The post The Basics Of Football Prediction & Betting Systems appeared first on Punter2Pro.
]]>In this article, I will explore what football betting systems are, their benefits, and the key considerations that should be taken into account when creating one. I will also discuss the importance of probability in football prediction and examine three popular types of football betting systems: grading systems, rule-based systems, and the Poisson distribution.
A football betting system is a strategy or set of rules that guides your football betting decisions. It can help you identify profitable betting opportunities, manage your bankroll, and increase your chances of winning.
There are many types of football betting systems out there, and each one has its strengths and weaknesses. In this article, we’ll take a look at some of the most popular approaches to football betting systems and how they work.
When making a betting system, football or otherwise, bettors should consider the following factors:
Creating a football betting system that satisfies all of the above factors can be challenging, so I invite you to check out the Strategies section of this site for a complete overview of what it takes to succeed as a bettor.
Probability plays a critical role in football prediction because it provides a measure of the likelihood of a particular outcome occurring.
In order to make informed decisions about when to bet, it’s vital to have a good understanding of the probabilities at play. This involves taking into account a wide range of factors, including team form, player availability, head-to-head records, or perhaps even less obvious influences on the game. By analysing this information, bettors can assess the value in the betting markets.
So what is “value”?
A bet is said to have “value” if the odds offered by the bookmaker/betting exchange underestimate the true probability of an outcome occurring. For example, if a bookmaker is offering odds of 5.0 on a particular team to win, but the fair odds for that outcome would be 4.0, then those available odds have value. This is what every football prediction model should seek to find in order to succeed in the long run.
Therefore an important and fundamental skill in football prediction is knowing how to convert bookmaker odds into probabilities and vice versa. The formulas are as follows.
To convert a percentage into decimal odds:
1 / percentage expressed as decimal
For example, an outcome with a 25% chance has decimal odds of: 1 / 0.24 = 4.0
To convert decimal odds into a percentage:
1 / decimal odds
For example, an outcome with decimal odds of 5.0 has an implied probability of: 1 / 5.0 = 0.2 = 20%
The remainder of this article provides an overview of a few basic approaches for any bettors seeking to develop their own football betting system.
A grading system is an excellent starting point for bettors seeking to calculate their own odds to identify potential value in the betting markets. It involves assigning grades or groups to relevant factors, such as team quality or performance, to help make more informed predictions about future events.
In football, a common approach is to group teams within a league based on their level of quality. This usually means assigning a numerical or alphabetical grade to each team, with higher grades indicating better quality. However, it is important to make every effort to avoid bias and ensure accuracy by grouping teams based on statistics rather than relying on personal opinion. One statistical method for identifying “natural groupings” is called k-clustering.
When grading teams based on performance, consider a reasonable time frame that accurately reflects current form. While past performance is a useful indicator, you need to avoid relying too heavily on outdated data as a team’s performance can change rapidly.
When done well, grading teams based on their performance enables the identification of patterns and tendencies among different types of teams that face each other. This approach is often used by both casual and experienced football bettors (whether they realise it or not), as a means of making informed betting decisions.
To begin using graded teams for football prediction, you’ll need to gather past results (try football-data.co.uk). Then you’ll have to assign the teams with a grade in order to produce a forecast for upcoming fixtures.
I recommend using Excel to generate a grid of stats for the results of every grade vs each other. For example, if you have chosen 4 groups in your grading system (let’s say A, B, C & D) then you will have the following 16 fixture ‘types’ to account for.
A vs A | A vs B | A vs C | A vs D |
B vs A | B vs B | B vs C | B vs D |
C vs A | C vs B | C vs C | C vs D |
D vs A | D vs B | D vs C | D vs D |
Within each of the above 16 fixture types there are 3 possible results: Win, Draw or Lose. This means there are 16 x 3 = 48 total outcomes that you need to create statistics for, based on historical performance.
For example, for A vs D (where A is at home) you could determine the following:
Note that the percentages need to add up to 100% for every fixture type.
In this case, your odds would translate to 1.42 (home win), 5.0 (draw), 10.0 (away win). If you believe these odds are accurate, then you would determine that greater odds available at sportsbooks or betting exchanges would represent a value bet.
Once you have established a basic grading system for football predictions, you can add additional factors to further refine and improve its accuracy. By introducing more complexity to the model, you can gain a more comprehensive understanding of the likelihood of different outcomes.
One possible factor to consider is a goals metric, which takes into account the typical winning margins when teams of different grades face each other. By incorporating this information, you can strengthen your predictions and potentially identify opportunities in the goals markets.
Another important factor to consider when developing a football betting strategy is the head-to-head record between specific clubs. This record can reveal patterns and tendencies that go beyond a team’s overall performance or grade. For example, a club may struggle to pick up results at a particular stadium or against a particular team, even if they are performing better overall.
When creating a grading system, it’s important to consider the potential pitfalls that can arise from the data used.
Realistically, using basic grading systems alone may not be sufficient to identify value in highly competitive betting markets — such as the Premier League Match Odds market. While it is possible to break even with a simple approach, a wide range of factors and influences might be needed to achieve long-term profitability. However, mastering the skills required to create odds using this approach can be invaluable when developing and implementing other more advanced betting systems.
Rule-based systems for football prediction involve creating a set of rules or criteria that are used to identify potential outcomes of football matches. These systems are based on the premise that certain factors or conditions are more likely to lead to a particular outcome.
A rule-based system might use factors such as team form, head-to-head record, injuries, and home advantage to predict the winner of a particular match. The system would be programmed with a set of rules that assign weights to each of these factors and then use them to calculate the probability of each team winning.
One of the main advantages of rule-based systems is that they are transparent and easy to understand. The rules used to make predictions can be clearly defined and the system can be tested against historical data to assess its potential profitability.
Rule-based betting systems can be used in conjunction with grading systems — or any other betting system for that matter.
Here are some examples of rules that might be used in a football betting system:
These are just a few examples, but there are countless other rules that can be created based on different factors such as team form, player availability, head-to-head records, home and away form, and more.
The main drawbacks of rule-based systems is that they are rigid and inflexible. They struggle to account for unforeseen circumstances or factors that are not explicitly included in the set of rules. You need to ask yourself: how much “power of hindsight” does my rule-based system actually provide?
When analysing past data, it’s possible to identify a combination of “rules” that could have turned a profit if used for placing bets. However, it’s important not to get excited too quickly, as things aren’t always as they seem. To illustrate this, consider playing the classic Sonic video game…
In theory, there will be a combination of buttons that can be pressed at precisely the right time to get Sonic through a level without being hit by spikes or villains, falling down a hole, or drowning. The string of buttons may be complex and far-fetched, but it’s possible to work it out through repeated playthroughs.
However, this one, very complex, death-dodging combination does not help in completing the rest of the game. It’s useless.
So what am I getting at?
The point is, while it may be tempting to analyse past data to identify patterns or rules that “would have worked had I done that”, it doesn’t always form the basis of a good predictive method. So it’s important to approach rule-based systems with caution.
For example, you may discover incidental patterns in football such as:
Even if these statements are true, it doesn’t necessarily mean you’ve found valuable betting opportunities. The danger lies in overfitting the data, where you’re tailoring your analysis to fit the data too closely, and as a result, your analysis does not apply to future outcomes.
