Research on profitable strategies for betting on draws in soccer has produced mixed results. Some studies have found that the Fibonacci betting strategy, where bettors increase their stakes following a loss, can be profitable (Demir et al., 2013; Archontakis & Osborne, 2007). However, other research suggests that this strategy may actually result in losses over time (Lahvička, 2013).
In addition to traditional strategies, researchers have explored newer approaches to exploit market inefficiencies. Machine learning algorithms have been applied to identify patterns in betting markets, with some promising results (Stübinger et al., 2019). Another approach, the PARX model, has also shown potential in improving betting predictions and returns (Angelini & Angelis, 2017).
Some studies have focused on specific markets, finding inefficiencies that can be exploited. For example, the German TOTO 13er Wette, a type of soccer pool, has been identified as a market where bettors might find opportunities for profit due to its unique characteristics (Stommer, 2023). In other cases, researchers have developed strategies for betting exchanges, where bettors use both “back” and “lay” bets to balance their risk and increase their chances of winning (O’Shaughnessy, 2012). While some research suggests that a careful and strategic approach to betting on draws can lead to profits (Malarić et al., 2008), the overall efficiency of soccer betting markets remains debated. Despite this, skilled bettors may still have opportunities to outperform average market conditions and achieve consistent success.
Some research suggests that a careful and strategic approach to betting on draws can lead to profits
Summary of: Malarić et al, 2008
Anecdote
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Articles Cited
- “Jiří Lahvička (2013): The Fibonacci Strategy Revisited: Can You Really Make Money by Betting on Soccer Draws?, https://doi.org/10.2139/ssrn.2280423
- The paper concludes that the Fibonacci betting strategy for betting on soccer draws, previously presented as both simple and profitable, is actually simple but not profitable, contradicting previous findings in the literature.”
- “Ender Demir, Hakan Danis, Ugo Rigoni (2013): Is the soccer betting market efficient? A cross-country investigation using the Fibonacci strategy., https://doi.org/10.5750/JGBE.V6I2.580
- The authors find that implementing the Fibonacci betting strategy on draws in 8 European soccer leagues over 4 seasons yields positive returns, indicating that the soccer betting markets are inefficient.”
- “F. Archontakis, E. Osborne (2007): Playing It Safe? A Fibonacci Strategy for Soccer Betting, https://doi.org/10.1177/1527002506286775
- The paper explores using a Fibonacci betting strategy to earn economic profits from betting on the draw outcome in soccer matches, specifically in the FIFA World Cup Finals, despite the fairly large risk involved.”
- “R. Stommer (2023): Beating the Average: How to Generate Profit by Exploiting the Inefficiencies of Soccer Betting, https://doi.org/10.2139/ssrn.4393149
- The paper presents a strategy to systematically generate profits from the German soccer betting TOTO 13er Wette by applying stochastic methods to determine the number of lottery tips required to achieve a specific number of correct match forecasts for any given level of safety, which reveals an inefficiency in the betting market.”
- “Darren O’Shaughnessy (2012): Optimal Exchange Betting Strategy for Win-Draw-Loss Markets, –
- The optimal betting strategy for “”win-draw-loss”” markets on betting exchanges, where bettors can both back and lay the different outcomes, and the exchange takes a fee on net profits rather than a margin on each bet.”
- “R. Malarić, Tomislav Katić, D. Sabolic (2008): The market efficiency of the soccer fixed odds internet betting market, https://doi.org/10.1080/13504850600722021
- This paper examines the efficiency of the European soccer fixed odds internet betting market and presents a simple betting strategy that appears to be profitable.”
- “Johannes Stübinger, B. Mangold, Julian Knoll (2019): Machine Learning in Football Betting: Prediction of Match Results Based on Player Characteristics, https://doi.org/10.3390/app10010046
- The paper presents a machine learning framework for forecasting football match results and achieving excess returns through betting, using a large dataset of player characteristics and skills as well as betting odds data.”
- “Giovanni Angelini, L. D. Angelis (2017): PARX model for football match predictions, https://doi.org/10.1002/FOR.2471
- The authors propose a new statistical model called the Poisson Autoregression with eXogenous covariates (PARX) model to predict the outcomes of football matches, and they show that this model outperforms a previous approach and can be used to develop a profitable betting strategy.”
Insufficient Detail?
At times it is difficult to answer the question as there are not enough relevant published journal articles to relate. It could be that the topic is niche, there’s a significant edge (and researchers prefer not to publish), there is no edge or simply no one has thought to investigate.
