Many of you may have seen the movie (or read the book) Moneyball. The story charts Oakland A’s general manager Billy Beane’s attempt to put together a baseball club on a budget by employing computer-generated analysis, getting the most out of what were considered to be very average players.
Can we transfer the idea of computer-generated analysis to our betting decisions?
There are a few hundred betting websites, and many of them will have thousands of clients. Everyone wants to be a winner and so people will tend to subscribe to the tipsters that they perceive to be the best.
The media industry has also caught up with the idea that people want to “know more, enjoy more, and share more” in terms of their betting experience and bookmakers have been advised that their target audience is open to what I describe as “bet stimulation”. The online in-running betting market has increased in volume dramatically since a company called Bettorlogic started to supply data to the industry.
Here is an example for the Norwich v Wigan game.
As the data flashes up during a game it stimulates our brains to “trigger” a bet as we become confident that we have information that will give us an edge.
Bookmakers have gone even further by having actors appear at half-time advising you to consider backing the 1-3 scoreline in a game at 14/1. In one particular game I checked the probability of Real Madrid winning 3-1 as they were 1-0 up away at HT and I discovered that Real Madrid and Barcelona had only won once each away FT 3-1 when winning away at HT 1-0 in the last 4 seasons.
The bookmakers are using data to give them an edge over the punter by providing really poor value “trigger” bets.
The next thing to look at is random behavior. If I put £10 on black and win, and then put £10 on black again, my chance of winning has no relationship with my previous bet. This is in fact what happens to many people when they bet. The strategy of joining trends and leaving them as a bet loses and then backing Liverpool because they do not lose on a Friday will lead to long term losses unless you are the lucky chap who recently won £180 000 for predicting 4 correct scores with an initial stake of £11
Bookmakers have an edge so is it possible for us to have an edge?
Let us look at Man Utd and their shots on target data at home. Do you think it will be consistent or inconsistent depending on the type of team they are up against.
As I write I am opening up my database and I can see this season that the number reads 7 5 7 7 7 6 7 7 and I welcome you to check who the away teams were. This is certainly not a random event.
In every game this season at home Man Utd have had between 5-7 shots on target, which is a very narrow range. However, goals to shots-on-target ratios are not consistent and vary game to game.
We can, though, look at the shots-on-target data, much like the general manager in Moneyball, to see any patterns forming that will define what we are looking for: expectation of a goal.
Have a look at Fulham v Norwich and we see that there was a cluster of shots on target before the first Fulham goal.
Of course, not all games will fit that cluster pattern.
This is where Liverpool had 9 shots on target but failed to score, which does happen but not very often.
Again there are teams that dominate the game in terms of initial shots-on-target data and still lose.
This is a good example which is Everton at Reading. Everton dominated the game and lost 2-1
People find it very easy to change their momentum process when watching a game and this is a great example from Swansea v Liverpool on Skysports commentary:
- Liverpool are now the team pressing for a late goal, but are unable to create a noteworthy chance.
- 89′ - Swansea look the most likely to grab a late winner at the moment but Liverpool can catch a break as they win a throw in inside Swansea’s half.
What can we do?
So what can we do to find an edge to give the bookmakers a run for our hard cash?
- Look at the strength of a shot, for example:39′ Chelsea win a free-kick in a dangerous position. Luiz takes it but it is a poor effort and straight at Hart with little pace on it.
- This is not going to be a likely goal so use a site like EPLIndex’s Stats Centre (shots at goal area graphic available) if you do not have pictures to see where the shots are being taken from. I went to an OPTA seminar last week which showed an excellent graphic of where the goals are scored from and the simple comment is that not many are scored from outside the box so just looking at where QPR shoot from will show you instantly that they have struggled to score as they are shooting from too far out. Harry has already stopped that and they were certainly much better in the final third at Wigan.
- Download the 4 4 2 StatsZone App which I think is free now and track a game in running. How good is the team that you are watching in the first 30 minutes of a game?
- Download the data from Football Data UK on to a spreadsheet to see what is the profile of 0-0 in the Premiership in terms of the average shots on target. A word of warning is that the site uses press association data for shots and shots on target so I manually change it back to an OPTA source like EPLIndex.
- Opening up my spreadsheet I can see that there are fourteen 0-0′s in the Premiership this season and the average shot on target for the home team is 2.85 and for the away team the average is 3.07 which has been pushed up by Liverpool having 9 shots on target at Swansea and not scoring.
- Look at historical trends such as 1-0 HT which I discussed in a previous article. If Newcastle have not won away when losing at HT 1-0 since they beat Sunderland in 2005, 4-1, then there is little point in thinking that at 1-1 Last week at Fulham (1-0) that they could win the game. If you had also noted the lack of draws when Newcastle have been down 1-0 HT then this should have “triggered” a bet and it would not be back Newcastle.
- See if you can predict expectation of goals. I was looking at the Norwich game at Swansea the shot on target data and suspected that Norwich would score very soon, which they did 60 seconds later.
This is not the best way to profit if you do find that you can predict goal expectation.
A) back in the goal market
b) lay the correct score as time decays.
Say Liverpool in real time at Swansea have had 6 shots on target after 80 minutes. You check your spreadsheet and see the average 0-0 is far lower then that so you trigger a LAY bet of the correct score ie 0-0 in anticipation of the goal which in this case did not arrive but there are a greater number of games where the goal will arrive.
Some of you may be aware that more goals are scored 90-FT then any other time band so without worrying who is going to score by backing a goal you have both teams playing for you as the game is near the end.
The same is true in reverse which is if the game is quiet there is expectation of a lack of goals but I am not a fan of this idea as I have seen quiet games that have exploded resulting in floods of goals.
You need to also look at accuracy prevention which is the ability of a team to stop the other team turning shots into shots on target which Stoke are past masters of.
At Villa last week , Villa had 13 shots and just two shots on target so the Stoke accuracy prevention ratio was 11/13 which is a massive 0.84 which is no wonder Villa fired a blank, FT 0-0.
I leave you with a breakdown of the EPL using time bands 0-30 31 -60 and 61-FT and you are welcome to change them for your strategy and a shot on target table.
In conclusion, betting can be random and bookmakers are using techniques to stimulate “random bets”, but I argue that football is predictable, and that if you look hard you may find some interesting patterns and historical trends.
Shot on target does not include the woodwork or blocks.
SOT = Shots on Target
GLS = Goals
|Team / Stats||SOT 0-30||SOT 31-60||SOT 61-FT||GLS 0-30||GLS 31-60||GLS 61-FT|
Images taken from the Excellent FourFourTwo StatsZone app
All of the stats from this article have been taken from the Opta Stats Centre at EPLIndex.com – Subscribe Now (Includes author privileges!) Check out our new Top Stats feature on the Stats Centre which allows you to compare all players in the league & read about new additions to the stats centre.
- Good Read
Categories: Arsenal (NN), Aston Villa, Betting Tips, Chelsea, EPL Index Featured Article, EPL Index Statistical Comparisons, Everton, Fulham, Liverpool, Manchester City, Manchester Utd, Newcastle Utd, Norwich City, QPR, Reading, Southampton, Stoke City, Sunderland, Swansea City, Tottenham Hotspur, West Bromwich Albion, West Ham United, Wigan
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