Vestsjælland W 2 - 2 Vejle

01.08.2015 - 12:30

Stadium: Harboe Arena Slagelse

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	33	18	55%	63%	47%
2	Horsens	33	16	48%	53%	44%
3	Silkeborg	33	16	48%	47%	50%
4	Lyngby	33	16	48%	35%	63%
5	Vestsjælland W	33	23	70%	53%	88%
6	Vejle	33	21	64%	65%	63%
7	Fredericia	33	18	55%	63%	47%
8	HB Køge	33	13	39%	50%	29%
9	Skive IK	33	15	45%	44%	47%
10	Vendsyssel	33	12	36%	47%	25%
11	Roskilde W	33	20	61%	56%	65%
12	Næstved	33	16	48%	44%	53%

#	Team	MP	Over 0.5	Overall	Home	Away
1	FC Helsingør	33	31	94%	100%	88%
2	Horsens	33	31	94%	94%	94%
3	Silkeborg	33	31	94%	88%	100%
4	Lyngby	33	31	94%	94%	94%
5	Vestsjælland W	33	30	91%	82%	100%
6	Vejle	33	31	94%	88%	100%
7	Fredericia	33	28	85%	88%	82%
8	HB Køge	33	31	94%	100%	88%
9	Skive IK	33	32	97%	100%	94%
10	Vendsyssel	33	30	91%	94%	88%
11	Roskilde W	33	31	94%	94%	94%
12	Næstved	33	31	94%	94%	94%

#	Team	MP	Over 1.5	Overall	Home	Away
1	FC Helsingør	33	21	64%	75%	53%
2	Horsens	33	25	76%	71%	81%
3	Silkeborg	33	25	76%	71%	81%
4	Lyngby	33	24	73%	59%	88%
5	Vestsjælland W	33	27	82%	71%	94%
6	Vejle	33	26	79%	76%	81%
7	Fredericia	33	24	73%	75%	71%
8	HB Køge	33	21	64%	81%	47%
9	Skive IK	33	24	73%	81%	65%
10	Vendsyssel	33	21	64%	71%	56%
11	Roskilde W	33	26	79%	81%	76%
12	Næstved	33	24	73%	63%	82%

#	Team	MP	Over 1.5	Overall	Home	Away
1	FC Helsingør	33	9	27%	25%	29%
2	Horsens	33	6	18%	24%	13%
3	Silkeborg	33	9	27%	18%	38%
4	Lyngby	33	11	33%	35%	31%
5	Vestsjælland W	33	5	15%	6%	25%
6	Vejle	33	12	36%	47%	25%
7	Fredericia	33	9	27%	38%	18%
8	HB Køge	33	4	12%	6%	18%
9	Skive IK	33	9	27%	19%	35%
10	Vendsyssel	33	6	18%	24%	13%
11	Roskilde W	33	14	42%	44%	41%
12	Næstved	33	8	24%	25%	24%

#	Team	MP	Over 1.5	Overall	Home	Away
1	FC Helsingør	33	3	9%	0%	18%
2	Horsens	33	4	12%	12%	13%
3	Silkeborg	33	4	12%	12%	13%
4	Lyngby	33	7	21%	24%	19%
5	Vestsjælland W	33	3	9%	0%	19%
6	Vejle	33	7	21%	29%	13%
7	Fredericia	33	6	18%	19%	18%
8	HB Køge	33	0	0%	0%	0%
9	Skive IK	33	4	12%	6%	18%
10	Vendsyssel	33	4	12%	24%	0%
11	Roskilde W	33	8	24%	25%	24%
12	Næstved	33	4	12%	13%	12%

#	Team	MP	Over 1.5	Overall	Home	Away
1	FC Helsingør	33	0	0%	0%	0%
2	Horsens	33	3	9%	6%	13%
3	Silkeborg	33	1	3%	6%	0%
4	Lyngby	33	4	12%	6%	19%
5	Vestsjælland W	33	2	6%	0%	13%
6	Vejle	33	3	9%	18%	0%
7	Fredericia	33	3	9%	13%	6%
8	HB Køge	33	0	0%	0%	0%
9	Skive IK	33	2	6%	6%	6%
10	Vendsyssel	33	1	3%	6%	0%
11	Roskilde W	33	5	15%	13%	18%
12	Næstved	33	2	6%	6%	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	33	15	45%	38%	53%
2	Horsens	33	17	52%	47%	56%
3	Silkeborg	33	17	52%	53%	50%
4	Lyngby	33	17	52%	65%	38%
5	Vestsjælland W	33	10	30%	47%	13%
6	Vejle	33	12	36%	35%	38%
7	Fredericia	33	15	45%	38%	53%
8	HB Køge	33	20	61%	50%	71%
9	Skive IK	33	18	55%	56%	53%
10	Vendsyssel	33	21	64%	53%	75%
11	Roskilde W	33	13	39%	44%	35%
12	Næstved	33	17	52%	56%	47%

