Betting Tips | Trading a game | How long can your team...

Betting Tips | Trading a game | How long can your team hold the lead?

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In this post I am going to explore the average time it takes a Premier League team to fight back from a goal down, comparing this to the average time that a Premier League team tends to hang on to a lead.

Firstly, I’ll set out the parameters that I used in assessing these statistics:

  1. In order to make this research as topical as possible, I chose to use data from this season. You are welcome to check the corresponding data from past seasons. While the sample size may be too small for some purposes, in this study I am aiming to predict a trend that is forming. For that reason, I chose to ignore data from previous seasons, as teams change and strategy changes.
  2. In order to make all samples equal, have not included minutes added to either half of a game.
  3. For a game to be included in the sample,
    a) both teams must score, one must take the lead, the other must equalise. For example, 0-1 becomes 1-1, 3-2 becomes 3-3, and so on.
    b) if a team scores to take the lead and then scores a second goal (taking a two-goal lead), I have not utilised this data.

In essence, I am interested to see how long it takes a team to “fight back”, to equalize in the game, and how long a team can hold on to maintain a lead (“survival”).

The T shows the time of the goal that breaks the deadlock (the goal to take the lead) and the time of the goal that results in the “fight back” (ties the score) (T+1).

The equation T+1-T, then, gives us the total time that it takes to tie the game again. T average is the average amount of time it takes to tie the game in all applicable games this season.

We can see that Aston Villa have the best survival rate at 37.33 minutes and Norwich the worst at 5.5 minutes.

Arsenal, Manchester Utd, and Swansea do not have a T average as  this season thus far ,  none of the games that these teams have played have involved them relinquishing a lead in the conditions that I have identified above.

From a trading point of view, this survival analysis can be used to your advantage.

Let us look at three games which will make it easy to understand the point. Hypothetically, let’s say that Southampton are 1-0 up against Swansea after 64′ minutes. In this instance, you might look at the T average of Southampton: 25.4. As Southampton have scored first, the data suggests that on previous occasions the opposition team should score (on average) somewhere around 25 minutes later. You might, then, place a bet forecasting the equaliser as soon as Southampton score , anticipating that they will hold the lead for around 25 minutes. All you do is ‘lay’ Southampton at 1-0. ‘Lay’ means to take the view that Southampton will not win the game.

Should the anticipated goal (Swansea’s) be scored then you back Southampton to win, since the price will now be bigger, so you cannot lose should the “fight back” occur. In this case Swansea score T+ 9 minutes, well within expectation of a goal by Swansea. If Swansea do not score then your bet is lost.

If we look at Everton vs Sunderland, we see that Sunderland scored after 45 minutes, so T is 45. If I look at the Sunderland T average I see that it stands at 37.25, which is  higher by comparison to the rest of the Premiership where the T average of all the teams is 25.  I can back Sunderland after 45 minutes and close my position during the second half by laying at a shorter price as time decays.

It is up to you how long you will wait. The longer you wait the more profit you can lock in but there is also the danger of a goal by Everton before you close your position. In this game Everton scored on 77 minutes (T+32, which is very close to the average for Sunderland).

Let’s take the Villa vs Man Utd Game. Villa have a T average of 37.33, which is the highest in the Premiership. When Villa score on 45 minutes you simply back Villa to win, calculating that if Man Utd score then it will not be until some time into the second half. When Villa scored on 50 minutes you would have been rewarded, as the price of Villa to win is much shorter than when you backed on 45 minutes at 1-0. In this case, all you would do is lay (back against Villa) and close your position and lock in a profit. You no longer care care what the final score is as you win whatever the outcome. In essence, you back the team that scores first when they have a high T average and then trade out during the game and lay (back against) a team when they have a low T Average as soon as they score.

Imagine that you lay (back against) Southampton and the goal is not scored within their T average. You can close your position, reducing your loss by backing Southampton at a shorter price. If you bet £10 and leave it and the bet loses then you lose £10. If you lay (back against) Southampton to a fixed liability of £10, backing Southampton a few minutes later if the score still stands at 1-0, then you will reduce your loss.

The majority of people think of betting as having a flutter on, say, Liverpool before a game, but there is really no advantage doing that. You can gain advantage by trading during a game, which means opening and closing positions, a model of trading the stock market.

Very few people back the draw and the bookmakers love that because they are aware of the “fight back” data.

This season the most common Full-time score is 1-1 at 16.16% so it’s no surprise to see why 1-1 is priced so low every week in your local bookmaker’s. 2-2 comes in third at 10%. This is possibly trend forming, and maybe we should be backing some 2-2 correct scores. Or will the 2-2 revert back to the mean (ie will there be fewer such scorelines as the season progresses)?

Last season 2-2 was just 3.68% and 1-1 was top with 11.84%

In conclusion, I hope that I have got you to think about your betting, and to see that trading can be a much smarter alternative.

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