Does Money Buy Success in the Premier League?

Introduction

The Research Question

The Premier League is the most watched football league in the world and one of the most commercially successful sports competitions on the planet. In the 2023/24 season, Premier League clubs generated a combined £6.3 billion in revenue — yet on-pitch results varied dramatically, from Manchester City's dominant title-winning campaign to Sheffield United's relegation with just 16 points.

This project asks a focused empirical question: to what extent does wage expenditure determine Premier League club performance? Using verified financial data from the Deloitte Annual Review of Football Finance 2025 and official Premier League standings, we run OLS regression models to quantify the relationship between club finances and on-pitch results.

The Data

Variables and Sources

Data was collected for all 20 Premier League clubs competing in the 2023/24 season. Financial figures are sourced from Deloitte's Annual Review of Football Finance 2025 (Table 1, p.44), which compiles data from company and group financial statements filed at Companies House. Performance data is sourced from the official Premier League website and verified against Wikipedia.

Findings

The Evidence

Figure 1 — Wage Costs vs Final Points

The relationship between wage expenditure and final points is strikingly strong. The Pearson correlation of r = 0.889 confirms that clubs with higher wage bills consistently finish higher in the table. Manchester City (£412.6m wages, 91 points) and Luton Town (£56.9m wages, 26 points) represent the extremes of this relationship.

Figure 1: Wage costs (£m) vs final points for all 20 Premier League clubs in 2023/24. Green = Big Six, Orange = other clubs. Dashed line = OLS regression fit.

Figure 2 — Revenue vs Final Points

Revenue is also strongly correlated with points (r = 0.859), though slightly weaker than wages. This makes intuitive sense — revenue funds wages, but clubs differ in how much of their revenue they allocate to the wage bill.

Figure 2: Total revenue (£m) vs final points. r = 0.859, M2 R² = 0.7383.

Figure 3 — Wage Efficiency vs Final Points

The wages-to-revenue ratio measures how much of a club's income goes on wages. Interestingly, this ratio does not predict performance as cleanly — some high-spending clubs (Aston Villa, Nottingham Forest) allocated over 90% of revenue to wages yet finished mid-table, while Tottenham allocated just 43% and finished 5th.

Figure 3: Wages/revenue ratio (%) vs final points. The dotted red line marks 100% — where wage costs equal revenue.

Figure 4 — Wage Bill by League Position

When clubs are ranked by their final league position and their wage bills displayed, the pattern is clear — with a few notable exceptions. Manchester United had the second-highest wage bill yet finished 8th. Luton Town spent the least and were relegated. The overall trend is unmistakable even if imperfect.

Figure 4: Club wage bills (£m) ranked from 1st to 20th place in the 2023/24 Premier League.

Figure 5 — Predicted vs Actual Points (M1)

M1 uses wage costs alone to predict final points. The predicted values track actual results closely for most clubs, though Manchester United is a clear outlier — their wage bill of £364m predicted around 77 points, but they finished with just 60. This highlights the limits of financial determinism in football.

Figure 5: M1 predicted points vs actual final points. Points on the dashed line = perfect prediction.

Figure 6 — Wage Costs vs Goals Scored

Higher wage expenditure is associated with scoring more goals — confirming that financial investment translates to attacking quality. The relationship is strong, though again Manchester United underperform relative to their wage bill on this measure too.

Figure 6: Wage costs (£m) vs goals scored in 2023/24.

Figure 7 — Wage Costs vs Goals Conceded

The relationship between wages and goals conceded is negative — clubs that spend more tend to concede fewer goals. Higher spending buys better defenders and goalkeepers. Sheffield United, the lowest points scorer, also conceded the most goals (104) despite a wage bill of £65m.

Figure 7: Wage costs (£m) vs goals conceded in 2023/24.

Regression Results

Three OLS models were estimated. All models use final points as the dependent variable.

*** p < 0.01   ** p < 0.05   * p < 0.10

Conclusion

What the Data Tells Us

The evidence is compelling: wage expenditure is the single strongest financial predictor of Premier League performance. M1 — using only wage costs — explains 79% of the variation in final points across all 20 clubs in 2023/24 (R² = 0.7907). The wage–points correlation of r = 0.889 is highly significant (p < 0.001), and every additional £1m in wages is associated with approximately 0.17 extra points.

Notably, when revenue is added to the model (M3), the improvement in R² is minimal — from 0.7907 to 0.7952 — and revenue becomes statistically insignificant (p = 0.55). This suggests wages, not revenue per se, are the direct mechanism through which financial resources translate to performance.

There are important caveats. Manchester United is a clear outlier — a wage bill of £365m predicted around 77 points, yet they finished with 60, reflecting managerial instability and poor squad cohesion. At n = 20, statistical power is limited and results should be treated as exploratory. The cross-sectional design cannot rule out reverse causality — successful clubs earn more broadcast revenue and can afford higher wages.

Limitations

This analysis is cross-sectional at a single point in time. Financial figures reflect year-end accounts and may not perfectly capture in-season spending decisions. Benchmark contamination is not an issue here, but transfer activity during the season is not captured by annual wage figures alone. Future work could extend to multiple seasons or incorporate player-level data.

Sources

Data Sources