It’s easy to fall into the trap of being overly confident in our own analysis, especially when it seems to show substantial profits. But there are three critical steps you should follow to increase your chances of effectively using ‘rules’ for football prediction:
The Poisson distribution is commonly used in football betting models to estimate the probability of a team scoring a certain number of goals in a particular match, taking into account their average goals per game. By utilising historical data, this distribution can help predict the team’s “goal expectation” for the upcoming match.
For example, if a team has an average of 1.5 goals per game, the Poisson distribution will calculate the probability of them scoring 0, 1, 2, 3, or more goals in a particular match. This information can then be used to determine the most likely outcome of the match and to make informed betting decisions.
Bettors can use Microsoft Excel or comparable program to develop a Poisson Distribution betting model for use in various goal-based betting markets such as Match Odds (1×2), Correct Score, Over/Under Match Goals, Both Teams To Score and Asian Handicap.
Based on my experience working on football prediction projects involving the Poisson Distribution, I have found it to be a more accurate method than using the basic grading and rule-based systems described earlier in this post. This is primarily because the Poisson Distribution avoids generalising by “grouping” or relying on far-fetched trends. Instead, it relies on concise and meaningful data to provide a more accurate estimation of potential outcomes.
Pinnacle has published a useful entry-level article on how to use the Poisson Distribution.?I’ll elaborate on some of the key points.
To begin, you’ll need to gather historical football results in order to calculate the average number of goals scored and conceded by each team, both in home and away games, within a specific timeframe such as one season. These averages are then compared to the league average to determine the attacking and defensive strengths of each team.
To calculate the attacking and defensive strengths, divide the Average Goals For or Average Goals Against by the league average. For instance, if the Average Goals For in the Premier League is 1.45 and Manchester City has an average of 1.97, they are 35% above the league average for attack, indicating their prowess in scoring goals. Here’s how it’s calculated:
1.97 / 1.45 = 1.35 1.35 = 135% 135% - 100% = 35% above average
These metrics, along with the opponent’s corresponding values, are then incorporated into a Poisson Distribution formula. This formula determines the probability of each possible result when two teams face each other. By converting these percentage probabilities into odds, as demonstrated earlier, it becomes possible to identify potentially valuable bets at bookmakers or exchanges.
The optimal number of games to use for calculating goal expectation figures is a subjective matter that requires experimentation. For instance, teams such as Leicester have undergone significant changes over the past decade, making a large window of five seasons less representative of their current form. Conversely, a small window of games (e.g., the past three fixtures) provides limited data to work with.
From my experience, after around ten games into a new season, you have a sufficient amount of current data to work with. However, the smaller the sample, the more likely you are to make poor decisions based on variance.
Expected Goals (xG) is a more sophisticated statistic that quantifies the goal-scoring likelihood of attempts on goal, providing a scientific evaluation of performances. It goes beyond goals, which don not always tell the entire story of a match.
By incorporating xG data into your football betting model, you can produce a more comprehensive analysis of a team’s performance and goal-scoring ability. This will improve the accuracy of your predictions.
While stats-based approaches to betting, like Poisson Distribution, can be effective, they do have their limitations. Firstly, the Poisson only considers measurable results — but there are instances where a team dominates a match but fails to score or loses due to an unexpected goal, such as a late penalty. The final score of a match may not necessarily reflect what occurred during the game.
Another limitation of using Poisson Distribution for football prediction is that it tends to underestimate the probability of draws and the probability of zero. However, this can be rectified using a technique called zero-inflation, which increases the probability of no goals. With this method, the model can account for games where neither team scores and better predict the likelihood of a draw.
While utilising the Poisson Distribution method can generate reasonably accurate football predictions, it’s crucial to recognise that many others are likely using this approach as well. Therefore it is essential to consider the Poisson distribution as a foundation for your model, and to consider incorporating other statistical methods and variables into your analysis. Additionally, always keep in mind that there are variables in football that cannot be predicted or quantified, such as injuries, team morale, and weather conditions.
The world of football prediction is rife with challenges due to the constantly changing nature of the sport. Each season sees teams undergoing significant changes, such as new managers, players, and stadiums, while injuries, player bans, and transfers can all impact team cohesion and strategy. Accurately predicting match outcomes can be a daunting under such circumstances.
Moreover, the media hype and noise surrounding football can further complicate predictions, as public opinion is easily swayed by sensational stories. Meanwhile countless variables such as player form, team morale, and weather conditions can legitimately influence the outcome of a games, making it essential for bettors to separate fact from fiction to make accurate predictions.
While statistical models are a far more reliable method of prediction than “gut feeling” or pure guesswork, they too have limitations in accounting for every variable and situation that can arise. Therefore building a successful betting model can be helped with a deeper understanding of the game, and the ability to quickly respond to breaking news and events.
Ultimately, achieving success in football prediction depends on accurately interpreting all factors that will impact the outcome of a match, and capitalising on value in the markets.
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]]>The post Value Betting Guide | Calculate & Use Expected Value (EV) appeared first on Punter2Pro.
]]>The concept of value in betting is closely tied to Expected Value (EV) – the long-term profit or loss expected from a particular bet or selection method. Value betting involves identifying opportunities where the odds suggest that a selection is less likely to win than it actually is, creating an edge in favour of the bettor and a positive Expected Value.
In this article, I’ll explain the concept of value betting and Expected Value in simple terms, using easy-to-follow examples to help you understand how to identify and take advantage of value odds for a profitable betting strategy.
In sports betting, a value bet is one that is more likely to win than the odds suggest.
A value bet can be identified when a bettor believes that the probability of an event occurring is greater than the implied probability of the odds offered by the bookmaker.
For example, if a bookmaker offers odds of 2.00 on a football team winning a match, those odds imply that the team’s chances of winning are (1/2.00) = 50%. However, if the bettor believes the team has a (greater) 60% chance of winning, then they would view this as a value betting opportunity and place a bet on the team to win.
Value betting is a fundamental strategy for successful betting, as it allows bettors to generate profits over time by consistently finding opportunities where the odds are in their favour.
Value betting applies to sports betting, poker, and other forms of gambling. In each case the goal is to produce a positive expected value (EV), or player “edge”, over time. In doing so, profit is also expected.
EV stands for ‘expected value’. Expected value is a mathematical concept used to determine the average profit/loss of a bet (or series of bets) by accounting for all possible outcomes and their probabilities.
Expected value (EV) is a key concept in value betting, as it helps bettors identify opportunities where betting odds are in their favour. For any bet you place, expected value can be summarised as follows:
In essence, a value bet is one where the expected value is positive or “plus EV”, meaning the bettor stands to gain more over the long run than they would lose.
Regularly betting on +EV bets would give the bettor an “edge” or “advantage”. Both terms mean the same thing.
Expected value (EV) is calculated by multiplying the real life probability of an outcome by the amount of the potential payout, and then subtracting the probability of losing multiplied by the amount wagered, as follows:
Expected Value = (Decimal win probability x Profit per bet) – (Decimal loss probability x Loss per bet).
I’ll show you how to use this formula using examples.
If a bettor places a £100 bet on a team to win at odds of 3.0, and the bettor believes the team has a 50% chance of winning, the potential payout for the bet would be:
Expected Value = (0.5 x £200) – (0.5 x £100) = £100 – £50 = £50
In this example, the expected value of the bet is £50, which means that the bettor can expect to make a profit of £50 for every £100 staked by placing bets of this type over the long run. Therefore the expected ROI is 50%.
