Quantitative football has been around for over a decade, and the data is very stable! Football data includes historical records, recent records, player injuries, referee and coach situations, stadium and weather conditions, odds data, etc. It is quantified as the degree of visual impact, denoted as "L", "M", "H". We don't need to worry too much about the numerical value of this quantitative impact, we just need to know that 'L' is the most noteworthy.
There are two types of attributes after quantification. The first is the comprehensive influence of the host and guest, with only two subdivisions: "L-H" and "H-L"; The second type is the impact on the results of "home", "draw", "away", "half home", "half draw", and "half away" result, which are divided into ten sub categories: "LH -", "MH -", "HH -", "LM -", "HM -", "- MH", "- ML", "- HH", "- HM", and "- HL".
Obviously, you will find that the first type focuses directly on the influence of "home and away", weakening the draw. The five sub categories of "LH -", "MH -", "HH -", "LM -", and "HM -" in the second type of attribute focus on "home and draw", weakening the away. At the same time, the five sub categories of "- MH", "- ML", "- HH", "- HM", and "- HL" focus on "draw and away", weakening the home.
Not all matches have available quantitative attributes, some have the first type of quantitative attribute, some only have the second type of attribute, and some matches have both types of attributes. This is the entry point of our analysis, it's like solving a math problem, interesting and fun.
Example 1: full-time home-draw-away prediction. Here is just one method to figure out. You can find a lot of methods if you'd like to.
home-away comprehensive impact: H-L
home -ML -HM
draw HH- HM-
away HH- HM-
h_draw HH- HM- -HM
h_away HH- HM- -HM
******** ['2025-09-28 20:00', 'SWE D1', 'Brommapojkarna', 'Mjallby AIF'] ['3.4', '3.5', '2.01'] HT/FT score , '0-0', '0-1'
home-away comprehensive impact: L-H
home -MH -HM
draw LH- MH- HH-
away MH- HH-
******** ['2025-09-28 20:00', 'SWE D1', 'Halmstads', 'Hammarby'] ['5.25', '4.2', '1.57'], HT/FT score, '0-0', '1-0'
home-away comprehensive impact: H-L
home -HM -HL
draw MH- HH-
away MH- HH-
******** ['2025-9-30 22:30', 'BUL D1', 'Botev Plovdiv', 'Levski Sofia'] ['5.5', '3.8', '1.56'], HT/FT score, '0-0', '0-1'
In these three games, the home draw and away were all special performances, each only affected by half of the factors, which can be called "break", and their "L" was only one. The direction of the "L" represents the result, and that is awesome.
example 2:half-time home-draw-away prediction. Here is just one method to figure out. You can find a lot of methods if you'd like to.
home-away comprehensive impact: H-L
home HH- -HL
away -HH -HL
h_home HH- -HL
h_draw -HH -HL
******** ['2025-09-25 08:00', 'MEX D1a', 'CDSyC Cruz Azul', 'Queretaro FC'] ['1.25', '6.5', '10'] HT/FT score , '1-2', '2-2'
In this MEX D1a match, both away and half_draw were special, as they were only affected by half of the factors, namely "break". Such situations are usually half_away, and the extremely high odds were very exciting. There are a lot of similar questions in the "History archive" section, so I won't list them one by one.
Example 1: over/under 2.5 prediction. Here is just one method to figure out. You can find a lot of methods if you'd like to.
home MH- -HH -HM -HL
away LH- -HH
h_home -HH -HL
h_draw MH- HH- -HH
******** ['2025-10-05 20:00', 'SWE D1', 'AIK Solna', 'IFK Varnamo'] ['1.42', '4.75', '6.5'] HT/FT score , '0-3', '2-3'
home-away comprehensive impact: L-H
home LH- MH- HH- -HH -HL
away MH- -HH
h_home MH- -HH -HL
h_draw LH- MH- HH- -HH -HM
h_away MH- -HH
******** ['2025-10-05 23:00', 'GRE D1', 'Levadiakos', 'Panaitolikos Agrinio'] ['1.66', '3.6', '5.5'] HT/FT score , '4-0', '6-0'
In these two games, we can clearly see that there are no four subdivisions in the middle, that is, there are no "LM-", "HM-", "-MH", and "-ML". Combined with the odds, we can see that the first odd is very low. Such situations usually indicate big balls, and there is a high probability that the first odd will not come out!
Example 4: The Ultimate Strategy!!!!!! If you don't want to spend too much time on various football math problems,
then this method is definitely for you. It simply combines the "home-away comprehensive impact"
and the distribution of ten sub-divisions to predict the outcome. Let's look at examples:
home-away comprehensive impact: H-L
home HM- -MH -ML
draw HM- -MH -ML
away HM- -MH
h_home HM- -MH -ML
h_draw HM- -ML
h_away HM- -ML
******** ['2025-10-07 01:00', 'DEN D1', 'Hvidovre IF', 'Lyngby'] ['3.3', '3.3', '2.1'] HT/FT score , '2-1', '2-2'
home-away comprehensive impact: H-L
home LM- HM- -MH -ML
draw HM- -MH -ML
away LM- HM- -ML
h_home LM- HM- -MH -ML
h_draw LM- HM- -MH -ML
h_away HM- -MH -ML
******** ['2025-10-08 08:30', 'COL D1C', 'Millonarios', 'America de Cali'] ['2.15', '2.9', '3.3'] HT/FT score , '0-0', '2-1'
home-away comprehensive impact: L-H
home LM- HM- -MH -ML
draw HM- -MH
away LM- HM- -MH
h_home LM- HM- -MH
h_draw LM- HM- -MH -ML
h_away HM- -MH -ML
******** ['2025-10-09 00:00', 'WCPAF', 'Comoros(中)', 'Madagascar'] ['2.35', '3', '3.4'] HT/FT score , '0-1', '1-2'
These three games only have four sub-divisions: "LM-," "HM-," "-MH," and "-ML." In this case,
the "H" side, based on the "home-away comprehensive impact", will determine the outcome,
meaning the "L" side won't be able to play. These situations occur every day and are perfect
for those of you who use a football sweep strategy.
The problem-solving process is full of surprises, and I hope you have a pleasant time! have fun!Due to the need to organize a large amount of data, the time will be relatively late. The data is updated daily 18:00-24:00 (UTC+8).
