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HB Køge 1 - 1 Hobro

13.02.2021 - 14:00

Stadium : Capelli Sport Stadion (Køge)

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	20	63%	56%	69%
2	Silkeborg	32	19	59%	50%	69%
3	Hobro	32	18	56%	63%	50%
4	Viborg	32	20	63%	75%	50%
5	Esbjerg	32	16	50%	50%	50%
6	Fremad Amager	32	18	56%	56%	56%
7	Fredericia	32	19	59%	44%	75%
8	HB Køge	32	16	50%	56%	44%
9	Skive Women	32	19	59%	56%	63%
10	Vendsyssel	32	17	53%	44%	63%
11	Hvidovre	32	17	53%	69%	38%
12	Kolding IF	32	13	41%	44%	38%

#	Team	MP	Over 0.5	Overall	Home	Away
1	FC Helsingør	32	30	94%	94%	94%
2	Silkeborg	32	32	100%	100%	100%
3	Hobro	32	30	94%	100%	88%
4	Viborg	32	32	100%	100%	100%
5	Esbjerg	32	31	97%	94%	100%
6	Fremad Amager	32	30	94%	88%	100%
7	Fredericia	32	32	100%	100%	100%
8	HB Køge	32	30	94%	94%	94%
9	Skive Women	32	30	94%	94%	94%
10	Vendsyssel	32	31	97%	100%	94%
11	Hvidovre	32	31	97%	94%	100%
12	Kolding IF	32	29	91%	94%	88%

#	Team	MP	Over 1.5	Overall	Home	Away
1	FC Helsingør	32	25	78%	69%	88%
2	Silkeborg	32	28	88%	100%	75%
3	Hobro	32	26	81%	94%	69%
4	Viborg	32	27	84%	88%	81%
5	Esbjerg	32	25	78%	75%	81%
6	Fremad Amager	32	26	81%	69%	94%
7	Fredericia	32	26	81%	75%	88%
8	HB Køge	32	24	75%	81%	69%
9	Skive Women	32	27	84%	81%	88%
10	Vendsyssel	32	26	81%	69%	94%
11	Hvidovre	32	26	81%	88%	75%
12	Kolding IF	32	26	81%	88%	75%

#	Team	MP	Over 1.5	Overall	Home	Away
1	FC Helsingør	32	7	22%	19%	25%
2	Silkeborg	32	11	34%	31%	38%
3	Hobro	32	9	28%	31%	25%
4	Viborg	32	11	34%	56%	13%
5	Esbjerg	32	8	25%	25%	25%
6	Fremad Amager	32	9	28%	38%	19%
7	Fredericia	32	7	22%	13%	31%
8	HB Køge	32	7	22%	6%	38%
9	Skive Women	32	9	28%	38%	19%
10	Vendsyssel	32	6	19%	0%	38%
11	Hvidovre	32	7	22%	19%	25%
12	Kolding IF	32	5	16%	25%	6%

#	Team	MP	Over 1.5	Overall	Home	Away
1	FC Helsingør	32	5	16%	13%	19%
2	Silkeborg	32	8	25%	25%	25%
3	Hobro	32	3	9%	13%	6%
4	Viborg	32	3	9%	19%	0%
5	Esbjerg	32	1	3%	0%	6%
6	Fremad Amager	32	3	9%	19%	0%
7	Fredericia	32	2	6%	0%	13%
8	HB Køge	32	3	9%	6%	13%
9	Skive Women	32	2	6%	6%	6%
10	Vendsyssel	32	3	9%	0%	19%
11	Hvidovre	32	3	9%	6%	13%
12	Kolding IF	32	4	13%	19%	6%

#	Team	MP	Over 1.5	Overall	Home	Away
1	FC Helsingør	32	4	13%	13%	13%
2	Silkeborg	32	6	19%	13%	25%
3	Hobro	32	2	6%	6%	6%
4	Viborg	32	2	6%	13%	0%
5	Esbjerg	32	0	0%	0%	0%
6	Fremad Amager	32	2	6%	13%	0%
7	Fredericia	32	0	0%	0%	0%
8	HB Køge	32	1	3%	0%	6%
9	Skive Women	32	1	3%	0%	6%
10	Vendsyssel	32	1	3%	0%	6%
11	Hvidovre	32	2	6%	6%	6%
12	Kolding IF	32	3	9%	13%	6%