If a bettor places a £100 bet on a team to win at odds of 2.0, and the bettor believes the team has a 50% chance of winning, the potential payout for the bet would be:
Expected Value = (0.5 x £100) – (0.5 x £100) = £50 – £50 = £0
In this example, the expected value of the bet is £0, which means that the bettor can expect to break even by placing bets of this kind over the long run. Therefore the expected ROI is 0%.
For example, if a bettor places a £100 bet on a team to win at odds of 1.8, and the bettor believes the team has a 50% chance of winning, the potential payout for the bet would be:
Expected Value = (0.5 x £80) – (0.5 x £100) = £40 – £50 = –£10
In this example, the expected value of the bet is -£0, which means that the bettor can expect to lose £10 for every £100 staked by placing bets of this kind over the long run. Therefore the expected ROI is -10%.
Without knowing the true win probability of an event occurring, bettors can’t determine what the fair odds should be or accurately assign an expected value (EV) to their bets.
Calculating the fair odds of a sports event is a huge challenge. Most bettors fail to consistently get it right.
The Betfair exchange odds are considered the most reliable benchmark for determining a fair price, backed by mathematical evidence. Typically, the correct price for an outcome can be found between the Back and Lay odds of a well-formed market, such as the Match Odds for Premier League games. In general, the true price is closer to the Back price than the Lay price, although this may vary depending on the specific market and circumstances. By comparing their own odds to the Betfair exchange odds, bettors can gain a better understanding of the value in their bets and potentially find profitable opportunities.
Why betting exchange odds are generally correct.
To estimate your potential sports betting profitability and determine the expected value of your betting strategy, it is essential to build a large dataset of past betting results. Provided you have this, you can begin to make assertions about your performance.
For example, let’s say your betting strategy has consistently generated a return on investment (ROI) of +5% over a large sample of bets. If you were to place more bets totalling £100,000 in the future, you can predict that you will earn 5% x £100,000 = £5,000 based on your historical performance.
Similarly, if your average ROI is -5%, you can expect to lose -5% x £100,000 = -£5,000 on every £100,000 staked going forward.
It’s important to note that bet sizes do not impact this calculation but can affect the variance in results. In other words the expected profit/loss is the same whether you place 1 bet of £100,000, or 50,000 bets of £2. However, the former is a lot more risky. Hence, an important aspect to consider when estimating your expected value and profitability is bankroll management.
Even if you have a winning betting strategy, poor bankroll management can quickly wipe out your profits. A common approach to bankroll management is to use a percentage of your overall bankroll for each bet. For example, if you have a bankroll of £10,000 and use a 2% unit size, your stake size for each bet would be £200. This helps to protect your bankroll and prevent large losses from bad variance.
Bettors may also consider the concept of Kelly Criterion, which is a mathematical formula used to determine the optimal bet size based on the perceived value and probability of the bet. The Kelly Criterion takes into account the size of your bankroll, the odds of the bet, and the perceived probability of the outcome.
Learn more about betting bankroll management.
Value bets occur because bookmakers and betting markets do not always set odds that accurately reflect the true probability of an outcome. In other words, bookmakers or betting exchanges sometimes offer odds that are more, or less, favourable than the true probability of the outcome, creating opportunities for bettors to identify value bets.
There are several reasons why bookmakers may not be perfectly efficient at setting odds. For example:
Learn more on how bookmakers set their odds.
Value bets, or “plus EV” bets, can be found at both bookmakers and betting exchanges.
It’s important to note that the vast majority of odds offered by bookmakers would produce a negative (minus EV) result, as the bookmaker specialises in maintaining an “edge” (advantage). In contrast, the average odds available on a betting exchange are typically more accurate, resulting in a fair betting environment where the bettor is neither at an advantage nor a disadvantage on average.
See how I broke exactly even from over 270 random football bets on Betfair.
However, the caveat of offering a fair betting platform is that betting exchanges attract sharp and experienced professionals that compete for odds. This makes it a tough and highly competitive marketplace for punters to find plus EV bets. Hence the easiest way to find value bets is to pick off prices from “soft” bookmakers, whenever they appear. However, bettors need to act fast as value odds normally disappear quickly.
These are the options for identifying value bets.
Value betting software uses algorithms and mathematical models to identify value betting opportunities in real-time. They can scan multiple bookmakers to find discrepancies in odds that suggest a value bet may be available. Importantly, value betting software saves time for bettors and drastically increases their chances of identifying profitable betting opportunities.
Truthfully, there aren’t too many value betting products that are (a) available to the public, and (b) provide genuine value.?However, I was granted free access to review the ValueBetting product by RebelBetting, and I was extremely impressed. The ValueBetting product from RebelBetting monitors price movements across a vast array of bookmakers, identifies plus EV selections the moment they appear, and displays them in a live feed. This product essentially provides users with all the tools necessary to generate a consistent profit.
I’ve also reviewed the Trademate Sports software, which is another superb value betting product. Check out my full Value Bet Finder Review to learn more about both services.
Tipsters are individuals or groups that provide betting advice and predictions on various sports events. They often use their expertise, experience, and analysis of data to provide insights into upcoming events, including information on teams, players, and other factors that may impact the outcome.
Some tipsters are able to find value bets, by determining that the probability of a particular outcome is higher than the odds offered by a bookmaker. Bettors can follow their selections, potentially making a profit over the log term.
However, it’s important to note that not all tipsters are reliable, and their predictions may not always be accurate. Additionally, tipsters often have their own biases or conflicts of interest, so it’s important to choose tipsters carefully and evaluate their predictions critically.
Check out my recommended Tipster sites and be aware of the risks involved in following Tipsters.
Bettors can also use historical data, statistics and other forms of intel to create their own odds for an event, based on percentages for the chance of an outcome occurring. By compiling fair odds in this way, bettors can compare their odds with those offered by bookmakers and potentially identify value bets. There are tools available to help with this process, such as the AceOdds Calculator, which quickly converts percentages into decimal odds.
by compiling odds, bettors have the basis of a system or strategy for selecting bets. For example a system may focus on underdogs or events where the public opinion is divided, as these are more likely to result in odds that do not accurately reflect the true probability of the outcome. Another approach is to consider multiple factors or variables including team and player statistics, recent form, injuries, and other data to identify potential value bets.
It’s important to note that not all betting systems are effective, and some may even be counterproductive. It’s vital to test and evaluate any betting system carefully before using it with real money.
Learn the basics of football betting systems.
Sports trading can also be used to identify and capitalise on value betting opportunities.
For example, if a trader believes that a particular team is undervalued by the market, they may buy bets (back) at favourable odds and then sell (lay) them when the odds correct in their favour. This will result in a profit if the bettor’s analysis is accurate and the odds shift in the predicted direction. The same principle applies if the trader decides to sell (lay) bets at unfavourable odds, before buying (backing) them at a later point.
Sports trading involves fast decision-making and quick action, so it’s important to have a solid strategy in place and be prepared to act quickly when value opportunities arise. Those who master sports trading can benefit from its flexible and dynamic environment, and “winners welcome” policy.
Value betting, like any betting strategy, has its limitations. Here are some of the most common limitations:
Overall, value betting can be lucrative, but it’s important to be aware of the challenges involved and to manage your risk and expectations accordingly.
You can learn more on how to quantify your expected value (EV) by reading the following posts:
Originally posted on 7th September 2016 and updated for 2023.
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]]>The post Expected Goals | How To Use xG For Football Betting appeared first on Punter2Pro.
