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SønderjyskE 3 - 1 HB Køge

06.08.2022 - 11:00

Stadium : Sydbank Park

Finished

Table Corners Cards 1st Half 2nd Half Over Under Goals Clean Sheet BTTS Match Scoring / Conceding First

Over 2.5
Over 0.5
Over 1.5
Over 3.5
Over 4.5
Over 5.5

#	Team	MP	Over 2.5	Overall	Home	Away
1	FC Helsingør	32	19	59%	56%	63%
2	SønderjyskE	32	21	66%	56%	75%
3	Hobro	32	16	50%	56%	44%
4	Vejle	32	15	47%	69%	25%
5	Fremad Amager	32	21	66%	50%	81%
6	Fredericia	32	22	69%	50%	88%
7	HB Køge	32	18	56%	63%	50%
8	Vendsyssel	32	18	56%	56%	56%
9	Nykøbing	32	21	66%	75%	56%
10	Næstved	32	18	56%	63%	50%
11	Hvidovre	32	22	69%	69%	69%
12	Hillerød	32	13	41%	38%	44%

#	Team	MP	Over 0.5	Overall	Home	Away
1	FC Helsingør	32	30	94%	88%	100%
2	SønderjyskE	32	30	94%	94%	94%
3	Hobro	32	27	84%	94%	75%
4	Vejle	32	29	91%	94%	88%
5	Fremad Amager	32	30	94%	94%	94%
6	Fredericia	32	30	94%	88%	100%
7	HB Køge	32	30	94%	88%	100%
8	Vendsyssel	32	28	88%	94%	81%
9	Nykøbing	32	32	100%	100%	100%
10	Næstved	32	29	91%	94%	88%
11	Hvidovre	32	30	94%	94%	94%
12	Hillerød	32	31	97%	94%	100%

#	Team	MP	Over 1.5	Overall	Home	Away
1	FC Helsingør	32	23	72%	69%	75%
2	SønderjyskE	32	25	78%	81%	75%
3	Hobro	32	22	69%	69%	69%
4	Vejle	32	24	75%	81%	69%
5	Fremad Amager	32	22	69%	56%	81%
6	Fredericia	32	25	78%	69%	88%
7	HB Køge	32	23	72%	75%	69%
8	Vendsyssel	32	24	75%	75%	75%
9	Nykøbing	32	29	91%	100%	81%
10	Næstved	32	27	84%	94%	75%
11	Hvidovre	32	26	81%	75%	88%
12	Hillerød	32	26	81%	81%	81%

#	Team	MP	Over 1.5	Overall	Home	Away
1	FC Helsingør	32	13	41%	38%	44%
2	SønderjyskE	32	14	44%	44%	44%
3	Hobro	32	8	25%	25%	25%
4	Vejle	32	9	28%	44%	13%
5	Fremad Amager	32	11	34%	38%	31%
6	Fredericia	32	16	50%	31%	69%
7	HB Køge	32	14	44%	50%	38%
8	Vendsyssel	32	11	34%	25%	44%
9	Nykøbing	32	14	44%	50%	38%
10	Næstved	32	12	38%	44%	31%
11	Hvidovre	32	17	53%	56%	50%
12	Hillerød	32	9	28%	19%	38%

#	Team	MP	Over 1.5	Overall	Home	Away
1	FC Helsingør	32	11	34%	31%	38%
2	SønderjyskE	32	9	28%	19%	38%
3	Hobro	32	1	3%	0%	6%
4	Vejle	32	6	19%	25%	13%
5	Fremad Amager	32	9	28%	31%	25%
6	Fredericia	32	7	22%	13%	31%
7	HB Køge	32	8	25%	19%	31%
8	Vendsyssel	32	7	22%	25%	19%
9	Nykøbing	32	7	22%	38%	6%
10	Næstved	32	9	28%	38%	19%
11	Hvidovre	32	9	28%	31%	25%
12	Hillerød	32	5	16%	6%	25%

#	Team	MP	Over 1.5	Overall	Home	Away
1	FC Helsingør	32	4	13%	19%	6%
2	SønderjyskE	32	3	9%	0%	19%
3	Hobro	32	1	3%	0%	6%
4	Vejle	32	4	13%	13%	13%
5	Fremad Amager	32	4	13%	13%	13%
6	Fredericia	32	3	9%	6%	13%
7	HB Køge	32	5	16%	13%	19%
8	Vendsyssel	32	2	6%	6%	6%
9	Nykøbing	32	6	19%	31%	6%
10	Næstved	32	3	9%	6%	13%
11	Hvidovre	32	2	6%	13%	0%
12	Hillerød	32	3	9%	6%	13%

