Evaluating the Impact of the FIA Budget Cap on Competitive Balance in Formula 1 : A Machine Learning Approach to Forecasting 2026 Constructor Points

Sammanfattning

During the 'Hybrid Era' (2014–2021), Formula 1 was constrained by a severe financial oligopoly, and the unrestricted spending of top teams effectively undermined the uncertainty of competition. To break these technical barriers, the FIA introduced a strict budget cap in 2021. However, evaluating the long-term effectiveness of this intervention—and predicting its impact on the comprehensive technical regulations of 2026—requires going beyond a descriptive review of the seasons. To empirically quantify this structural change, this study adopts a longitudinal interrupted time series framework from 2012 to 2025. Macroeconomic dispersion metrics reveal a tangible fracturing of the monopoly: By employing a longitudinal interrupted time-series framework to compare the pre- and post-budget cap eras, the analysis reveals that the Herfindahl-Hirschman Index (HHI) dropped by 10.3%, while the Gini Coefficient recorded a 10.0% improvement in global resource distribution, signaling the emergence of a resilient midfield..To address the volatility of the impending 2026 regulations, the research further engineers a dynamic Decision Support System (DSS). By utilizing an eXtreme Gradient Boosting (XGBoost) algorithm combined with a targeted counterfactual data sanitization protocol—specifically recalibrating early-season mechanical anomalies like Red Bull Racing's 2022 retirements to reflect true aerodynamic pace—the model successfully neutralizes stochastic noise. This hybrid forecasting framework, which optimizes a 60/40 weighted split between real-time pace extrapolation and historical algorithmic potential, achieved a highly robust CV-RMSE of 17.20% during backtesting. Crucially, the model's feature importance analysis dictates a competitive paradigm shift: under financial constraints, Aerodynamic Testing Restrictions (ATR) and human Driver Rating have decisively eclipsed traditional "Works Team" prestige as the primary determinants of championship success. This thesis studies whether the FIA budget cap is associated with improved competitive balance in Formula 1, and whether a machine-learning-based model can be used to forecast the 2026 constructor standings.