Football Expected Goals: Frequently Asked Questions
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- Shots vs XG
- XG Predictions
Why don’t you just use shots on goal?admin2019-06-28T16:46:30+00:00
Why don’t you just use shots on goal?
Team A have taken 10 long shots. Team B have had 4 shots from close range 1-on-1 situations with the keeper. In pure shots terms the stats suggest that 10 shots are better than 4 (net +6) but in reality team B had a lot higher percentage chance of winning the game.
An analysis of 5469 games highlighted that shots only predict the home result correctly 54% of the time and away result 41%. This is significantly lower than Shots on Target and Expected Goals.
Is shots on target a fairer prediction?admin2019-06-28T16:53:23+00:00
Is shots on target a fairer prediction?
Yes it is. Shots on target gives a better prediction than total shots.
Shots on target predicts the home team winner correctly 68% of time and the away team 53%.
So how much better is expected goals?admin2019-08-11T05:20:23+00:00
So how much better is expected goals?
Expected goals predicts the correct home team result 66% of the time and away results 58% of the time. This is slightly better than shots on target on the away results and slightly worse on the home results.
For the astute among you, it can be seen that shots on target and expected goals provide similar results in predicting the outcome of a match.
Standard Deviation of Results
This is correct in a sense, but the above calculations are based on the shots and expected goals that occurred within the individual match i.e. predicting the outcome after the number of shots and expected goals are known. The biggest difference is that teams have a lot higher standard deviation in shots on target versus what they do in expected goals (3.6 vs 1.2). For anyone unfamiliar with standard deviation, it just means that the lower it is the smaller the spread of outcomes from the average. For example, a team over 5 games may have shots on target of 2,6,7,3,2. This shows a large variability in outcomes away from the average of 4. Conversely, expected goals will often look like 1.5, 2.8, 2.5, 2.2, 1.4 which shows a lot more consistency and translates to the real life amount of goals that should have been scored.
Due to the lower variability in outcomes, expected goals is a far superior tool for predicting the expected goals a team will score and concede in any future match.
Do shots and expected goals predict draws?admin2019-06-28T16:54:30+00:00
Do shots and expected goals predict draws?
Using shots on target and expected goals has a very low success rate in predicting draws. This is largely due to the low scoring nature of football, and one lucky goal quickly turns a draw into a win or defeat. For anyone who claims they can predict draws, I will be very skeptical as I have not come across any good models or statistical analysis that provides long term profitability.
How does ‘Football Xg’ predict the outcome of a match?admin2019-06-28T16:51:42+00:00
How does ‘Football Xg’ predict the outcome of a match?
By looking at expected goals of historical matches, current form and strength of opposition and running a number of statistical scenarios, the expected net goals is calculated which is then converted into a percentage chance of winning. Once we have the percentage chance of winning, we can easily convert that to odds to see if there is value in the price. A prediction can then be made to either back or lay any given team.
The bookies have hundreds of people doing this, how can your Xg predictions be any better?admin2021-04-03T14:35:47+00:00
The bookies have hundreds of people doing this, how can your Xg predictions be any better?
You are correct that the bookies can predict the expected outcome of any match with a great amount of accuracy. The main difference is that the average punter is not always rational, so the bookies will adjust their book to where the demand is coming from rather than the actual chances of a team winning the match. That often means there is value in going against the crowd if the odds are an unfair reflection of their actual chance of winning. For example, Man U went on a good run when Solskjaer was originally appointed. The stats for their games showed they were far overachieving based on their actual chances. There was great value in laying Man U and as most people are aware, the wheels soon feel off that bandwagon.
Where to next?
Please check out the xG Predictions section which includes our calculations of the fair odds for upcoming games across all the major leagues – includes a FREE option with no registration required. This will help in the process of identifying value in the odds (the only way to be profitable long term).
Also check out the xG league tables section in the statistics section to see which teams are overperforming or underperforming versus their xG.
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xG Blog
Greetings, enthusiasts of football analytics and strategy. I am a seasoned expert in the realm of football statistics and predictive modeling, and my extensive knowledge is rooted in both theoretical understanding and practical application in the field. Allow me to delve into the intriguing world of football Expected Goals (xG) and address the frequently asked questions surrounding this cutting-edge metric.
Shots on Goal vs. xG Predictions:
In the realm of football analytics, the question often arises: "Why not simply use shots on goal as a predictive metric?" The provided article illuminates a crucial distinction between shots on goal and xG predictions. While raw shots data might suggest a straightforward superiority for Team A, xG takes into account the quality and context of each attempt. In a comprehensive analysis of 5469 games, it was revealed that shots only accurately predicted home results 54% of the time and away results 41%, significantly lower than both Shots on Target and Expected Goals.
Shots on Target vs. Expected Goals:
The article highlights the superiority of Shots on Target over total shots as a predictive measure, with Shots on Target correctly forecasting the home team winner 68% of the time and the away team 53%. Expected Goals, however, surpasses both, predicting the correct home team result 66% of the time and away results 58% of the time. This nuanced understanding emphasizes the importance of considering the quality and context of goal-scoring opportunities.
Standard Deviation and Outcome Consistency:
The discussion delves into the concept of standard deviation, emphasizing its relevance in assessing the variability of outcomes. Teams exhibit a higher standard deviation in shots on target compared to expected goals, indicating a greater spread of outcomes. Expected goals, with its lower variability, emerges as a superior tool for predicting a team's future scoring and conceding performance.
Predicting Draws with Shots and xG:
Addressing the challenge of predicting draws, the article notes that using shots on target and expected goals has a low success rate. The inherent low-scoring nature of football and the potential impact of a single lucky goal make draws difficult to accurately predict over the long term.
Football xG Prediction Methodology:
The piece provides insight into how 'Football xG' predicts match outcomes. By evaluating expected goals from historical matches, considering current form and the strength of opposition, and employing statistical scenarios, the expected net goals are calculated. This is then converted into a percentage chance of winning, offering a data-driven basis for predicting match results.
Competing with Bookmakers:
Lastly, the article addresses a common skepticism: How can 'Football xG' predictions compete with bookmakers who employ extensive teams for similar analysis? The key lies in the rationality of the average punter. While bookmakers may adjust odds based on market demand, they may deviate from the actual probabilities. 'Football xG' predictions leverage this irrationality, identifying value in odds that may not accurately reflect a team's true chances of winning.
In conclusion, 'Football xG' provides a sophisticated and data-driven approach to predicting football match outcomes, surpassing traditional metrics and offering valuable insights for enthusiasts and strategic bettors alike. To explore further, the article encourages readers to delve into xG predictions, statistics, and blog sections for a comprehensive understanding of upcoming games and team performances.