]]>Expected Goals (xG) is a statistical metric that assigns a “quality” value to every attempt on goal, based on past data. This enables us to better analyse games and determine whether results are in line with the expected outcome. Expected Goals has the potential to revolutionise football prediction, team and player evaluation, and even sports betting.
Expected goals (xG) is a statistical metric used in football to quantify the quality of scoring chances in a match. It is a measure of the likelihood of a particular shot resulting in a goal.
xG is typically calculated using machine learning models that analyse large amounts of data on historical shots and goals, in order to identify the factors that are most predictive of goal-scoring success. These models can be trained on a variety of variables, such as the distance from the goal, the angle of the shot, the body position of the shooter, and the number of defenders between the shooter and the goal.
Once a model has been trained, it generates an xG value for each chance in a particular match. This value represents the probability of the chance resulting in a goal, on a scale of 0 to 1. For example, a shot with an xG value of 0.1 would be expected to result in a goal 10% of the time, while a shot with an xG value of 0.9 would be expected to result in a goal 90% of the time.
xG has become a popular metric in football analysis, as it provides a more objective way to evaluate the quality of scoring chances than traditional statistics like shots on goal or goals scored. It can also be used to identify players or teams that are overperforming or underperforming relative to their expected scoring output.
You might have heard of “expected goals” or seen it used on Match Of The Day. Here’s an example from an old Premier League fixture. What this shows is an xG score of 2.2-0.4 to Man United after the game.
On average, 9.7% of shots in the Premier League are converted into goals. Some are long-range, some are headers, and others are straight forward ‘tap-ins’. Importantly, not all shots have an equal chance of hitting the back of the net. Expected Goals accounts for this, and determines how many goals teams ought to have scored in a match. This gives an expected scoreline.
In the above graphic, Man United’s chances are shown in red/pink, and Stoke’s in dark grey. The bigger the square, the better the chance was. It shows that Man United created more clear-cut chances than Stoke — some of which were inside the six yard box. In this case, the final (actual) score of 3-0 isn’t too far away from the xG estimation of 2.2-0.4. But ultimately Man United scored 0.8 more goals than the xG model expected. This suggests they were fairly clinical, or perhaps slightly fortunate — but nonetheless, they deserved to win the game.
The accuracy of the model largely depends on what factors are used to calculate the xG rating for individual chances. For instance, some basic xG models will only account for the distance of the shots. Other more complex models will account for the positioning of several influential players in relation to the ball to more accurately define how difficult it was to score from different situations. I discuss this in more detail later on in this article.
The xG statistic is growing in popularity because it gives fans, pundits, and even those involved in the sport, a much better way of justifying who was superior in a game — regardless of the actual score.
Previously we might have relied on basic stats, like shots on goal to justify our opinions. But with Expected Goals we have the ability to delve deeper, and account for the quality of those shots. Now we can say “that game should have been 3-0″, with enough detail to justify the statement we’re making.
I’ve spoken before on this site about the limitations of using basic statistics for football analysis. It’s important to recognise that some results simply don’t tell the full story. The scoreline isn’t the only stat that matters for your betting analysis. It’s important to have some sort of context to a past fixture, and even better to be able to answer questions, such as:
Now, thanks to Expected Goals, we can mathematically answer these questions and make better judgements on football matches going forward. From a betting perspective, it has the potential to vastly improve on the basic football prediction models I detailed in my post: The Basics Of Creating a Football Prediction Betting Model.
Runs of form often deceive us throughout the season. It’s is something I’ve touched on before in my guide to football hype & noise.
Expected Goals (xG) is a powerful metric that can help bettors to maintain realistic expectations. By comparing a team’s xG with the actual outcome, bettors can calculate the xG goal difference and assess whether the team’s current performance is sustainable.
This measurement can be particularly useful for mid-table clubs, which may experience ups and downs during a season but generally lack the depth and class of top Premier League teams. By using xG, bettors can gain a clearer understanding of a team’s true potential and make more informed betting decisions going forward.
In the next section, I’ll delve deeper into how xG goal difference works.
The Expected Goals (xG) figure has a lot more meaning for individual strikers than it does for other players who aren’t necessarily expected to score (e.g. defenders).
I was intrigued by something:
Are the top scoring strikers in the Premier League flattered by the fact their team creates more chances for them?
I looked into it and found that during the 2016/17 season (when xG first came about), the player who outperformed the number of goals he was expected to score by the biggest margin was in fact… top goalscorer Harry Kane.
Harry Kane was deservedly regarded as the best, most prolific striker in the Premier League 2016/17 season. He was expected to have scored 18.59 goals, but managed to score an extra 10.41.
Player | Goals | Expected Goals | Expected Goals Difference |
---|---|---|---|
Only includes players with 50+ shots | |||
Kane (Tottenham) | 29 | 18.59 | 10.41 |
Lukaku (Everton) | 25 | 15.32 | 9.68 |
Llorente (Swansea) | 15 | 7.09 | 7.91 |
Son (Tottenham) | 14 | 6.73 | 7.27 |
King (Bournemouth) | 16 | 9.56 | 6.44 |
This table also sheds light on why the top Premier League clubs were interested in buying Swansea’s Llorente (#3) at the end of that season. He performed well despite playing for a struggling team.
Provided the level of detail is high enough, Expected Goals could be used to compare and even value strikers, based solely on their ability to convert chances.
That’s the big question.
xG can include as many or as few factors as you like in order to calculate the average likelihood of each shot being scored. In theory the more the model knows about past cases, the more accurate it is. But, of course, this relies on the model being fed with relevant data only.
I’ve seen sports bettors forming their own xG prediction models by manually assigning a score to each individual chance in games. The principle is great, but in practice there are many ambiguous cases — such as accidental goals — that can potentially weaken the accuracy of the model.
Football data experts Opta create their own Goal Expectation figures. They’ve analysed over 300,000 shots?(a large sample) to calculate the likelihood of an attempt being scored, given a specific position on the pitch, during a particular phase of play. Opta’s model accounts for factors such as:
To obtain an accurate Goal Expectation figure, advanced data gathering and statistical skills are required. However, it is still possible to gain an insight into football matches using fairly simple expected goals systems.
Understat is a great site for monitoring the expected goals from past fixtures. But unfortunately I haven’t yet found a free source that enables visitors to download xG figures for all historical fixtures.
To summarise xG, it’s worth reiterating that the scoreline isn’t the only stat that matters.
OK — in terms of points, it is. But Expected Goals reveals a number of things about a game, series of games, and individual players such as:
Expected goals enables us to better judge teams and players, reduces bias, and helps to more accurately predict future results. The applications to betting are certainly there — and it doesn’t need to stop at football. In fact, the logic behind xG can be applied to any sport. For now it’s being used for football — a complex game?that’s very difficult to predict, and requires equally complex stats to derive something useful from past results.
However, Expected Goals isn’t an all-knowing metric that’ll instantly turn your betting model into a money-making machine, mind you. In fact, in the future it could just help make the markets more accurate. But for now it is a step in the right direction for football prediction and value hunting.
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Outcome bias affects a high percentage of gamblers for two main reasons:
The combination of both gives gamblers the inclination to judge past decisions by wins and profits alone.
To illustrate outcome bias, let’s evaluate the outcome of a wager placed in a casino.
Imagine there’s a game of Blackjack where a player, ‘Maverick’, has a 18 and the dealer has 10.
