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HB Køge 3 - 0 Esbjerg

19.11.2021 - 13:00

Stadium: Capelli Sport Stadion

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	23	72%	69%	75%
2	Horsens	32	17	53%	56%	50%
3	Hobro	32	18	56%	56%	56%
4	Lyngby	32	19	59%	56%	63%
5	Esbjerg	32	20	63%	75%	50%
6	Fremad Amager	32	18	56%	56%	56%
7	Fredericia	32	22	69%	69%	69%
8	HB Køge	32	14	44%	56%	31%
9	Vendsyssel	32	14	44%	38%	50%
10	Nykøbing	32	22	69%	69%	69%
11	Hvidovre	32	16	50%	38%	63%
12	Jammerbugt	32	23	72%	69%	75%

#	Team	MP	Over 0.5	Overall	Home	Away
1	FC Helsingør	32	31	97%	100%	94%
2	Horsens	32	28	88%	88%	88%
3	Hobro	32	31	97%	100%	94%
4	Lyngby	32	30	94%	94%	94%
5	Esbjerg	32	28	88%	88%	88%
6	Fremad Amager	32	30	94%	94%	94%
7	Fredericia	32	31	97%	100%	94%
8	HB Køge	32	30	94%	94%	94%
9	Vendsyssel	32	31	97%	94%	100%
10	Nykøbing	32	32	100%	100%	100%
11	Hvidovre	32	30	94%	88%	100%
12	Jammerbugt	32	32	100%	100%	100%

#	Team	MP	Over 1.5	Overall	Home	Away
1	FC Helsingør	32	26	81%	81%	81%
2	Horsens	32	22	69%	75%	63%
3	Hobro	32	27	84%	81%	88%
4	Lyngby	32	25	78%	75%	81%
5	Esbjerg	32	25	78%	88%	69%
6	Fremad Amager	32	26	81%	75%	88%
7	Fredericia	32	27	84%	88%	81%
8	HB Køge	32	25	78%	81%	75%
9	Vendsyssel	32	25	78%	75%	81%
10	Nykøbing	32	28	88%	88%	88%
11	Hvidovre	32	22	69%	63%	75%
12	Jammerbugt	32	28	88%	88%	88%

#	Team	MP	Over 1.5	Overall	Home	Away
1	FC Helsingør	32	15	47%	38%	56%
2	Horsens	32	8	25%	25%	25%
3	Hobro	32	10	31%	25%	38%
4	Lyngby	32	8	25%	25%	25%
5	Esbjerg	32	9	28%	38%	19%
6	Fremad Amager	32	12	38%	44%	31%
7	Fredericia	32	15	47%	50%	44%
8	HB Køge	32	7	22%	19%	25%
9	Vendsyssel	32	9	28%	19%	38%
10	Nykøbing	32	14	44%	44%	44%
11	Hvidovre	32	8	25%	31%	19%
12	Jammerbugt	32	11	34%	38%	31%

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

#	Team	MP	Over 1.5	Overall	Home	Away
1	FC Helsingør	32	5	16%	6%	25%
2	Horsens	32	2	6%	13%	0%
3	Hobro	32	2	6%	6%	6%
4	Lyngby	32	3	9%	6%	13%
5	Esbjerg	32	2	6%	0%	13%
6	Fremad Amager	32	3	9%	6%	13%
7	Fredericia	32	4	13%	13%	13%
8	HB Køge	32	3	9%	13%	6%
9	Vendsyssel	32	0	0%	0%	0%
10	Nykøbing	32	3	9%	13%	6%
11	Hvidovre	32	1	3%	6%	0%
12	Jammerbugt	32	2	6%	13%	0%

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	9	28%	31%	25%
2	Horsens	32	15	47%	44%	50%
3	Hobro	32	14	44%	44%	44%
4	Lyngby	32	13	41%	44%	38%
5	Esbjerg	32	12	38%	25%	50%
6	Fremad Amager	32	14	44%	44%	44%
7	Fredericia	32	10	31%	31%	31%
8	HB Køge	32	18	56%	44%	69%
9	Vendsyssel	32	18	56%	63%	50%
10	Nykøbing	32	10	31%	31%	31%
11	Hvidovre	32	16	50%	63%	38%
12	Jammerbugt	32	9	28%	31%	25%

