DMP-FINAL: Predicting the Market Value of Football Players Using Various Factors

Final Data Management Plan (DMP) and machine-actionable DMP (maDMP) for the FAIR Data Science course experiment at TU Wien (2026). The project predicts the end-of-season transfer market value of football players in millions EUR using XGBoost regression trained on two openly licensed datasets from Mendeley Data. The DMP follows the FWF template 
and describes data sources, storage infrastructure (TU Wien DBRepo, GitHub, Zenodo, TU Wien Research Data Repository), FAIR metadata standards applied (RO-Crate, CodeMeta, FAIR4ML, Croissant, Model Card), 
licensing, and long-term preservation arrangements. The maDMP follows the RDA DMP Common Standard schema and covers five logical dataset groups: two input datasets, one trained model, generated output data, and source code. This deposit contains two files: the finalised DMP as PDF/A and the maDMP as JSON.