Additional Soccer Betting Statistics

Since my previous post, Betting on Soccer Draws Provides the Best Value, I have completed additional analysis using the soccer results data. The results in this post are based on a larger data set, consisting of 1,540 football matches. Since my last post my initial results still hold true but the differences between systematic betting on wins, draws, and losses has tightened up.

For those who haven’t read my first post, since the end of January I have been tracking virtually every football match offered by a particular bookmaker. For each match, I have logged the available odds at a random snapshot in time, along with the eventual outcome.

In this post I compare the relative value of betting on home wins, draws, and home losses for three scenarios:

1. When the odds for a home win are less than 1.5 (home odds < 1.5) 2. When the odds for a home win are between 1.5 and 2.00 (1.5 <= home odds < 2.00) 3. When the odds for a home win and a home loss are both greater than 2.00 (home odds >= 2.00 and away odds >= 2.00)

I have excluded results where the odds for a home loss are less than 1.5 because I don’t have enough data to reach any meaningful insights.

1. When the odds for a home win are less than 1.5

Statistic
 
  |  
  |  
Home Team Win
 
  |  
  |  
Draw
 
  |  
  |  
Home Team Loss
 
Occurances   |   102   |   24   |   11
Frequency   |   74.45%   |   17.52%   |   8.03%
Average Odds   |   1.34   |   4.54   |   9.57
Average Payout   |   $0.99   |   $0.74   |   $0.73

 

If you had bet on every home team that had odds of 1.50 or less, you would have returned $0.99 for every dollar invested. In this scenario betting on the home team provided the best value with home loss betting providing the worst value.

2. When the odds for a home win are between 1.5 and 2.00

Statistic
 
  |  
  |  
Home Team Win
 
  |  
  |  
Draw
 
  |  
  |  
Home Team Loss
 
Occurances   |   264   |   148   |   94
Frequency   |   52.17%   |   29.25%   |   18.58%
Average Odds   |   1.75   |   3.35   |   4.82
Average Payout   |   $0.91   |   $0.98   |   $0.87

 

Now the results are closer to the total sample data results in my previous post. Here, betting on draws provided the best value, with home loss betting providing the worst value.

3. When the odds for a home win and a home loss are both greater than 2.00

Statistic
 
  |  
  |  
Home Team Win
 
  |  
  |  
Draw
 
  |  
  |  
Home Team Loss
 
Occurances   |   294   |   252   |   267
Frequency   |   36.16%   |   31.00%   |   32.84%
Average Odds   |   2.49   |   3.14   |   2.89
Average Payout   |   $0.88   |   $0.98   |   $0.92

 

Now the results are the same as total sample data results in my previous post. Here, betting on draws provided the best value, with home win betting providing the worst value.

Summary

If the odds for a home win were less than 1.5, betting on the home team in my sample data provided the best value. If the odds for a home team were between 1.5 and 2.00, then draws provided the best value, with away team betting providing the worst value. If the odds for both a home win an a home loss were greater than 2.00 (indicating an anticipated tight encounter), draws provided the best value, with home team betting providing the worst value.

The higher the odds for a home team win, the worse the value of home team betting. For tight encounters, i.e. where win and loss bets both have odds of 2.00 or more, punters systematically under bet on the ‘boring’ draw result, hence making it the best value. When the odds for a home team win are low, i.e. less than 1.50, punters under bet on the home team. This maybe because they believe the odds don’t provide good enough value. Also, the favourite-longshot bias may come into effect, where punters get wooed by the 10.00+ odds available for the underdog.

Please note that because I have split the data up into specific categories, my sample sizes for each set are much smaller, making the results less reliable.

Disclaimer

None of my data has been double checked, nor have the summary statistics. Please don’t rely upon any of these results. This post is designed for your casual enjoyment only.

Suggestions?

If you have any requests or ideas for other analysis to run with the data feel free to let me know.

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