Portfolio Risk Management in Elite Football Clubs: A Statistical and Managerial Accounting Analysis of Real Madrid Before 2022

Abstract

This study examines risk management at Real Madrid Club from a combined statistical and managerial accounting perspective prior to 2022. The paper treats the club as a high-value sport organization whose risk exposure is created not only by match outcomes, but also by transfer investment, player asset valuation, market-value concentration, and operational pressure. A season-level dataset covering 16 Real Madrid seasons from 2005/06 to 2020/21 is used to construct sporting-risk indicators, including win rate, loss rate, points per match, average match gap, and short-rest rate. These indicators are merged with managerial accounting measures, including net transfer spending, transfer-fee exposure, transfer turnover, player valuation dispersion, and club market-value concentration. The empirical strategy applies descriptive statistics, correlation analysis, visual diagnostics, and ordinary least squares regression using Python, with SPSS, Stata 17, or EViews suggested for verification. The results show that Real Madrid's average win rate was 0.660, average loss rate was 0.178, and average points per match was 2.143. The correlation results also indicate that transfer-fee exposure is positively associated with the composite risk index (r = 0.675), while net transfer spending is positively associated with win rate (r = 0.446). These findings suggest that elite-club risk should be understood as a portfolio of operational, investment, and asset-value risks rather than as a simple sporting outcome. The study contributes a practical framework for the use of football data in management accounting and risk-control decisions.