#	Team	MP	Over 2.5	Overall	Home	Away
1	FC Helsingør	32	1	3%	0%	6%
2	Horsens	32	4	13%	13%	13%
3	Hobro	32	1	3%	0%	6%
4	Lyngby	32	2	6%	6%	6%
5	Esbjerg	32	4	13%	13%	13%
6	Fremad Amager	32	2	6%	6%	6%
7	Fredericia	32	1	3%	0%	6%
8	HB Køge	32	2	6%	6%	6%
9	Vendsyssel	32	1	3%	6%	0%
10	Nykøbing	32	0	0%	0%	0%
11	Hvidovre	32	2	6%	13%	0%
12	Jammerbugt	32	0	0%	0%	0%

#	Team	MP	Over 2.5	Overall	Home	Away
1	FC Helsingør	32	6	19%	19%	19%
2	Horsens	32	10	31%	25%	38%
3	Hobro	32	5	16%	19%	13%
4	Lyngby	32	7	22%	25%	19%
5	Esbjerg	32	7	22%	13%	31%
6	Fremad Amager	32	6	19%	25%	13%
7	Fredericia	32	5	16%	13%	19%
8	HB Køge	32	7	22%	19%	25%
9	Vendsyssel	32	7	22%	25%	19%
10	Nykøbing	32	4	13%	13%	13%
11	Hvidovre	32	10	31%	38%	25%
12	Jammerbugt	32	4	13%	13%	13%

#	Team	MP	Over 2.5	Overall	Home	Away
1	FC Helsingør	32	17	53%	63%	44%
2	Horsens	32	24	75%	75%	75%
3	Hobro	32	22	69%	75%	63%
4	Lyngby	32	24	75%	75%	75%
5	Esbjerg	32	23	72%	63%	81%
6	Fremad Amager	32	20	63%	56%	69%
7	Fredericia	32	17	53%	50%	56%
8	HB Køge	32	25	78%	81%	75%
9	Vendsyssel	32	23	72%	81%	63%
10	Nykøbing	32	18	56%	56%	56%
11	Hvidovre	32	24	75%	69%	81%
12	Jammerbugt	32	21	66%	63%	69%

#	Team	MP	Over 2.5	Overall	Home	Away
1	FC Helsingør	32	24	75%	81%	69%
2	Horsens	32	26	81%	81%	81%
3	Hobro	32	27	84%	81%	88%
4	Lyngby	32	26	81%	81%	81%
5	Esbjerg	32	28	88%	94%	81%
6	Fremad Amager	32	21	66%	63%	69%
7	Fredericia	32	25	78%	81%	75%
8	HB Køge	32	28	88%	88%	88%
9	Vendsyssel	32	28	88%	88%	88%
10	Nykøbing	32	21	66%	69%	63%
11	Hvidovre	32	29	91%	88%	94%
12	Jammerbugt	32	23	72%	63%	81%

#	Team	MP	Over 2.5	Overall	Home	Away
1	FC Helsingør	32	27	84%	94%	75%
2	Horsens	32	30	94%	88%	100%
3	Hobro	32	30	94%	94%	94%
4	Lyngby	32	29	91%	94%	88%
5	Esbjerg	32	30	94%	100%	88%
6	Fremad Amager	32	29	91%	94%	88%
7	Fredericia	32	28	88%	88%	88%
8	HB Køge	32	29	91%	88%	94%
9	Vendsyssel	32	32	100%	100%	100%
10	Nykøbing	32	29	91%	88%	94%
11	Hvidovre	32	31	97%	94%	100%
12	Jammerbugt	32	30	94%	88%	100%

You can check out how often HB Køge and Esbjerg 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 HB Køge’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 44%.

You can also check how many times the total has gone under. In Esbjerg’s case, 22% of their matches have seen under 1.5 goals scored. And in terms of matches with under 2.5 goals, the rate is 38%.

You can also see whether HB Køge and Esbjerg 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 HB Køge vs Esbjerg 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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