Free football 1x2 predictions and tips for Egypt Second League

#	Name	P	W	D	L	Goals	Last 5	Pts
1	Olympic El Qanah	34	21	9	4	53:19	DLWDL	72
2	Asyut Petrol	34	16	12	6	42:27	WDWLL	60
3	Abu Qair Semad	34	15	13	6	40:25	WDWDD	58
4	Masar	34	15	10	9	47:29	WLDWL	55
5	Proxy	34	13	16	5	41:31	WWDWW	55
6	La Viena FC	34	14	12	8	38:23	DWLWW	54
7	Itesalat	34	11	13	10	30:34	LDLDD	46
8	El Seka El Hadid	34	12	10	12	28:33	DDLLW	46
9	Maleyet Kafr El Zayiat	34	11	11	12	31:29	WWLDW	44
10	El Mansura	34	9	17	8	28:27	DDDWD	44
11	Tersana	34	8	16	10	31:32	DDDWD	40
12	Dayrout	34	10	13	11	23:30	DWWDD	43
13	El Dakhleya	34	10	10	14	31:43	LWWLW	40
14	El Entag EL Harby	34	10	9	15	38:48	DLWDL	39
15	Tanta SC	34	5	18	11	27:36	DWDLD	33
16	Baladiyyat Al Mehalla	34	7	11	16	34:38	LLDWW	32
17	Aswan Sc	34	5	10	19	15:42	LLLLL	25
18	Raya Ghazl	34	4	10	20	20:51	LLLLL	22

When are the 1x2 Egypt Second League Predictions available?

You can track down our 1x2 Second League tips and predictions on this page, predictions are posted 4 days before any Second League event. Using artificial intelligence on football predictions help users predict outcomes for 1x2 tips in a given event.

What is 1x2 Predictions?

1X2 predictions is simply the outcome of a fixture and is often referred to as match result. The 1X2 connects straightforwardly to this: backing the home team, which is signified by the number 1, backing the draw, which is signified by the letter X, backing the away team, which is signified by the number 2.

Top Countries

News and Articles

Bayer assistant coach Meijer becomes head coach at Sparta Rotterdam

Rogier Meijer leaves Bayer Leverkusen after one year to become Sparta Rotterdam head coach, signing until 2028 after an eventful spell in Germany.

Value betting explained with examples from AI probabilities

A clear, example-driven guide to value betting using AI probabilities, showing how to convert odds into implied probabilities, spot positive expected value, size stakes responsibly, and avoid common traps.

Expected goals explained and how AI uses xG to predict results

Understand expected goals (xG) from first principles and see how AI uses xG, shot quality, and team context to predict football results with stronger accuracy and calibration.

Machine learning vs human intuition in match forecasting

Compare machine learning and human intuition in match forecasting, examining strengths, blind spots, and why a hybrid approach often delivers the most dependable predictions.

How to use Elo ratings for football predictions

A practical guide to using Elo ratings in football predictions, from team strength and home advantage to draw probability, league adjustments, and model improvement.

Over and under goals: how AI predicts goal totals

Learn how AI predicts over and under goals by estimating expected goals, tempo, team styles, and variance, then converting them into calibrated probabilities for total goals markets.