In this situation 18 is strong, and it’s a statistical no-brainer for Maverick to stand. But let’s also imagine that Maverick doesn’t do things normally and he feels a “vibe” that he will improve his hand by hitting. That is, he thinks he’ll pull an Ace, 2, or 3. He decides to hit.
A 2 card is drawn. He now has 20. The dealer flips over and reveals a 5. Maverick wins! But did Maverick make a good decision?
Those most affected by outcome bias would reason that Maverick’s risky move won the game, and therefore it couldn’t have been a bad choice. But the fact remains: Maverick made a very poor decision at the time of the bet; one that’ll inevitably backfire on him a lot more often than it’ll benefit him.
Outcome bias can negatively influence gamblers of all forms of betting, including sports.
We live in a society that infers that whatever decisions lead to profit were ‘right’. At least until it goes wrong…
I have a few friends working in trading roles at investment banks who know this all too well. I found it interesting to learn how much of their trading ability and value to the company is measured in terms of profit alone and, more strikingly, how little is measured by the methodology and decision making process used to earn it.
One friend spoke of the enormous stress he was under to increase his trading profits in order to continue working at his job for another year. He told me that his colleagues, who felt the same pressure, had resorted to lumping on increasingly larger trades in an attempt to bump up their yearly performance. Do you see where I’m going with this?
If those high risk trades made a profit then that would be deemed ‘right’, irrespective of whether it was smart, responsible or even sustainable. Such ‘winners’ would be rewarded with job retentions and bonuses, while ‘losers’ would be deemed to have made bad choices.
This exact kind of outcome bias is ever-present in sports betting. Gamblers have a tendency to appraise past decisions on results alone, with little regard to the selection process used.
Sport is an outcome-driven industry that only fuels poor sports betting decisions.
Take football as the prime example. The obsession with winning supersedes common sense across the entire game.
Managers are regularly condemned by their clubs based on results, and not performance.
Imagine the Man United manager is under fire after a string of consecutive losses and it’s crunch time this weekend in upcoming Manchester derby. Can he save his job?
Suppose the players respond to the pressure and fight for the manager’s job. United dominate the game, hitting the post twice, missing a penalty, and drawing multiple saves from the opposing goalkeeper. In 90+4 United score a the wonder goal they deserved — but it was controversially deemed offside by VAR and struck off. Final score: 0-0.
The outcome of the match will often dictate whether or not the manager is deemed fit for the job; hence in this scenario the manager would be sacked.
Yet on the flip side, if United got the rub of the green and won 3-0 as deserved, then the board would almost certainly view the current situation in a positive light. They might even see the manager as “turning a corner”. In either case, there’s a tendency for score lines to dictate big decisions in football, no matter how irrational it seems.
The “do or die” culture in football makes it harder for bettors to think in terms of probabilities, potential, luck — or anything other than pure results. It’s a challenge to switch between the two modes.
Goals and wins mean everything to emotional football fans. But this can heavily impede sound judgements.
Imagine a team played an uncharacteristic 4-4-2 formation in a match. How might die-hard fan ‘Biased Bob’ evaluate that decision?
Therefore Bob is biased towards the outcome of the game.
While Bob might represent an extreme case, many sports fans feel so emotionally attached to their club/player that poor judgements are commonplace.
The “if it won, it was right. If it lost, it was wrong” mindset is dangerous when carried forward from sports fandom into sports betting. It’s too binary.
Bettors must change their perspective of what a “good” and “bad” bet actually is.?
Good bets can lose, and bad bets can win. The result itself does not change whether the decision to place the bet was wise, or unwise. A good bet is that had the odds in your favour; where you found value.
For instance, suppose the fair odds for an underdog to win a football match is 6.5. One bettor accepts odds of 5.0, and another accepts odds of 7.0. If the bet wins, both bettors succeeded in terms of selecting the winner. But only one bettor succeeded in terms of finding value: the one that took 7.0. This is how any truly successful gambler will measure the quality of their bets.?
You can learn more about assessing your betting performance from my articles:?
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One of the simplest examples of gambler’s fallacy can be demonstrated using a Roulette wheel. Suppose that the past five spins produced a black number. What colour is most likely to appear on the next spin?
Those most impacted by gambler’s fallacy would reason that red is more likely to win on the next spin because black has already appeared consecutively, against the odds, five times.
However this logic is incorrect. Just because black occurred more frequently than was expected, does not mean the chance of it reoccurring diminishes in the future. Consider that black always has the exact same chance of winning as red. Therefore the next spin is not more likely to produce a red than a black. The chance remains equal, as always.
Gambler’s fallacy cannot apply to sport because it’s possible for previous outcomes to impact future outcomes. Past performance is, in many cases, a relevant predictor for upcoming events.
Consider that, unlike Roulette, the results for sportsperson or team aren’t just down to pure chance. Sporting performance is impacted by a variety of factors such skill, confidence levels, physical attributes, and experience. These factors, among many others, dictate how likely an outcome is to occur. Importantly, these outcomes are not completely independent from previous ones because there are common threads (e.g. current fitness levels) that may exist between events.
Furthermore the results from previous events alone can directly impact upcoming events. For instance it’s common for football teams to build momentum and team spirit over a series of wins – this could result in either complacency or more confidence in the future. On the other hand, a series of losses can generate compounding pressure on a team – this could result in a lack of confidence, or a much-needed boost in determination and fight. In both cases, the past affects the future. So it’s not necessarily a ‘fallacy’ for bettors to place relevance on previous events in order to predict the future.
If you step outside of the sport itself, gambler’s fallacy can (and does) negatively impact sports bettors in terms of estimating their chances of winning upcoming bets.
For instance, a sports bettor that heavily relies on luck may reason that a string of losses means a turn-around is imminent. Or that a string of wins means losses are more likely to occur soon.
This line of thinking can lead to poor decisions. The reality is that nothing is guaranteed to “even out” — especially if the strategy is weak or flawed. It’s superstitious, and irrational, to believe that good or bad sports betting fortunes are going to somehow impact the future outcomes of professional sport.
Smart sports bettors acknowledge that every upcoming event has a chance of winning or losing (with varying probabilities). Unlike an amateur, the pro will not be swayed by short-term results and will view outcomes as a long series of fluctuations that are, ultimately, expected to generate a return. Hopefulness and superstition doesn’t come into it — because the pro would’ve aimed to obtain value on every bet placed. Therefore good (or bad) fortune is a bonus (or upset), and nothing more.
Compared with other forms of bias that I’ve covered on this site, gambler’s fallacy is arguably the easiest error to make. So you have to be conscious enough of it to prevent it from weakening your approach to betting.
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]]>The favourite-longshot bias refers to the tendency for longshots to be overrated, in terms of their chance of winning, compared to favourites. In other words, the odds for longshots are comparatively worse value than favourites.
It’s important for sports bettors to acknowledge the favourite-longshot bias in order to avoid taking low-value odds.
It’s been widely established that, across many sports, longshot prices are disproportionately shorter relative to their fair prices than favourites.
There are three mains reasons why I believe the favourite-longshot bias exists in sports betting:
In sports such as horse and greyhound racing a longshot often represents a little-known or out of form runner that has not demonstrated much ability to win the race. The longshot is certainly not the focal point of the event. This poses a problem for bookmakers: how can they price this obscure entity without getting it terribly wrong?
The usual approach bookmakers take is to refer to the betting exchanges as a guide for where to set the odds. But if the public also knows very little about an entity, then that’s going to be reflected with very low liquidity and wide spreads on the Betfair market. This doesn’t give much to go by.
