Is there a correlation between Premier League wages and league position?
Let’s explore this by looking at the 2012-13 Premier League season data analysis – which shows exactly how much each club in the Premier League spent on wages last year (see the bar chart below).
This can be easily plotted on a scatter graph to test how strong the correlation is between spending and league position. (y axis is league position, x axis is wage bill in millions of pounds).
The mean spending on wages is 89 million pounds. Our regression line is y = -0.08x + 17.52. We can see some of the big outliers are QPR (with a big wage bill but low premier league position) and Everton (with a low wage bill relative to others who finished in a similar position).
The Pearson’s product moment correlation coefficient (r) is -0.73. This is negative because in our case league position is numerically lower the higher up the league you are. This shows a pretty strong correlation between league spending and league position. An r value of -1 would be a perfect correlation in our case, whereas 0 would be no correlation.
Is there a correlation between turnover and league position?
We can also see what the correlation is between league position and overall club turnover (see the bar chart above). Here we can see there is a huge gulf between the top few clubs and everyone else in the league. There’s only 40 million pounds difference between the bottom ranked club for revenue Wigan and Newcastle, with the 7th biggest revenue. But then a massive jump up to those with the top 6 revenues.
This time we have a mean turnover of 128 million pounds and a regression line of y = -0.05x + 16.89. The Pearson’s r value this time is r = -0.79, so there is a slightly stronger correlation than from wages – and this is a strong correlation overall. So, both wage bills and turnover provide a pretty good predictor of where a team will finish – and also a decent yardstick to measure how well a team has done relative to their resources.
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I think position is a fairly poor measure of performance. Perhaps points, goals scored etc. would be better.
The data look nonlinear to me. It would be better to fit a curve, or else to transform the financial data first. This would both improve the correlation and remove the tendency for clubs from 6th-15th to be below the line (better than expected) and 15th downwards to be above the line (worse than expected).
Are there any articles that back up the assertion that more wages lead to a higher league position?