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Fredericia 1 - 1 HB Køge

06.06.2015 - 14:00

Stadium : Monjasa 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	AGF	33	19	58%	47%	69%
2	Horsens	33	17	52%	53%	50%
3	Lyngby	33	14	42%	53%	31%
4	Viborg	33	9	27%	24%	31%
5	Vejle	33	16	48%	56%	41%
6	Fredericia	33	11	33%	31%	35%
7	HB Køge	33	9	27%	35%	19%
8	Skive Women	33	14	42%	25%	59%
9	Vendsyssel	33	12	36%	44%	29%
10	Roskilde Women	33	11	33%	31%	35%
11	AB Women	33	16	48%	44%	53%
12	Brønshøj Women	33	12	36%	41%	31%

#	Team	MP	Over 0.5	Overall	Home	Away
1	AGF	33	30	91%	88%	94%
2	Horsens	33	32	97%	94%	100%
3	Lyngby	33	29	88%	88%	88%
4	Viborg	33	29	88%	88%	88%
5	Vejle	33	31	94%	100%	88%
6	Fredericia	33	27	82%	81%	82%
7	HB Køge	33	28	85%	82%	88%
8	Skive Women	33	29	88%	94%	82%
9	Vendsyssel	33	28	85%	81%	88%
10	Roskilde Women	33	31	94%	88%	100%
11	AB Women	33	31	94%	94%	94%
12	Brønshøj Women	33	27	82%	88%	75%

#	Team	MP	Over 1.5	Overall	Home	Away
1	AGF	33	25	76%	65%	88%
2	Horsens	33	27	82%	76%	88%
3	Lyngby	33	24	73%	76%	69%
4	Viborg	33	23	70%	82%	56%
5	Vejle	33	27	82%	88%	76%
6	Fredericia	33	23	70%	75%	65%
7	HB Køge	33	21	64%	59%	69%
8	Skive Women	33	25	76%	75%	76%
9	Vendsyssel	33	20	61%	56%	65%
10	Roskilde Women	33	23	70%	63%	76%
11	AB Women	33	24	73%	81%	65%
12	Brønshøj Women	33	22	67%	65%	69%

#	Team	MP	Over 1.5	Overall	Home	Away
1	AGF	33	10	30%	35%	25%
2	Horsens	33	7	21%	29%	13%
3	Lyngby	33	7	21%	29%	13%
4	Viborg	33	3	9%	12%	6%
5	Vejle	33	11	33%	38%	29%
6	Fredericia	33	5	15%	6%	24%
7	HB Køge	33	5	15%	18%	13%
8	Skive Women	33	6	18%	13%	24%
9	Vendsyssel	33	4	12%	6%	18%
10	Roskilde Women	33	7	21%	19%	24%
11	AB Women	33	10	30%	25%	35%
12	Brønshøj Women	33	5	15%	12%	19%

#	Team	MP	Over 1.5	Overall	Home	Away
1	AGF	33	4	12%	12%	13%
2	Horsens	33	1	3%	6%	0%
3	Lyngby	33	4	12%	12%	13%
4	Viborg	33	2	6%	6%	6%
5	Vejle	33	1	3%	0%	6%
6	Fredericia	33	1	3%	0%	6%
7	HB Køge	33	2	6%	12%	0%
8	Skive Women	33	3	9%	6%	12%
9	Vendsyssel	33	0	0%	0%	0%
10	Roskilde Women	33	3	9%	13%	6%
11	AB Women	33	6	18%	13%	24%
12	Brønshøj Women	33	1	3%	6%	0%

#	Team	MP	Over 1.5	Overall	Home	Away
1	AGF	33	2	6%	6%	6%
2	Horsens	33	1	3%	6%	0%
3	Lyngby	33	3	9%	12%	6%
4	Viborg	33	1	3%	6%	0%
5	Vejle	33	1	3%	0%	6%
6	Fredericia	33	1	3%	0%	6%
7	HB Køge	33	1	3%	6%	0%
8	Skive Women	33	2	6%	6%	6%
9	Vendsyssel	33	0	0%	0%	0%
10	Roskilde Women	33	2	6%	6%	6%
11	AB Women	33	6	18%	13%	24%
12	Brønshøj Women	33	0	0%	0%	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	AGF	33	14	42%	53%	31%
2	Horsens	33	16	48%	47%	50%
3	Lyngby	33	19	58%	47%	69%
4	Viborg	33	24	73%	76%	69%
5	Vejle	33	17	52%	44%	59%
6	Fredericia	33	22	67%	69%	65%
7	HB Køge	33	24	73%	65%	81%
8	Skive Women	33	19	58%	75%	41%
9	Vendsyssel	33	21	64%	56%	71%
10	Roskilde Women	33	22	67%	69%	65%
11	AB Women	33	17	52%	56%	47%
12	Brønshøj Women	33	21	64%	59%	69%