Therefore the bookmaker has to make their own call as to where to set the odds. Very often that results in an extremely cagey, low-value price.
Sports bettors enjoy the excitement of the longshot. The average recreational gambler would sooner speculate on outsiders in hope of receiving a large payout than backing short-priced runners for smaller, more regular returns. Therefore longer-priced runners are typically over-backed relative to their likelihood of actually winning.
Naturally, this increases the risk for bookmakers: if the longshot wins, then they’ll need to shell out huge sums due to disproportionate sums placed at such high odds.
Bookmakers manage that risk by continually reducing the price as longshots attract more volume from bettors. While cutting the price reduces the average odds to pay out on, it also makes the longshot selection increasingly less attractive as a proposition. That way bettors are more likely to explore other options in the market.
Given that longshots tend to involve less-known entities, and that casual bettors often see them as a more exciting proposition than favourites, it’s all too easy for bookmakers to take advantage.
Sports bettors are more price conscious about what they know and understand. Even casual bettors will have an expectation as to where the price of a favourite should be. This might be based on observations, previous results — even previous prices. The same can’t be said for an obscure selection, with little or nothing to go by. Ignorance is easy to exploit.
But perhaps the biggest difference between backing a favourite and backing a longshot is that is that the longshot is often taken on the pure basis that it could, on the off chance, produce a very nice profit. You don’t back a favourite to win big — therefore you, at the very least, want the payout to be competitive. Essentially, bettors are happier to take sub-par odds on the longshot than the favourite.
Think of it this way: an 80/1 bet offers a relatively similar level of “excitement” to a 90/1 bet, yet the odds are substantially different. Let’s suppose that 90/1 is the fair price. Would an average punter realise, or care, that they’re getting such a bad deal by taking 80/1?
Bookmakers are aware that price consciousness is lacking at high odds and that the majority of punters won’t have the means to price up longshots, or the inclination to shop around before taking them.
To date, it’s still disputed why the favourite-longshot bias exists. But the above reasons make the most sense given the typical behaviours of both bookmakers and sports bettors.
Firstly, for the reasons covered in the previous section, it’s important to note that Betfair will regularly offer substantially higher odds on longshots than bookmakers. Switching to Betfair is a very simple way of improving the value you take at high odds.
But the existence of the favourite-longshot bias doesn’t necessarily mean you should only be backing favourites, or basing your strategy solely around them. Nor does it mean you should neglect longshots entirely. As always, assess every selection on an individual basis.
Several betting strategies I’ve worked on targeted mid-market prices — not favourites or longshots specifically — for the following reasons:
Thus mid-market odds strike a good balance of liquidity and the potential to find value.
If you’re intrigued by the favourite-longshot bias and would like to learn more on the theory, I recommend the following:
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Sports betting markets do not offer controlled certainty, so the chance (or odds) for any given outcome will change in the time before an event starts.
A number of factors can affect odds, but the main reasons for price fluctuations are as follows:
The most experienced sports bettors aim to determine a theoretical price that represents value for an outcome, and then base their decisions around that. But it’s understated that if variables change, then so does the price that represents value.
I was once in contact with an enthusiastic bettor and reader of this site who was devising various strategies. Like many others, he was creating a pricing model to identify value bets and aimed to take those odds as they appeared in the market. However, the downfall for several of his strategies was that he also reasoned that odds which drifted to a greater price at a later point time would represent even greater value. His line of thinking was that taking a higher price would only improve the average odds of his selections, and thereby increase his profits.
That’s when we discussed a simple yet somewhat overlooked concept in sports betting: value moves with the odds. So in theory a price right now may not still be value in days, hours, minutes — or even even seconds time.
You heard right: a value bet a few seconds ago may no longer be a value bet now!
To understand why value moves with the odds, here’s a very simple example. This concept is nowhere near as mind-blowing as it sounds.
Imagine there’s an upcoming football match between Crystal Palace and Arsenal and, given all current circumstances, the fair odds for Crystal Palace to win is 4.0. In this case, it’s correct to reason that a price of over 4.0 for Crystal Palace in the match odds betting market is a good bet to place at this moment in time. So if the market offers 5.0 for Palace, we’d place that bet (let’s assume we did).
Now, suppose the plot thickens. News breaks on the day of the match that two of Palace’s key players have come down with the Norovirus and are no longer fit to play. As a result, the match odds for Palace shoot up to 7.0 to reflect the weakened squad.
Suddenly that 5.0 bet isn’t looking so good after all, is it? It’s almost certainly not a value bet any longer.
The na?ve mistake here would be to ignore the dent in Crystal Palace’s chances and rely on previous assumptions. Indeed the price of 7.0 is greater than the previously taken odds of 5.0 — but we cannot be sure that the new price represents value. That’s because we no longer have an accurate barometer for the ‘fair’ odds, as the previous fair price of 4.0 was created under very different assumptions that no longer stand. Therefore a re-appraisal is necessary to find out where the new value price sits. Only then can we determine if 7.0 is worth taking or not.
Similarly, if a negative change impacted Arsenal instead of Palace then that would strengthen Palace’s chances, which would be reflected by a decrease the odds for Palace to win the game. This scenario would strengthen the value of the original bet placed at 5.0.
The value you have isn’t in your control because your price is fixed while other variables are moving.
Yes, this may seem highly obvious. Yet bettors often forget that a series of small changes in circumstances can re-shape an event enough to move where the value lies. In particular, bettors must take care whenever a tipster suggests a “target price” — because circumstances may have changed from the time the tips were published.
One of the difficulties with sports betting is that even if you capture value at the time of bet placement, it doesn’t necessarily mean it’s still a value bet now or that it’ll still be one by the time the event starts. In fact, every strategy — even highly profitable ones — have a mixed bag of value.
In other words, some odds you take will turn out to be great bets, while others will turn out to be bad bets. This can be determined by comparing each your odds to those available at the start of the event (once their up/down journey is complete). Whenever your odds are greater the Start Price, that’s a value bet and you have successfully secured an advantage, irrespective of the outcome. For proof of this concept, check out my article Beating The Closing Line.
Unfortunately we as bettors cannot predict all changes in circumstances. Hence we cannot be certain that the odds we take at the time of bet placement will remain value by the time the event starts. So the aim is produce a strategy where the majority of bets will beat the start price by a substantial margin. And the only way to be sure that’s occurring is to monitor your results and check for consistency.
As a sports bettor you’ll continually face crucial decisions about the odds you take. Most often you’ll have to decide whether to accept lower odds than you initially wanted. Should you ever take lower odds?
There is no straightforward Yes/No answer as every bet needs to be assessed on an individual basis. Ultimately it depends on whether or not those lower odds still represent value.
One of the reasons I recommend the Smart Betting Club tipster proofing site is that their statistics reveal the impact of taking odds below those recommended by their tipsters. This highlights the point at which the value diminishes entirely for the strategy being used. You’ll have to evaluate your own strategy in the same way by analysing past data.
Given that odds fluctuate on the lead up to sports events, it’s important to consider what implications this has for your betting strategy.
For those taking a high-level stats-based approach to finding value, you’ll need to be aware that price changes within the market are occurring for a reason. Fluctuations may supersede the accuracy of your own odds compilation method. In other words, if changes occur that you haven’t accounted for then your method may not hold up.