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	12	38%	44%	31%
2	Silkeborg	32	13	41%	50%	31%
3	Hobro	32	14	44%	38%	50%
4	Viborg	32	12	38%	25%	50%
5	Esbjerg	32	16	50%	50%	50%
6	Fremad Amager	32	14	44%	44%	44%
7	Fredericia	32	13	41%	56%	25%
8	HB Køge	32	16	50%	44%	56%
9	Skive Women	32	13	41%	44%	38%
10	Vendsyssel	32	15	47%	56%	38%
11	Hvidovre	32	15	47%	31%	63%
12	Kolding IF	32	19	59%	56%	63%

#	Team	MP	Over 2.5	Overall	Home	Away
1	FC Helsingør	32	2	6%	6%	6%
2	Silkeborg	32	0	0%	0%	0%
3	Hobro	32	2	6%	0%	13%
4	Viborg	32	0	0%	0%	0%
5	Esbjerg	32	1	3%	6%	0%
6	Fremad Amager	32	2	6%	13%	0%
7	Fredericia	32	0	0%	0%	0%
8	HB Køge	32	2	6%	6%	6%
9	Skive Women	32	2	6%	6%	6%
10	Vendsyssel	32	1	3%	0%	6%
11	Hvidovre	32	1	3%	6%	0%
12	Kolding IF	32	3	9%	6%	13%

#	Team	MP	Over 2.5	Overall	Home	Away
1	FC Helsingør	32	7	22%	31%	13%
2	Silkeborg	32	4	13%	0%	25%
3	Hobro	32	6	19%	6%	31%
4	Viborg	32	5	16%	13%	19%
5	Esbjerg	32	7	22%	25%	19%
6	Fremad Amager	32	6	19%	31%	6%
7	Fredericia	32	6	19%	25%	13%
8	HB Køge	32	8	25%	19%	31%
9	Skive Women	32	5	16%	19%	13%
10	Vendsyssel	32	6	19%	31%	6%
11	Hvidovre	32	6	19%	13%	25%
12	Kolding IF	32	6	19%	13%	25%

#	Team	MP	Over 2.5	Overall	Home	Away
1	FC Helsingør	32	25	78%	81%	75%
2	Silkeborg	32	21	66%	69%	63%
3	Hobro	32	23	72%	69%	75%
4	Viborg	32	21	66%	44%	88%
5	Esbjerg	32	24	75%	75%	75%
6	Fremad Amager	32	23	72%	63%	81%
7	Fredericia	32	25	78%	88%	69%
8	HB Køge	32	25	78%	94%	63%
9	Skive Women	32	23	72%	63%	81%
10	Vendsyssel	32	26	81%	100%	63%
11	Hvidovre	32	25	78%	81%	75%
12	Kolding IF	32	27	84%	75%	94%

#	Team	MP	Over 2.5	Overall	Home	Away
1	FC Helsingør	32	27	84%	88%	81%
2	Silkeborg	32	24	75%	75%	75%
3	Hobro	32	29	91%	88%	94%
4	Viborg	32	29	91%	81%	100%
5	Esbjerg	32	31	97%	100%	94%
6	Fremad Amager	32	29	91%	81%	100%
7	Fredericia	32	30	94%	100%	88%
8	HB Køge	32	29	91%	94%	88%
9	Skive Women	32	30	94%	94%	94%
10	Vendsyssel	32	29	91%	100%	81%
11	Hvidovre	32	29	91%	94%	88%
12	Kolding IF	32	28	88%	81%	94%

#	Team	MP	Over 2.5	Overall	Home	Away
1	FC Helsingør	32	28	88%	88%	88%
2	Silkeborg	32	26	81%	88%	75%
3	Hobro	32	30	94%	94%	94%
4	Viborg	32	30	94%	88%	100%
5	Esbjerg	32	32	100%	100%	100%
6	Fremad Amager	32	30	94%	88%	100%
7	Fredericia	32	32	100%	100%	100%
8	HB Køge	32	31	97%	100%	94%
9	Skive Women	32	31	97%	100%	94%
10	Vendsyssel	32	31	97%	100%	94%
11	Hvidovre	32	30	94%	94%	94%
12	Kolding IF	32	29	91%	88%	94%

You can check out how often HB Køge and Hobro 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:

75% 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 50%.

You can also check how many times the total has gone under. In Hobro’s case, 19% 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 HB Køge and Hobro 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 Hobro 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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