Do bookmaker markets systematically overrate the Big 6 Teams?

In this thread I look at the data from 10/11 to 18/19 using implied Team Goals for/against built from bookmaker odds and contrast to actual goals for/against to analyse this common perception

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Looking first at the data for the Big 6 teams

GOALS FOR
Actual: 3879
Market Expectation: 3871.4

GOALS AGAINST
Actual: 2118
Market Expectation: 2080.7

It appears the bookmakers model is close to spot on- with a minor under estimation of goals against
Looking first at the data for the Big 6 teamsGOALS FORActual: 3879Market Expectation: 3871.4GOALS AGAINSTActual: 2118Market Expectation: 2080.7It appears the bookmakers model is close to spot on- with a minor under estimation of goals against
Looking first at the data for the Big 6 teamsGOALS FORActual: 3879Market Expectation: 3871.4GOALS AGAINSTActual: 2118Market Expectation: 2080.7It appears the bookmakers model is close to spot on- with a minor under estimation of goals against
Looking first at the data for the Big 6 teamsGOALS FORActual: 3879Market Expectation: 3871.4GOALS AGAINSTActual: 2118Market Expectation: 2080.7It appears the bookmakers model is close to spot on- with a minor under estimation of goals against
Looking first at the data for the Big 6 teamsGOALS FORActual: 3879Market Expectation: 3871.4GOALS AGAINSTActual: 2118Market Expectation: 2080.7It appears the bookmakers model is close to spot on- with a minor under estimation of goals against
Repeating the same data for every non Big 6 team over the same period

GOALS FOR
Actual: 5520
Market Expectation: 5496.0

GOALS AGAINST
Actual: 7281
Market Expectation: 7286.7

The precision in both metrics here is incredibly high- note that the sample size is higher which helps
Repeating the same data for every non Big 6 team over the same periodGOALS FORActual: 5520Market Expectation: 5496.0GOALS AGAINSTActual: 7281Market Expectation: 7286.7The precision in both metrics here is incredibly high- note that the sample size is higher which helps
Repeating the same data for every non Big 6 team over the same periodGOALS FORActual: 5520Market Expectation: 5496.0GOALS AGAINSTActual: 7281Market Expectation: 7286.7The precision in both metrics here is incredibly high- note that the sample size is higher which helps
Repeating the same data for every non Big 6 team over the same periodGOALS FORActual: 5520Market Expectation: 5496.0GOALS AGAINSTActual: 7281Market Expectation: 7286.7The precision in both metrics here is incredibly high- note that the sample size is higher which helps
Repeating the same data for every non Big 6 team over the same periodGOALS FORActual: 5520Market Expectation: 5496.0GOALS AGAINSTActual: 7281Market Expectation: 7286.7The precision in both metrics here is incredibly high- note that the sample size is higher which helps
It seems as though the market bias towards big teams may not be quite the issue that many suspect and overall they are quite balanced towards big/small teams (when handling correctly for margins)

At specific team level less can be read into as less samples equals less confidence
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