#	Team	MP	Over 2.5	Overall	Home	Away
1	AGF	33	3	9%	12%	6%
2	Horsens	33	1	3%	6%	0%
3	Lyngby	33	4	12%	12%	13%
4	Viborg	33	4	12%	12%	13%
5	Vejle	33	2	6%	0%	12%
6	Fredericia	33	6	18%	19%	18%
7	HB Køge	33	5	15%	18%	13%
8	Skive Women	33	4	12%	6%	18%
9	Vendsyssel	33	5	15%	19%	12%
10	Roskilde Women	33	2	6%	13%	0%
11	AB Women	33	2	6%	6%	6%
12	Brønshøj Women	33	6	18%	12%	25%

#	Team	MP	Over 2.5	Overall	Home	Away
1	AGF	33	8	24%	35%	13%
2	Horsens	33	6	18%	24%	13%
3	Lyngby	33	9	27%	24%	31%
4	Viborg	33	10	30%	18%	44%
5	Vejle	33	6	18%	13%	24%
6	Fredericia	33	10	30%	25%	35%
7	HB Køge	33	12	36%	41%	31%
8	Skive Women	33	8	24%	25%	24%
9	Vendsyssel	33	13	39%	44%	35%
10	Roskilde Women	33	10	30%	38%	24%
11	AB Women	33	9	27%	19%	35%
12	Brønshøj Women	33	11	33%	35%	31%

#	Team	MP	Over 2.5	Overall	Home	Away
1	AGF	33	23	70%	65%	75%
2	Horsens	33	26	79%	71%	88%
3	Lyngby	33	26	79%	71%	88%
4	Viborg	33	30	91%	88%	94%
5	Vejle	33	22	67%	63%	71%
6	Fredericia	33	28	85%	94%	76%
7	HB Køge	33	28	85%	82%	88%
8	Skive Women	33	27	82%	88%	76%
9	Vendsyssel	33	29	88%	94%	82%
10	Roskilde Women	33	26	79%	81%	76%
11	AB Women	33	23	70%	75%	65%
12	Brønshøj Women	33	28	85%	88%	81%

#	Team	MP	Over 2.5	Overall	Home	Away
1	AGF	33	29	88%	88%	88%
2	Horsens	33	32	97%	94%	100%
3	Lyngby	33	29	88%	88%	88%
4	Viborg	33	31	94%	94%	94%
5	Vejle	33	32	97%	100%	94%
6	Fredericia	33	32	97%	100%	94%
7	HB Køge	33	31	94%	88%	100%
8	Skive Women	33	30	91%	94%	88%
9	Vendsyssel	33	33	100%	100%	100%
10	Roskilde Women	33	30	91%	88%	94%
11	AB Women	33	27	82%	88%	76%
12	Brønshøj Women	33	32	97%	94%	100%

#	Team	MP	Over 2.5	Overall	Home	Away
1	AGF	33	31	94%	94%	94%
2	Horsens	33	32	97%	94%	100%
3	Lyngby	33	30	91%	88%	94%
4	Viborg	33	32	97%	94%	100%
5	Vejle	33	32	97%	100%	94%
6	Fredericia	33	32	97%	100%	94%
7	HB Køge	33	32	97%	94%	100%
8	Skive Women	33	31	94%	94%	94%
9	Vendsyssel	33	33	100%	100%	100%
10	Roskilde Women	33	31	94%	94%	94%
11	AB Women	33	27	82%	88%	76%
12	Brønshøj Women	33	33	100%	100%	100%

You can check out how often Fredericia 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:

70% of Fredericia’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 33%.

You can also check how many times the total has gone under. In HB Køge’s case, 36% of their matches have seen under 1.5 goals scored. And in terms of matches with under 2.5 goals, the rate is 73%.

You can also see whether Fredericia 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 Fredericia 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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