I call this the “Elite No Team Data Football Calculator” because there is no team data involved.  It is purely based on mathematics. This calculator can be used for any match, including league games, cup games, internationals, and friendlies.

I created this calculator for cup matches and Champions League matches.  However, it can be used for any match.

INSTRUCTIONS

1.  Go to Betfair and look at any match. 

2.  Input the Betfair match odds and the 0-0 odds into the calculator. 

The calculator will generate odds for current score, over/under and both teams to score (BTTS) markets.

At the bottom of the screen, you will The calculator will also provide you with a graph and implied XGs (expected goals) for each team.

The First Half Tab

When you put all 5 odds into the calculator, a new tab (labelled “First Half”) will appear at the top of the calculator. If you click on this tab, you will see the odds for the first half.  

You will see that the odds for both the full-time and the first-half are very accurate when compared to the Betfair odds.

The Half-Time Tab

This is where I find value.

At half-time, the odds will differ more from the Betfair odds.  In-play odds are known to be inefficient compared to pre-match odds (eg Angelini et al., 2021).

The calculator allows to you select 4 half-time scores - 0-0, 1-0, 0-1 and 1-1.

The calculator is likely to be most accurate for the 0-0 and 1-1 score.  You need to be more careful when considering the one-goal scorelines.  The calculations are based on implied XGs.  This means that the calculations are based on goals.

When a team is one goal up or one goal down, it might change its strategy.  For example, underdogs can sometimes play defensively when they go one goal up.  The calculator can't pick up on such strategic changes.

Similarly, if a strong players gets injured and has to be substituted, the calculator won't know about that.

For this reason, you have to use some judgement.  

You have the option of adjusting the XGs by clicking on the "+" and "-" signs on the stepper under the XGs.  Each step represents a percentage.  Therefore, if you change the stepper number from 0 to 1, it will increase the XG by 1%.  If you change the stepper to -1, it will reduce the XG by 1%.

WHY BETFAIR ODDS COULD BE WRONG AT HALF-TIME

An in-depth study by Klemp et al. 2021 indicated that:

1. In-play stats from the first half do not influence the result of the second half  
2. Pre-match odds are the best indicator of how the second half will play out

Note that all the odds generated by the calculator are based on pre-match odds!

HALF-TIME STRATEGIES

So, punters and traders usually bet based on in-play stats.  By doing this, they drive the market into inefficiency.   This provides an opportunity to find value!

The calculator can be used for various strategies, including:

1. Lay the draw at HT
2. Lay or back the favourite
3. Lay 0-0
4. Back or Lay the Over/Under Goal Markets

Basically, I look for value by comparing the calculator's odds with Betfair's odds. 

For example, I just won a small bet in a match between HJK Helsinki v Silkeborg.  These were 2 teams that I knew nothing about.  

The score was 0-0 at half-time.

At half-time, the calculator gave odds of 1.31 for Over 0.5 goals.  The Betfair odds were 1.41 for Over 0.5 goals.

I bet on Over 0.5 goals and won the bet.

As long as the calculator tells me that I'm getting value, I am happy to bet.

References

Angelini, Giovanni & De Angelis, Luca & Singleton, Carl. (2022). Informational efficiency and behaviour within in-play prediction markets. International Journal of Forecasting. 38. 282-299. 10.1016/j.ijforecast.2021.05.012. 

Badiella, Llorenç & Puig, Pedro & Peñas, Carlos & Casals, Martí. (2022). Influence of Red and Yellow cards on team performance in elite soccer. Annals of Operations Research. 10.1007/s10479-022-04733-0. 

Choi, Darwin & Hui, Sam. (2012). The Role of Surprise: Understanding Overreaction and Underreaction to Unanticipated Events using In-Play Soccer Betting Market. Journal of Economic Behavior & Organization. 107. 10.2139/ssrn.2011564.

Klemp, M., Wunderlich, F. & Memmert, D. In-play forecasting in football using event and positional data. Sci Rep 11, 24139 (2021). https://doi.org/10.1038/s41598-021-03157-3