Ballyclare Comrades vs Harland & Wolff Welders Prediction — Model Probabilities
Edge (pp): green = we see more probability than the market · gold = essentially even (±0.5pp) · red = we see less. The Decision above outranks any single row: the engine backs well-supported edges, not merely big ones.
Ballyclare Comrades v Harland & Wolff Welders — Team-Based Signals
Ballyclare Comrades vs Harland & Wolff Welders Head-to-Head — Last 6 Meetings
3-1
HT 1-1
Harland & Wolff Welders
KİRL1
4-2
HT 3-2
Ballyclare Comrades
KİRL1
0-0
HT 0-0
Harland & Wolff Welders
KİRL1
0-5
HT 0-2
Ballyclare Comrades
KİRL1
2-1
HT 1-0
Ballyclare Comrades
KİRL1
2-2
HT 1-0
Ballyclare Comrades
KİRL1
Ballyclare Comrades 1-4 Harland & Wolff Welders — Actual Match Statistics
Harland & Wolff Welders swept aside Ballyclare Comrades 4-1 away from home. Half-time: 0-3. 5 goals made it one of the day's more open games.
Our pre-match lean was Ballyclare Comrades at 41%, but a lead that slim is closer to a coin-flip than a call — and it fell the other way.
Over 2.5 goals sat near a coin-flip at 50% and both teams to score was close to even at 49%.
On the day, Ballyclare Comrades had 61% of the ball to Harland & Wolff Welders's 39%, shots finished 17-12.
For context: across their last 6 meetings in our records, honours were even at 2 apiece, 2 drawn. Those games averaged 2.17 goals for Ballyclare Comrades and 1.50 for Harland & Wolff Welders.
What was the final score of Ballyclare Comrades vs Harland & Wolff Welders?
Ballyclare Comrades 1-4 Harland & Wolff Welders in the North Ireland - 1st Division on 01/01/2024. The analysis above shows what our model predicted before kick-off next to what actually happened.
What did the model predict for Ballyclare Comrades vs Harland & Wolff Welders?
Before kick-off our model rated a Ballyclare Comrades win the most likely single outcome at about 41%, with the full match-result split Ballyclare Comrades 41%, draw 25%, Harland & Wolff Welders 34%. The final score 1-4 went against our main leads this time — single matches are noisy by nature; our accuracy is measured across thousands of predictions, not one result.