Brisbane Roar vs Melbourne Victory 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.
Brisbane Roar v Melbourne Victory — Team-Based Signals
Brisbane Roar vs Melbourne Victory Head-to-Head — Last 6 Meetings
0-1
HT 0-0
Brisbane Roar
AVUS
0-1
HT 0-0
Brisbane Roar
AVUS
0-0
HT 0-0
Melbourne Victory
AVUS
1-1
HT 0-0
Melbourne Victory
AVUS
0-0
HT 0-0
Brisbane Roar
AVUS
3-0
HT 2-0
Brisbane Roar
AVUS
Brisbane Roar 3-2 Melbourne Victory — Actual Match Statistics
Brisbane Roar edged past Melbourne Victory 3-2. The game was level at 1-1 at the break, so the decisive goals came after it. 5 goals made it one of the day's more open games.
Our pre-match lean was Melbourne Victory at 49%, 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 46%.
On the day, Brisbane Roar had 54% of the ball to Melbourne Victory's 46%, shots finished 15-11, expected goals 2.24 to 0.91 — an xG gap that size says the one-goal margin undersold Brisbane Roar's control.
Coming into the game, across their last 6 meetings in our records, Brisbane Roar had the better of it with 2 wins, 3 drawn. Those games averaged 0.50 goals for Brisbane Roar and 0.67 for Melbourne Victory.
What was the final score of Brisbane Roar vs Melbourne Victory?
Brisbane Roar 3-2 Melbourne Victory in the Australia - A-League on 03/03/2024. The analysis above shows what our model predicted before kick-off next to what actually happened.
What did the model predict for Brisbane Roar vs Melbourne Victory?
Before kick-off our model rated an Melbourne Victory win the most likely single outcome at about 49%, with the full match-result split Brisbane Roar 28%, draw 23%, Melbourne Victory 49%. The final score 3-2 went against our main leads this time — single matches are noisy by nature; our accuracy is measured across thousands of predictions, not one result.