San Jose Earthquakes vs Orlando City 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.
San Jose Earthquakes v Orlando City — Team-Based Signals
San Jose Earthquakes vs Orlando City Head-to-Head — Last 6 Meetings
5-0
HT 3-0
San Jose Earthquakes
ABD
3-0
HT 3-0
Orlando City
ABD
3-2
HT 2-0
San Jose Earthquakes
ABD
1-1
HT 0-0
Orlando City
ABD
2-2
HT 0-0
San Jose Earthquakes
ABD
1-1
HT 0-0
Orlando City
ABD
San Jose Earthquakes 0-1 Orlando City — Actual Match Statistics
Orlando City nicked a narrow win over San Jose Earthquakes 1-0 away from home. The game was level at 0-0 at the break, so the decisive goals came after it.
Our pre-match lean was San Jose Earthquakes at 43%, 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 54% and both teams to score was close to even at 51%.
On the day, San Jose Earthquakes had 50% of the ball to Orlando City's 50%, shots finished 10-11, expected goals 0.59 to 1.93 — an xG gap that size says the one-goal margin undersold Orlando City's control.
Coming into the game, across their last 6 meetings in our records, Orlando City led the recent series with 2 wins, 3 drawn. Those games averaged 1.50 goals for San Jose Earthquakes and 2.00 for Orlando City.
What was the final score of San Jose Earthquakes vs Orlando City?
San Jose Earthquakes 0-1 Orlando City in the USA - Major League on 19/05/2024. The analysis above shows what our model predicted before kick-off next to what actually happened.
What did the model predict for San Jose Earthquakes vs Orlando City?
Before kick-off our model rated a San Jose Earthquakes win the most likely single outcome at about 43%, with the full match-result split San Jose Earthquakes 43%, draw 25%, Orlando City 32%. The final score 0-1 went against our main leads this time — single matches are noisy by nature; our accuracy is measured across thousands of predictions, not one result.