{"id":17259374,"url":"https://github.com/sshleifer/nbadraft","last_synced_at":"2025-04-14T06:13:09.957Z","repository":{"id":74359363,"uuid":"21313108","full_name":"sshleifer/nbaDraft","owner":"sshleifer","description":"Predicting NBA performance using college box-score stats and combine measurements.","archived":false,"fork":false,"pushed_at":"2014-08-06T04:00:32.000Z","size":4212,"stargazers_count":7,"open_issues_count":1,"forks_count":6,"subscribers_count":2,"default_branch":"master","last_synced_at":"2025-04-14T06:13:04.586Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Python","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/sshleifer.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}},"created_at":"2014-06-28T23:43:08.000Z","updated_at":"2025-03-26T13:19:23.000Z","dependencies_parsed_at":"2023-02-25T23:00:28.955Z","dependency_job_id":null,"html_url":"https://github.com/sshleifer/nbaDraft","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sshleifer%2FnbaDraft","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sshleifer%2FnbaDraft/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sshleifer%2FnbaDraft/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sshleifer%2FnbaDraft/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/sshleifer","download_url":"https://codeload.github.com/sshleifer/nbaDraft/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248830399,"owners_count":21168272,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","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":"2024-10-15T07:25:41.175Z","updated_at":"2025-04-14T06:13:09.934Z","avatar_url":"https://github.com/sshleifer.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"##nbaDraft\nPredicting NBA performance with college box-score stats, combine measurements and python.\n###datasets\nThe data used to make predictions is in colPro.csv, comprised from draft_mix.csv, colData.csv, bestRapm.csv and measurements.\n###scrapers\nA handful of web requests that make the datasets you see in the datasets folder.\nThey take ~1hr to run, so I'll update them when they need to be updated.\n###assemble_dataset.py\n  Merges many of the datasets into colPro.csv, and then splits that into train.csv and test.csv.\n###model.py\n  My attempts at using NCAA boxscore stats and measurements to predict Regularized Adjusted Plus Minus for former US college players. I try different techniques for feature engineering, missing data, and ensemble modeling.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsshleifer%2Fnbadraft","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsshleifer%2Fnbadraft","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsshleifer%2Fnbadraft/lists"}