Free List of Betting Strategies

We are happy to provide you with a free list of betting strategies tested on historical data.

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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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 (same odds limit, always the same time SP bets are placed etc). After further investigation I then 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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Football

Using Machine Learning to Predict Football Matches

Machine Learning and Artificial Intelligence are powerful tools to learn from large amounts of data and help to make better decisions. In this article I would like to train a machine learning model that is capable of predicting the outcome of football matches.

Backtest Results:
Backtest Period: 08 Apr 2019 to 12 May 2019
Total Profit: +5.37 Points
Average Profit: +4.74 Points per Month
Number of bets: 56
Max. Drawdown of 6.96 Points during 9 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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Football

Dixon-Coles Model for Football Predictions

A betting strategy to predict the outcome of football matches based on the Dixon-Coles model is evaluated on historical data using Python code. The Dixon-Coles model to predict the outcome of football matches goes back to a scientific publication in the year of 1997. Back then Dixon and Coles, the authors of the paper, published a mathematical model that would allow to predict the result of football (soccer) matches.

Backtest Results:
Backtest Period: 03 Nov 2018 to 12 May 2019
Total Loss: -26.93 Points
Average Loss: -4.25 Points per Month
Number of bets: 280
Max. Drawdown of 37.27 Points during 88 Days

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Horse Racing

Lay the Favourite in Horse Racing

How profitable is it to bet against favourites in horse races? This strategy is about laying favourites in horse racing markets on a betting exchange.

Backtest Results:
Backtest Period: 31 Dec 2012 to 08 Oct 2020
Total Loss: -433.10 Points
Average Loss: -4.58 Points per Month
Number of bets: 76,944
Max. Drawdown of 539.66 Points during 2,280 Days

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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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