Rowdie: Mathematical football prediction and betting tips

How to create sports betting model and odds

I read many articles about how the sports betting models and odds are being created, but most of them are just a click bait full of bullshit or a scam.

Let us at Rowdie guide you through the whole process how to bet learning process step by step. We are about to present a formula for creating the sports betting odds and at the end there will come out some concrete numbers!

We are even providing you the betting odds calculator – a tool that will spit out the odds of the 1 X 2 results as well as the odds for exact score. Another free betting tool we provide is the value bet calculator, that tells you how much you earn in the long term if you are precise in odds creating.

The biggest challenge for creating of odds is to distinguish between the relevant statistics and the “noise”.

Please look at the table presenting our point of view on the relevance of the facts and statistics on the end result.

Type of Statistics Relevance
Playing Home/Away Medium/High
Injuries Medium
Ball Possession % Low/Medium
Shots on target Medium
Shots Low/Medium
Touches Low
Passes Low
Corners Low
Scored Goals Home High
Scored Goals Away High
Received Goals Home High
Received Goals Away High
Scored Goals Total Medium/High
Received Goals Total Medium/High
Head to Head High

Creating sports betting odds – Real example

Please look at the following analysis I was doing for the top game. As the Premier League season 2018/2019 run towards the end, there were only 2 possible winners. Only 5 games left to play, the title could go to Liverpool or the Citizens. Here is the Premier League table before the match

It is obvious that Manchester City needs to win to keep up in the battle for the title. Manchester City won 9 games in a row and are rocking the scene.

Now let us look at the pre match odds of the major bookmakers and dig deeper into the arguments.

Bookie 1 X 2 Payout
Bet365 1.3 6.00 11.00 97,4%
Betfred 1.28 6.50 11.00 98,0%
WH 1.27 6.00 11.00 95,7%
Pinnacle 1.29 6.44 10.31 97.3

First we consider the following arguments connected with the motivations

  1. There is not to be denied that Manchester City wants to win the PL title. They need the victory. Nothing else is an option here.
  2. Top 4 positions in the Premier League give you the UEFA ticket. There are still 15 points to play for and Spurs can not afford to give a point away.

This is EPL and not any Eastern European league, where it would be “not nice” to mess up the title run. How would the players who earn millions explain it to trainers, managers and fans? Spurs will fight!

What does the math and statistics say about the chances?

Now let’s forget about the “should” and look at the Team statistics.

Head to Head statistics of both teams

Head to head statistics of both teams reveal a lot. We go as far as 2 years back.

Date Round Tournament
17/04/19 QF Man City 4:3 Tottenham UEFA Champions League, Knockout stage
09/04/19 QF Tottenham 1:0 Man City UEFA Champions League, Knockout stage
29/10/18 10 Tottenham 0:1 Man City Premier League
14/04/18 34 Tottenham 1:3 Man City Premier League
16/12/17 18 Man City 4:1 Tottenham Premier League
30/07/17 Man City 3:0 Tottenham International Champions Cup
21/01/17 22 Man City 2:2 Tottenham Premier League

Summary Table

Manchester City Tottenham
Won 5 1
Lost 1 5
Draw 1 1
Won in Manchester 3 0
Lost in Manchester 0 3
Draws in Manchester 1 1
Goals Total 17 8
Goals in Manchester Stadium 13 6
Ball possession last match in Man. 64% 36%
Ball possession Dec. 2017 in Man. 52,9% 47,1%

Some more questions and answers:

Q. How relevant is the fact that Manchester City plays at home?

A. We believe the relevance is huge since the goal potential of Manchester City is more than double (13:6) and Spurs were not able to win in Manchester since February 2016

Q. How relevant is the fact that Tottenham sent Manchester home from the Knockout phase of UEFA Champions League?

A. We believe the impact is average, since Spurs were able to score 3 goals in the Home stadium of Manchester, but had only 36% ball possession.

Q. A week ago the teams played in UEFA league and Spurs won. Is it relevant?

A. UEFA League is different to Premier League. The teams are the same, but performance tends to be different.

Now let us put this into numbers. We should not forget it is all about probability and asking the right question.

The question is:

What is the chance of scoring for both teams during the match through the period of 90 minutes? The count of goals defines the end result, right?

We made a decision to base our football prediction model on the results of the goals scored on a stadium of Manchester since the Home team advantage is significant.

We can split the goal score into probability. In the last 4 matches the score on the field of Manchester was 13:6. This was an average 3,25 goals scored by Manchester City and only 1,5 goals scored by the Tottenham Spurs.