On the other hand, the movement of odds can be highly advantageous to bettors. Changes in circumstances often creates temporary uncertainty, making it a prime opportunity for sports traders to secure exaggerated odds, or profit from price movements. It’s at these same moments that different betting sites are frequently mismatched with their odds, creating arbitrage and value bet opportunities for bettors to capitalise on.
If possible, automate your strategy. There’s no better way of dealing with price movements that having the ability to monitor live prices and act dynamically at the instant an opportunity appears.
For better or worse, the movement of odds will impact your strategy. The important thing is that you acknowledge that price moves usually represent a change in opinion — as well as value.
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]]>The post Best Value Betting Software 2022 | Top Value Bet Finder appeared first on Punter2Pro.
]]>Truthfully I’ve struggled to find Value Betting Software that’s:
I’ve sieved?though a lot of so-called Value Bet finders/tools and discarded them one by one. However, finally, there’s some Value Betting products that I can recommend. Both of them enable punters to earn long-term profits from their sports bets.
If you’ve been struggling to find a genuine, profitable Tipster then definitely read on: Value Betting is the proven, smart alternative method you should know about.
‘Value’, in betting terms, is presented when?the odds?suggest?that the selection isn’t as likely to win?as it really is. Value betting puts the ‘edge’ in the player’s favour, meaning it’s profitable long-term.
While Value Betting carries risk, it’s not traditional gambling as you know it — because you’re expected to win over time. If you’d like to learn more, then I recommend reading my post What Does Value Betting Mean?
Finding Value Betting Software that actually provides a money-making opportunity is certainly a challenge. Value Betting Software isn’t?generally?available to the public. After all, why would anyone give access to their profitable?Value Bet?selections and encourage more competition for odds?
I’ve asked this same question of Tipsters, and made my reservations clear in previous posts. For more information take a look at my post:?Can Tipsters Be Trusted?
The answer to this question is pretty simple…
Granted, many?professionals would never?dream of giving anyone else access their software — hence the shortage of available products. But many Value Betting techniques are somewhat limited in terms of profitability. Bookmakers clamp down on Value Bettors by limiting their stakes, and in some cases, closing their accounts entirely…
Therefore professional gamblers tend to make?as much money as they possibly can, and then move on to monetising their ‘Bet Finder’ on a subscription basis. This way they can continue earning from it once they’re unable to place bets themselves.
It makes sense, right?
Value Betting Software is?a lot like Arbing Software. Both products present an opportunity for Punters to capitalise on inaccurate prices in the sports betting markets and?earn long-term profits.
What follows is a comparison of various factors which have an impact on Value Betting & Arbing.
This is where Arbing and Value Betting differ the most. Arbs guarantee the Punter risk-free profits, whilst Value Bets carry a risk (albeit, a?calculated one). Value Bettors take on the risk because their bets have an ‘edge’ that wins over time.
To learn more on what it means to have the “Edge” or “Expected Value” in your favour, read my post:?Calculating The Expected Value (EV) Of Your Bets
Arbing?[generally] secures?a smaller % profit?on each trade than?Value Betting. This is, in part, due to the commission paid on winnings earned on the betting exchange (e.g. Betfair).
However, this is only a generalisation. It also depends heavily on the sports/markets used.?For example, the margins on Horse Racing — regardless whether Arbing or Value Betting — tend to be higher than on football.
Every betting account that partakes in Arbitrage betting has a lifespan, which can be anything from day to a month before the Bookmaker gives it the chop. Value Bettors get the same treatment. You have to accept that the time will inevitably come where the?Bookmaker limits your stakes or prevents you from placing further bets.
The good news is that Value Bets are more difficult to spot than Arbitrage Bets. Punters can identify their Value Bets using various methods & techniques, by comparing odds from a range of different sources. Arbitrage Bets are found by simply comparing the?Bookmaker odds to the Exchange. So Value Betting is more complex — thus Bookmakers?can’t detect it as easily.
Furthermore, because Value Bets generally?carry?risk,?the Bookmaker is more lenient to Value Bettors than Arbers (who guarantee a profit on every trade). However, bare in mind that if you bet frequently and consistently earn a profit, then you’re bound to draw attention to yourself at some point — whether you’re Arbing or not.
I highly recommend reading my post?Prevent Your Betting Accounts From Being Restricted Or Closed.
In-Browser Value Betting Software
I recently came across a Value Betting Finder named Trademate Sports. I was granted free access to review the product, and I must admit I was very impressed. In my opinion, this is the kind of product that Punters should use as an alternative to Tipsters.
Trademate was previously known as Edgebet.net.
The Trademate Sports value betting software calculates the true odds of the outcome of a sporting event and provides you with all the tools necessary to identify profitable opportunities in the global sport betting markets.?
Their algorithm runs 24 hours a day, 365 days per year across Football, NFL, NBA, MLB, Handball, etc. Each sport represents a new opportunity and their algorithm is able to detect exploitable value.
There’s no need to download anything to use the Trademate Sports Value Betting Software. The in-browser interface means that service it’s fully compatible with any computer or mobile device.
A lot of other Value Betting Tools are made by programmers, for?the use of programmers with an interest in sports betting. What stands out about Trademate Sports is that it’s designed for the average Punter. There’s no programming knowledge required to get up and running.?It takes about one minute to get set fully up, with bets instantly coming through on the Trade Feed. And if you get stuck there’s a live chat feature, too.
After logging in for the first time I quickly got to grips with how everything works. It’s just a simple case of setting up what Bookmakers you’re going to use, and how much you’re investing into each one.
The user has an option to set a bell sound alert whenever a new trade pops into the feed — which means you can even bet whilst you’re working on something else!
Note: Value bets must be placed in your regular betting account(s). Trademate isn’t integrated with any Bookmakers.
In their own words:
There’s a number of factors we have to consider when calculating the correct odds of a match, each sport and market have their own individual and sometimes complex nuances, our algorithm determines how these nuances and factors should be weighted to calculate the true odds, based on the liquidity and timing across the various markets.
Trademate Sports?doesn’t?elaborate further into what they do to identify value bets. They still maintain some level of secrecy. But from reading their website, and chatting to their staff, I can infer that they?are [at least in part] following various prices in order to anticipate market movements. For those of you that read Punter2Pro regularly, you’ll be aware that I’m an advocate of?this sort of technique.
For proof of this concept, check out the Punter’s Guide To Beating The SP.
Unlike other Value Bet Tools, Trademate doesn’t have any Bookmaker affiliate links on the website whatsoever. This is good news, because it makes no sense that a Bookmaker would support?this product. Bookmakers only endorse products or strategies where players are set up to lose.
It’s extremely tedious logging each and every bet you’ve placed, updating the results, and calculating the profit. Thankfully Trademate?makes life easy in this department. You simply open up your feed, click the ‘trades’?you’ve placed, and enter the stake for each one. You can amend any of the bet details at any point, in case you entered the wrong details (odds, stake etc).
Users?can also monitor their total bankroll by entering how much money was initially deposited at each Bookmakers. This is a nifty feature — but it’s slightly limited in that it doesn’t yet enable the user to enter?subsequent deposits and withdrawals. However, this doesn’t actually?impact the important stats, such as the ROI %.
Now here’s the really impressive part of Trademate Sports — the data presentation.
