Sports Betting and Trading Strategies

In this section we provide you with a list of betting and trading strategies that are tested on historical data. We describe the idea behind the betting strategy and use data from a bookmaker or betting exchange to back test the strategy. We hope that with this approach we can help you to increase profits with your betting and trading activities.

Football

Predicting Football Using FIFA Rankings

In this article we describe how FIFA rankings can be used to predict football matches. FIFA rankings are publicly available and can be used to train a Neural Network. This type of machine learning model is used to predict odds of football matches and derive a sports betting strategy.

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Use a Rating Model to Predict Tennis Matches

Rating systems are very popular to rank players and teams especially in sports such as tennis, chess or go. In this article Python is used to build a rating system for tennis betting which is evaluated on historical data.

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Lay The Field At BSP Limit

With this betting strategy lay bets are placed on selections using the Betfair Starting Price (BSP) with an odds limit. As a result only horses and greyhounds with very low BSP are laid (lower than a threshold of X) and profitability is evaluated on historical exchange data.

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Horse Racing

Genetic Programming to Create a Betting Strategy

Genetic Programming belongs to the field of artificial intelligence and can be used in sports betting to automatically develop a betting strategy: You start with a set of random betting rules and evolve them through selection, mutation and cross-over to find a strategy that you can use to make some profit.

Backtest Results:
Backtest Period: 01 Jan 2019 to 19 Jan 2021
Total Profit: +1,005.06 Points
Average Profit: +40.26 Points per Month
Number of bets: 137,826
Max. Drawdown of 890.26 Points during 145 Days

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Horse Racing

Back the Newcomer in Horse Racing

I came across this strategy when reverse engineering Betfair starting price bets. It came to my attention that certain horses had very similar patterns in terms of starting price bets. After further investigation I discovered that these were horses that have not participated in any race previously. With this I defined a very simple betting strategy for a backtest: Back bet on horses making their debut using the Betfair Starting Price (BSP).

Backtest Results:
Backtest Period: 01 Jan 2014 to 08 Oct 2020
Total Profit: +2,987.38 Points
Average Profit: +36.25 Points per Month
Number of bets: 47,129
Max. Drawdown of 905.74 Points during 573 Days

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Football

Lay the Draw in Football

Lay the draw is probably the most popular trading strategy for inplay football betting markets. Some readers reported having some success when applying this strategy in the past. Based on this, we conducted a more systematic backtest to see if this popular approach is still profitable.

Backtest Results:
Backtest Period: 18 Jan 2020 to 01 Feb 2020
Total Profit: +5.31 Points
Average Profit: +12.24 Points per Month
Number of bets: 1,909
Max. Drawdown of 8.95 Points during 6 Days

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Horse Racing

Lay Bets in the Range of 1.01 - 1.07 in Horse Racing Markets

After observing a couple of UK / IRE horse racing markets on Betfair, we noticed that shortly after the creation of the market lay bets were placed in the range between 1.01 and 1.07.

Backtest Results:
Backtest Period: 01 Jan 2014 to 10 Jan 2020
Total Profit: +238.50 Points
Average Profit: +3.25 Points per Month
Number of bets: 74,726
Max. Drawdown of 8.05 Points during 41 Days

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Football

Back Premier League Draws in Games without clear Favourite

This betting system involves backing the draw in football matches for games without a clear favourite, i.e. both teams have similar odds. We would like to share the Python code that we used to test the strategy as well as the backtesting result.

Backtest Results:
Backtest Period: 18 Aug 2012 to 12 May 2019
Total Profit: +51.31 Points
Average Profit: +0.63 Points per Month
Number of bets: 436
Max. Drawdown of 24.01 Points during 453 Days

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Football

Betting on Home Underdogs in Football

This is a very simple strategy where a back bet is placed on underdogs who are playing at home. A team qualifies as underdog when the odds for a win are higher compared to the opponent. Backtest is done for major football leagues in Europe but the strategy could also be applied to other sports.

Backtest Results:
Backtest Period: 17 Aug 2013 to 12 May 2019
Total Profit: +37.63 Points
Average Profit: +0.54 Points per Month
Number of bets: 2,280
Max. Drawdown of 38.74 Points during 441 Days

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Football

Laying Home Favourites in the Bundesliga

This betting system focuses on the German football league, Bundesliga, and involves betting against the favourite. There are various sets of rules that can be applied in order to increase profitability. Some of them are selecting home favourites only or excluding certain odds ranges.

Backtest Results:
Backtest Period: 03 Aug 2012 to 19 May 2019
Total Profit: +17.79 Points
Average Profit: +0.22 Points per Month
Number of bets: 2,332
Max. Drawdown of 60.14 Points during 511 Days

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Propose a Strategy

Do you know a quantitative betting or trading strategy that we should cover here? Please do not hesitate to contact us - we are always looking forward to receive input on strategies with the goal to become the largest database of betting and trading strategies.

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