Under 2.5
Under 0.5
Under 1.5
Under 3.5
Under 4.5
Under 5.5

#	Team	MP	Over 2.5	Overall	Home	Away
1	FC Helsingør	32	13	41%	44%	38%
2	SønderjyskE	32	11	34%	44%	25%
3	Hobro	32	16	50%	44%	56%
4	Vejle	32	17	53%	31%	75%
5	Fremad Amager	32	11	34%	50%	19%
6	Fredericia	32	10	31%	50%	13%
7	HB Køge	32	14	44%	38%	50%
8	Vendsyssel	32	14	44%	44%	44%
9	Nykøbing	32	11	34%	25%	44%
10	Næstved	32	14	44%	38%	50%
11	Hvidovre	32	10	31%	31%	31%
12	Hillerød	32	19	59%	63%	56%

#	Team	MP	Over 2.5	Overall	Home	Away
1	FC Helsingør	32	2	6%	13%	0%
2	SønderjyskE	32	2	6%	6%	6%
3	Hobro	32	5	16%	6%	25%
4	Vejle	32	3	9%	6%	13%
5	Fremad Amager	32	2	6%	6%	6%
6	Fredericia	32	2	6%	13%	0%
7	HB Køge	32	2	6%	13%	0%
8	Vendsyssel	32	4	13%	6%	19%
9	Nykøbing	32	0	0%	0%	0%
10	Næstved	32	3	9%	6%	13%
11	Hvidovre	32	2	6%	6%	6%
12	Hillerød	32	1	3%	6%	0%

#	Team	MP	Over 2.5	Overall	Home	Away
1	FC Helsingør	32	9	28%	31%	25%
2	SønderjyskE	32	7	22%	19%	25%
3	Hobro	32	10	31%	31%	31%
4	Vejle	32	8	25%	19%	31%
5	Fremad Amager	32	10	31%	44%	19%
6	Fredericia	32	7	22%	31%	13%
7	HB Køge	32	9	28%	25%	31%
8	Vendsyssel	32	8	25%	25%	25%
9	Nykøbing	32	3	9%	0%	19%
10	Næstved	32	5	16%	6%	25%
11	Hvidovre	32	6	19%	25%	13%
12	Hillerød	32	6	19%	19%	19%

#	Team	MP	Over 2.5	Overall	Home	Away
1	FC Helsingør	32	19	59%	63%	56%
2	SønderjyskE	32	18	56%	56%	56%
3	Hobro	32	24	75%	75%	75%
4	Vejle	32	23	72%	56%	88%
5	Fremad Amager	32	21	66%	63%	69%
6	Fredericia	32	16	50%	69%	31%
7	HB Køge	32	18	56%	50%	63%
8	Vendsyssel	32	21	66%	75%	56%
9	Nykøbing	32	18	56%	50%	63%
10	Næstved	32	20	63%	56%	69%
11	Hvidovre	32	15	47%	44%	50%
12	Hillerød	32	23	72%	81%	63%

#	Team	MP	Over 2.5	Overall	Home	Away
1	FC Helsingør	32	21	66%	69%	63%
2	SønderjyskE	32	23	72%	81%	63%
3	Hobro	32	31	97%	100%	94%
4	Vejle	32	26	81%	75%	88%
5	Fremad Amager	32	23	72%	69%	75%
6	Fredericia	32	25	78%	88%	69%
7	HB Køge	32	24	75%	81%	69%
8	Vendsyssel	32	25	78%	75%	81%
9	Nykøbing	32	25	78%	63%	94%
10	Næstved	32	23	72%	63%	81%
11	Hvidovre	32	23	72%	69%	75%
12	Hillerød	32	27	84%	94%	75%

#	Team	MP	Over 2.5	Overall	Home	Away
1	FC Helsingør	32	28	88%	81%	94%
2	SønderjyskE	32	29	91%	100%	81%
3	Hobro	32	31	97%	100%	94%
4	Vejle	32	28	88%	88%	88%
5	Fremad Amager	32	28	88%	88%	88%
6	Fredericia	32	29	91%	94%	88%
7	HB Køge	32	27	84%	88%	81%
8	Vendsyssel	32	30	94%	94%	94%
9	Nykøbing	32	26	81%	69%	94%
10	Næstved	32	29	91%	94%	88%
11	Hvidovre	32	30	94%	88%	100%
12	Hillerød	32	29	91%	94%	88%

You can check out how often SønderjyskE and HB Køge matches in the 1st Division go over or under a certain number of goals on this page. This is a handy tool to help predict how many goals they could potentially score when they meet in their upcoming match.

Here is an example of what we mean:

78% of SønderjyskE’s matches in the 1st Division have had more than 1.5 goals scored. And when we raise the line of total goals to 2.5, then the rate of matches that go over that number is 66%.

You can also check how many times the total has gone under. In HB Køge’s case, 28% of their matches have seen under 1.5 goals scored. And in terms of matches with under 2.5 goals, the rate is 44%.

You can also see whether SønderjyskE and HB Køge matches go over or under a total number of goals when playing at home, away, or overall in 1st Division.

The over/under goal analysis for SønderjyskE vs HB Køge offers valuable insights into each club's playing styles as well as a reasonable estimation of goals we could see in the match.

However, predicting the number of goals in a match does not always go the way the math says it will. It’s important to always consider other factors as well in order to get the best chance of making an accurate prediction.

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