Kahraba Ismailia vs Haras El Hodood: match statistics

Kahraba Ismailia show better form over the last five matches: 3 wins, 1 draw and 1 loss, averaging 2.0 points per game, while Haras El Hodood have 0 wins, 3 draws and 2 losses in that period (0.6 pts/game). Offensively the hosts scored 6 goals in their last 5 matches and at home average 0.94 goals with an average xG of 1.20, whereas the visitors scored only 2 goals in their last 5 and average 0.62 goals away with xG 1.15. Kahraba are also more efficient in chance conversion: conversion rate 10% versus 6% for Haras, with 3.12 shots on target per game vs 2.92, and a share of goalless matches of 24% versus 46% — a clear effectiveness advantage. Defensively the gap is smaller: hosts concede 2.00 goals on average at home, while Haras concede 1.62 away, however both teams have negative goal differences (Kahraba -18 at home, Haras -13 away) and vulnerability to conceded goals. Considering better form, higher conversion and a much lower rate of goalless matches, I predict a home win; probability estimate: 62% Kahraba, 20% draw, 18% Haras.

Seasonal BTTS rates are similar: Kahraba 47% and Haras 46%, while the league BTTS percentage is 46%, providing an even starting point. However, Haras’ attack is weak — only 22 goals this season (0.62 per match) and just 2 goals in the last 5 matches (0.4 per match), which significantly lowers the likelihood they score today. Kahraba can also deliver clean sheets: 41% of their season matches are CS, they conceded 48 goals this season (1.18 per match), and in the last 5 matches they conceded an average of 1.0 goal (5 goals), so their defense can contain Haras’ weak offense. Although xG suggests similar chance creation (xG 1.21 for Kahraba vs 1.15 for Haras) and a combined ~2.36 xG, Haras’ conversion rate is only 6% (vs 8% Kahraba) and in the last 5 matches Haras had xG 1.48 with only 0.4 goals, therefore the higher probability is on “No” (No Goal).

The xG-based model gives a total expected xG = 2.69: home 1.41 (attacking xG 1.21 vs away defense 1.61) and away 1.28 (attacking xG 1.15 vs home defense 1.40), which is clearly above the league average of 1.99 goals per match. Seasonal metrics confirm a tendency toward more than 1.5 goals — Over 1.5 occurred in 53% of home matches and 62% of away matches, while Over 0.5 occurs in 71% of home fixtures and 92% of away fixtures. From a Poisson distribution with lambda = 2.69 we get probability for >1.5 at approximately 75%, >2.5 around 51% and >3.5 about 29%, therefore the strongest signal is Over 1.5. Additionally, in the last 5 matches the home side averaged 1.2 goals (6 goals/5) while the away side only 0.4 (2 goals/5), but the away team has higher recent xG (1.48 vs 1.10), suggesting potential improvement in conversion and an increase in total goals; hence the recommendation of Over 1.5 as the most value-driven selection.

The most likely scenario is a draw at half-time and a draw at full-time (X/X) — I assigned 36% to this combination. The home side drew at the break in 47% of matches and the visitors in 38%, yielding an estimated ~43% probability for an HT draw and justifying a strong weighting of scenarios featuring X at the break. A draw after 90 minutes is supported by seasonal draw rates: homes record draws in 47% of fixtures, visitors in 23%, and the visitors’ poor form over the last five matches (an average of 0.6 points per game) limits the chances of an away victory. At the same time I allocated 28% to the HT draw → home win turnaround (X/1), because the home team has slightly better xG (1.21 vs 1.15) and the visitors concede an average of 0.85 goals after the break (conceded_2hg_avg_away=0.85), which favors a second-half change of result.