{"id":14958256,"url":"https://github.com/tmalik1116/f1_qualifying_predictor_ml","last_synced_at":"2025-10-24T14:31:31.806Z","repository":{"id":252848157,"uuid":"841569710","full_name":"tmalik1116/F1_Qualifying_Predictor_ML","owner":"tmalik1116","description":"Estimate Formula 1 qualifying results using ML","archived":false,"fork":false,"pushed_at":"2025-02-05T21:45:36.000Z","size":170272,"stargazers_count":4,"open_issues_count":2,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-02-05T22:29:50.706Z","etag":null,"topics":["ai","ergast-api","f1","fastf1","formula1","machine-learning","machine-learning-algorithms","ml","motorsport","pandas","python","racing","react","reactjs","sports","xgboost","xgboost-regression"],"latest_commit_sha":null,"homepage":"https://f1-qualifying-predictor-ml.vercel.app","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/tmalik1116.png","metadata":{"files":{"readme":"docs/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":"2024-08-12T17:05:07.000Z","updated_at":"2025-02-05T21:45:39.000Z","dependencies_parsed_at":"2024-08-26T16:42:21.426Z","dependency_job_id":"db226e03-b145-42e6-99ff-31ea22baf934","html_url":"https://github.com/tmalik1116/F1_Qualifying_Predictor_ML","commit_stats":{"total_commits":73,"total_committers":2,"mean_commits":36.5,"dds":"0.36986301369863017","last_synced_commit":"823e6563fa3e587fdfdc51efaca7101ac7514196"},"previous_names":["tmalik1116/f1_quali_predictor","tmalik1116/f1_qualifying_predictor_ml"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tmalik1116%2FF1_Qualifying_Predictor_ML","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tmalik1116%2FF1_Qualifying_Predictor_ML/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tmalik1116%2FF1_Qualifying_Predictor_ML/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tmalik1116%2FF1_Qualifying_Predictor_ML/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/tmalik1116","download_url":"https://codeload.github.com/tmalik1116/F1_Qualifying_Predictor_ML/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":237982408,"owners_count":19397254,"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":["ai","ergast-api","f1","fastf1","formula1","machine-learning","machine-learning-algorithms","ml","motorsport","pandas","python","racing","react","reactjs","sports","xgboost","xgboost-regression"],"created_at":"2024-09-24T13:16:37.432Z","updated_at":"2025-10-24T14:31:31.801Z","avatar_url":"https://github.com/tmalik1116.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Formula 1 Qualif-AI\n#### V1.0\n\n## Estimate future Formula 1 qualifying results using ML (XGBoost Regression)\n![F1_UI](https://github.com/user-attachments/assets/fb577ccd-3e13-45aa-bdf7-cf0aa4185ab6)\n\n\n## Usage\n\nhttps://www.f1quali.online/\n\nThe user is given a choice between predicting results for a single driver or for all participants in a session. Shown below are the menus for both and example inputs. \n\n### Driver Prediction\nhttps://github.com/user-attachments/assets/10a2d042-d3bd-470a-aa2a-3d0270f36414\n\n\n\n### Session Prediction\nhttps://github.com/user-attachments/assets/84aaae1c-0758-46e2-9646-06f82d8068d2\n\n\n\n## Deep-Dive\nThe entire frontend UI is built using React. GET and POST requests are made to the backend server which runs a custom Python API using the trained model. The model used was an XGBoost Regressor from the open-source xgboost library in Python. I trained an instance of this model on a custom dataset which includes data from the past decade of the sport. \nThe relevant data was obtained programatically from theOehrly's fastf1 Python library (https://github.com/theOehrly/Fast-F1). \n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftmalik1116%2Ff1_qualifying_predictor_ml","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ftmalik1116%2Ff1_qualifying_predictor_ml","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftmalik1116%2Ff1_qualifying_predictor_ml/lists"}