrics with a focus on sports data\n\n## Projects\n\n* Jimmy Johnson Value Curve: estimating the weibuill-distribution value curve observed in the market for NFL draft picks  \n* OBP vs. SLG: comparing the predictive power of OBP, SLG, and OPS over MLB wins, and improving upon the established SLG metric \n* RPI: examining the extent to which RPI explains March Madness outcomes and revisiting the established ratios assigned to its components \n* Wednesday Topic Presentation: Do Defenses Win Championships? (hint: of course, but so do offenses)\n* Term Paper: Tennis Ratings Models. Examining ATP and WTA ratings' predictive powers in Grand Slam tennis matches, and comparing these to lesser-used Elo, RPI, and PageRank models\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjldbc%2Fsports-econometrics","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fjldbc%2Fsports-econometrics","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjldbc%2Fsports-econometrics/lists"}