Let us convert it:

  • Man City needs on average 27 minutes and 41 seconds to score a goal against Spurs when playing Home.
  • Spurs need in average 60 minutes to score a goal against Manchester City in their home stadium.

The possible results are:

Spurs Spurs Spurs Spurs Spurs Spurs
Man 0:0 0:1 0:2 0:3 0:4 0:5
Man 1:0 1:1 1:2 1:3 1:4 1:5
Man 2:0 2:1 2:2 2:3 2:4 2:5
Man 3:0 3:1 3:2 3:3 3:4 3:5
Man 4:0 4:1 4:2 4:3 4:4 4:5
Man 5:0 5:1 5:2 5:3 5:4 5:5

Probability Manchester wins = P(1:0) + P(2:0) + P(3:0) + P(4:0) + P(5:0) + P(5:1) + P(5:2) + P(5:3) + P(5:4) + P(3:2) + P(3:1) + P(4:1) + P(4:2) + P(4:3) + etc.

Probability Draw =  P(0:0) + P(1:1) + P(2:2) + P(3:3) + P(4:4) + P(5:5) + …

Probability Spurs win = the sum of probabilities of results above the draw line

For odds-creating we used our simple odds calculator. See exact score probabilities and odds in the following tables:

Spurs Spurs Spurs Spurs Spurs Spurs
Man 0.0087 0.0130 0.0097 0.0049 0.0018 0.0005
Man 0.0281 0.0422 0.0316 0.0158 0.0059 0.0018
Man 0.0457 0.0685 0.0514 0.0257 0.0096 0.0029
Man 0.0495 0.0742 0.0557 0.0278 0.0104 0.0031
Man 0.0402 0.0603 0.0452 0.0226 0.0085 0.0025
Man 0.0261 0.0392 0.0294 0.0147 0.0055 0.0017

In percentage the probabilities look like this

Spurs Spurs Spurs Spurs Spurs Spurs
Man 0.87% 1.30% 0.97% 0.49% 0.18% 0.05%
Man 2.81% 4.22% 3.16% 1.58% 0.59% 0.18%
Man 4.57% 6.85% 5.14% 2.57% 0.96% 0.29%
Man 4.95% 7.42% 5.57% 2.78% 1.04% 0.31%
Man 4.02% 6.03% 4.52% 2.26% 0.85% 0.25%
Man 2.61% 3.92% 2.94% 1.47% 0.55% 0.17%

The probabilities and odds are as following:

1 X 2 Σ
Prob. 0.72 0.14 0.14 1.00
Odds 1.39 7.12 6.98

Now we are all set to compare our results with the odds provided by bookmakers

1 X 2 Payout
Bet365 1.3 6 11 97,4%
Our odds 1.39 7.12 6.98 100%

We clearly see the possibility for a value bet! It looks like the amount of stakes towards the home win and a draw are pushing the bookies to increase the Away win. As I wrote in the odds and value case study, there are some limits I set for the value bet. I never go for odds higher than 7 and value lower than 4%. The odds 6.98 in the analyzed match is questionable, but the calculated value 57,6% seems convincing. Now the question is. Do I go for the value? Do I trust my analysis?  Are today’s football predictions reliable or not?

 

How do we know the football prediction model is accurate?

This is really a significant question. You can build a model and be happy about how great it looks, but is it going to make money?

The hard way to test your model is to take the historical data and verify it. You can take the last season of any league and apply the data! This is however a time consuming approach, since you would have to do the statistical test at least 385 times. Using the odds creator, you simply have to be in the sports betting business for quite some time. So how do you know? After betting 20 games. Did you make money or did you lose it? Let the money be the final judge.

You and the bookies

Bookies have prediction models and keep testing and improving them. You can get crazy with difficult statistical methods or use can use common sense or the logic we presented. What is statistics without a judgement?

We are also using some sophisticated football prediction models that show a great performance, but do they come with a better result than your brain power?

Do not be scared if your model is as simple as an goal average. There is no guarantee that the prediction model based on average goal number presented above is worse than the complicated stuff. There is no guarantee that going back 5 seasons will give you more valid data than going back 3 games…

Remember bookmakers make money anyways on most of the matches by redistributing the deposits between the results in the right ratio. Just make sure they do not make money on you. Insider tip: We are really good at Serie A football predictions, with an above average performance.

 

How to analyse the statistics when sports betting and creating our own odds. Easy step by step guide

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