The EV (Expected Value) of the bets is plotted against the actual profit on the ‘Analytics’ page. It also shows the Closing EV — which is basically the Starting Price (SP) of the event. This is important to monitor because whilst your bet?may have originally had?value when it first appeared on the feed, circumstances can change (e.g. a key player is announced injured), and the price adjusts accordingly. This means your bet’s value?will be impacted, too. So you want to be ‘beating’ the Closing EV with the prices you’ve bet on.
There’s another chart on the same page which presents?the Closing Odds vs. the Hit Rate. This gives the user an idea of how?well distributed their results are.
Critically, there’s also a full breakdown of the?betting results in a table format. ‘Turnover’ represents the total amount staked. Included within this breakdown is the ‘Flat ROI’, which shows how the bets would’ve performed with an equal bet size.?I recommend using the ‘Flat ROI’ as a marker, because?too often our results?(and expectations) are distorted by the increased variance that comes with ranging bet sizes.
To learn more about variance in sports betting, read my post How Can I Be Sure That I’m Really Winning?
Trademate Sports comes with a free 7 day trial. I highly recommend taking advantage of that.
There are 2 pricing plans on Trademate Sports — “Core” and “Pro”. Both offer ample value betting opportunities.?You’ll receive?30 EUR free credit, too!
It’s a smart idea to start out with a 1 month plan in order to monitor your progress and determine how much spare time you have to place your value bets. Once you know you’re able to cover costs, you’re ready to scale up with a 3 month plan.
Keep in mind that your PnL is directly correlated to your turnover. The more bets you place, the more you’ll earn in the long-run.
Downloadable & Mobile Value Betting Software
It was over a decade ago that RebelBetting revolutionised sports arbitrage?with their?industry-leading desktop application. Now, finally, they’ve ventured into the realm of Value Betting by launching yet another superb product to the standard you’d expect from the established brand.
All RebelBetting software is developed by Clarobet AB, a small team of developers and sports betting specialists based the north of Sweden.?They serve customers from over 120 countries.
The RebelBetting company started out in 2007 when two programmers and two professional poker players combined forces to build a subscription-based sports betting program that generates?guaranteed profits. This lead to the creation of their cutting-edge?Sports Arbitrage Finder,?and pathed the way for the all-new Value Betting service.
RebelBetting Value Betting software is designed to enable bettors to take advantage of overpriced odds.?Simply put, their Value Bet Finder identifies bets that have more chance of winning than the Bookmakers’ odds imply,?and helps users to place them as easily as possible. It’s this profitable, systematic approach to betting that I fully endorse, and thoroughly reiterate, throughout this entire site.
If you’re looking for a stable, dependable Value Betting Service then look no further than RebelBetting’s offering.
RebelBetting Value Betting Software comes in two forms — the downloadable software?and the?web version. Both versions have their own unique strengths.
Here’s a comparison of the two products:
The downloadable RebelBetting Value Bet Finder is compatible with PC or Mac. It doesn’t run on mobile devices, or through a standard web-browser.
This isn’t a negative, though. RebelBetting understands that, above anything else, a Value Bet Finder needs to be extremely fast and stable. Thus the power of your computer will only serve to improve its overall performance.
Remember: value bets don’t stay around for long. Using a computer — equipped with a mouse and dual monitors — is the ideal setup.
Once you’ve downloaded the light-weight RebelBetting software and followed the (rather standard) on-screen installation steps, you’ll be up and running in minutes. It’s the same process as installing any other out-of-the-box application.
Launched in 2019 was RebelBetting’s mobile web version of their Value Betting Software.
It can be used on any platform, on both your mobile devices or desktop computer. All major browsers are supported, with no need to install anything.
RebelBetting’s?Value Betting Software is highly user-friendly and simplistic. It automatically logs you into Bookmakers, takes you directly to betslips, and fills them out for you. Neat.
In truth, once you’re set up, the only thing you have to do is check your stake/odds prior to placing your Value Bets. It’s that simple.
The desktop application makes full use of a built-in browser which does it’s utmost to select your bets automatically. This worked perfectly in the above example (note the correct selection has been detected, in red).
RebelBetting’s built-in browser saves users the aggravation of loading up multiple tabs for each Bookmaker, constantly logging into accounts, locating the correct sports markets, and filling out bet slips. Subscribers will earn far more from Value Betting than they ever could hope for with a ‘manual’ approach.
This video from RebelBetting underlines just how streamlined, well-designed and simplistic it is to find & place Value Bets using the software.
As you would expect from a desktop application, the RebelBetting Value Bet Finder packs a bunch of configurable features.
Here’s the ones which stand out:
RebelBetting Value Betting Software doesn’t provide a risk-free proposition, like their?Arbitrage Betting?platform does. Every Value Bet you place carries risk. But it’s certainly a calculated, proven method for you to outsmart the Bookmakers at their own game.
Using the RebelBetting Software you will be provided with a steady stream of Value Bets from more than 90 Bookmakers, at any given time. That’s an enormous supply of bets — and it’s likely to grow as time goes on, and more Bookmakers are bolted on.
So what’s the profitability like?
In the test-runs of RebelBetting’s Software, users tripled their bankroll after placing 6,000 Value Bets recommend by the software. The average ROI, given the recommended stakes, was 14%.
While I expect the ROI to decrease a little over time, there’s no doubting that the approach works. That’s a huge sample size of data. Much like Trademate, it’s highly likely to generate a profit provided you stay rigid and continue to follow the recommended bets.
RebelBetting are so confident you’ll earn a profit that they offer a?100% Profit Guarantee?on your first month. In their own words: “If you don’t make a profit, you’ll get another month for free.”
In my opinion, this is the software Bettors should use before they consider venturing into the more uncertain world of Sports Tipsters.
There are 2 pricing plans for the RebelBetting Value Betting Software — 1 Month and 1 Year. You’re discounted 50% per month for taking the annual option.
The pricing is noticeably low. There’s really more than enough value offered by the software to cover either subscription, and leave you with a profit.
Understandably, you might feel most comfortable starting out with a 1 month subscription.
But with?the vast array of Bookmakers to use (90+) it could be wise to invest in a year long contract (at 50% less per month). My advice would be to switch to the annual package as soon as you’re confident you’ll have longer than a 6 month run at Value Betting.
Remember that?Bookmakers will begin to limit your stakes?for placing Value Bets. What you’ll generate from Value Betting largely depends on your how much total stake you can get away.
For the moment Trademate Sports and RebelBetting are the Value Bet Finders that impresses. Both Value Bet Finders more than justify their monthly fees.
But what other ways can you earn from sports betting?
If either of my recommendations are out of your price range, or you don’t have the risk tolerance or bankroll, then I highly recommend that you explore other types of Value Bets:
These are two money-making alternatives that carry?no risk. I advise that you?begin with these techniques and then progress on to Value Betting.
Alternatively, you might decide to seek value from Sports Tipsters, who recommend bets to you based on their expertise.
Just be careful: the historical results of Tipsters need thorough proofing. It’s an industry rife with scammers and ambiguous results.
Before you proceed, read my review of the Top Tipster Sites. I highly recommend using the following sites:
Lastly, you could take the harder — but potentially most rewarding — route: develop your very own profitable Value Betting Strategy.
For this I highly recommend reading the following posts:
It’ll take a lot of work and ingenuity to develop a consistently profitable sports betting model. But it’s certainly possible.
Good luck with whatever approach you take.
Originally posted on 25th January 2017, and updated for 2022.
The post Best Value Betting Software 2022 | Top Value Bet Finder appeared first on Punter2Pro.
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