#	Team	MP	Over 2.5	Overall	Home	Away
1	FC Helsingør	33	2	6%	0%	12%
2	Horsens	33	2	6%	6%	6%
3	Silkeborg	33	2	6%	12%	0%
4	Lyngby	33	2	6%	6%	6%
5	Vestsjælland W	33	3	9%	18%	0%
6	Vejle	33	2	6%	12%	0%
7	Fredericia	33	5	15%	13%	18%
8	HB Køge	33	2	6%	0%	12%
9	Skive IK	33	1	3%	0%	6%
10	Vendsyssel	33	3	9%	6%	13%
11	Roskilde W	33	2	6%	6%	6%
12	Næstved	33	2	6%	6%	6%

#	Team	MP	Over 2.5	Overall	Home	Away
1	FC Helsingør	33	12	36%	25%	47%
2	Horsens	33	8	24%	29%	19%
3	Silkeborg	33	8	24%	29%	19%
4	Lyngby	33	9	27%	41%	13%
5	Vestsjælland W	33	6	18%	29%	6%
6	Vejle	33	7	21%	24%	19%
7	Fredericia	33	9	27%	25%	29%
8	HB Køge	33	12	36%	19%	53%
9	Skive IK	33	9	27%	19%	35%
10	Vendsyssel	33	12	36%	29%	44%
11	Roskilde W	33	7	21%	19%	24%
12	Næstved	33	9	27%	38%	18%

#	Team	MP	Over 2.5	Overall	Home	Away
1	FC Helsingør	33	24	73%	75%	71%
2	Horsens	33	27	82%	76%	88%
3	Silkeborg	33	24	73%	82%	63%
4	Lyngby	33	22	67%	65%	69%
5	Vestsjælland W	33	28	85%	94%	75%
6	Vejle	33	21	64%	53%	75%
7	Fredericia	33	24	73%	63%	82%
8	HB Køge	33	29	88%	94%	82%
9	Skive IK	33	24	73%	81%	65%
10	Vendsyssel	33	27	82%	76%	88%
11	Roskilde W	33	19	58%	56%	59%
12	Næstved	33	25	76%	75%	76%

#	Team	MP	Over 2.5	Overall	Home	Away
1	FC Helsingør	33	30	91%	100%	82%
2	Horsens	33	29	88%	88%	88%
3	Silkeborg	33	29	88%	88%	88%
4	Lyngby	33	26	79%	76%	81%
5	Vestsjælland W	33	30	91%	100%	81%
6	Vejle	33	26	79%	71%	88%
7	Fredericia	33	27	82%	81%	82%
8	HB Køge	33	33	100%	100%	100%
9	Skive IK	33	29	88%	94%	82%
10	Vendsyssel	33	29	88%	76%	100%
11	Roskilde W	33	25	76%	75%	76%
12	Næstved	33	29	88%	88%	88%

#	Team	MP	Over 2.5	Overall	Home	Away
1	FC Helsingør	33	33	100%	100%	100%
2	Horsens	33	30	91%	94%	88%
3	Silkeborg	33	32	97%	94%	100%
4	Lyngby	33	29	88%	94%	81%
5	Vestsjælland W	33	31	94%	100%	88%
6	Vejle	33	30	91%	82%	100%
7	Fredericia	33	30	91%	88%	94%
8	HB Køge	33	33	100%	100%	100%
9	Skive IK	33	31	94%	94%	94%
10	Vendsyssel	33	32	97%	94%	100%
11	Roskilde W	33	28	85%	88%	82%
12	Næstved	33	31	94%	94%	94%

You can check out how often Vestsjælland W and Vejle 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:

82% of Vestsjælland W’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 70%.

You can also check how many times the total has gone under. In Vejle’s case, 21% of their matches have seen under 1.5 goals scored. And in terms of matches with under 2.5 goals, the rate is 36%.

You can also see whether Vestsjælland W and Vejle 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 Vestsjælland W vs Vejle 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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