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AC Horsens

At a glance

Based on
Full matches0
Recent matches0
Best-fit markets

No standout market signals yet.

Full Time Result

Win

Flat
Season
No matches
-
Last 5
No matches
-

Draw

Flat
Season
No matches
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Last 5
No matches
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Lose

Flat
Season
No matches
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Last 5
No matches
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Points

Points per game

Flat
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Last 5
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Both Teams To Score

BTS

Flat
Season
No matches
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Last 5
No matches
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BTS & Win

Flat
Season
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Last 5
No matches
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BTS & Lose

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Last 5
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Goals

Average goals scored

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Last 5
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Average goals conceded

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Last 5
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Over 1.5

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Over 2.5

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Over 3.5

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Scored in

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Conceded in

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Clean sheets

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Intervals

Goal in 1H

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Goal in 2H

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Win 1H

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Lose 1H

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Win 2H

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Lose 2H

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Both scored in BH

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Result analysis

0 wins
Home
Away
0
0
v Higher
0
0
v Lower
0 draws
Home
Away
0
0
v Higher
0
0
v Lower
0 losses
Home
Away
0
0
v Higher
0
0
v Lower

Day by day

Stat

Overall

Monday

Tuesday

Wednesday

Thursday

Friday

Saturday

Sunday

Matches played

0

0

0

0

0

0

0

0

Home Win

0%

0%0%0%0%0%0%0%

Draw

0%

0%0%0%0%0%0%0%

Away Win

0%

0%0%0%0%0%0%0%

BTS

0%

0%0%0%0%0%0%0%

BTS & Win

0%

0%0%0%0%0%0%0%

Over 1.5

0%

0%0%0%0%0%0%0%

Over 2.5

0%

0%0%0%0%0%0%0%

Over 3.5

0%

0%0%0%0%0%0%0%

Stats breakdown

AC Horsens stats 

Use this page to test whether the main patterns around AC Horsens still hold when you move beyond the headline view and into deeper team stats.

How to use this stats page

Use this page when you want a denser read on AC Horsens. Start with the best-fit markets and sample context, then move through the stat groups to see whether the same pattern holds across results, goals, and timing splits.

The result-analysis blocks below are there to help you test whether the headline stats still make sense when you look at wins, draws, and losses separately.

Page guide

What this page is showing

This page currently uses 22 AC Horsens matches from Superliga to calculate the team stat groups, best-fit markets, and result analysis shown here.

Current scope

Freshness and methodology

Satdee updates this public stats page as match data changes. Treat the rates and labels as research context rather than predictions, then cross-check the relevant fixtures and wider league environment before you rely on a single signal.

Data quality

Research next

Move from a team page to a watchlist you can explain

  1. Start with the strongest stat groups and best-fit markets.
  2. Check whether the same signal still holds on the matches page and in the league context.
  3. Use the wider market pages only after the team-level pattern still looks coherent.
  4. Return to the Satdee matchday calendar and keep only the fixtures that still make sense.

FAQ

Questions users usually ask next 

A few quick answers about what this team page is showing, how to use it in the Satdee workflow, and where to go next.

Why use AC Horsens stats instead of the overview alone?

AC Horsens stats breaks the team into deeper rate-based groups and result analysis, which is more useful when you want to understand whether the broad overview still holds under closer inspection.

What should I do after finding a useful signal here?

Check the matches page and the wider league context, then return to the Satdee matchday calendar if the upcoming fixture still fits the angle you want to follow.