Always chasing
8/10Toronto conceded first in 8 of their last 10 (league 48%).
Toronto vs Orlando City Prediction, Stats & Betting Tips
Major League Soccer - Season 2026
Clinical
Toronto are scoring more goals than their chances (xG) usually bring
+3goals more than their chances (xG) in their last 10
80% of teams scoring this many more goals than their chances scored fewer in their next 10 games.
Bookmakers: Toronto 40% to winOrlando City 36%
Toronto vs Orlando City score prediction
Major League Soccer
The goals we expect each side to score, not an exact score: built from both teams' chances, the bookmakers' view and real goals here.
Evenly matched in front of goal
3.5 goals in total, a little over the Major League Soccer average of 3.2.
goals expected
Toronto1.9
Orlando City1.6Calculated by MyGameOdds · xG: our own model
How it works
We look at how many chances each team has created and allowed in its recent games in this league, what the bookmakers expected from those games, and the goals actually scored. Then we compare that with how many goals home and away teams usually score here.
Does it work? Since July 2025, our numbers have been 7% closer to the real goals than just using the league average.
How we measure →Get our AI football prediction and stats for Toronto vs Orlando City: our model’s probabilities next to the bookmakers’ odds in each market, how often similar predictions came true, and both teams’ recent form.
Toronto vs Orlando City — Our Model vs the Bookmakers
Market check · Major League Soccer
For each market: our model’s probability for this match, the bookmakers’ probability from the current odds (margin removed), whether the two agree, and how often our predictions like this one came true over the last 12 months. When they disagree, the bookmakers’ number has usually been the better guide.
How to read it
our model’s probabilitybookmakers’ probabilityAgreesDisagreesour model’s pick is / is not the bookmakers’ favouriteTrack record: finished matches from the last 12 months
Full-Time Result →Agrees with bookmakers
Our model’s pick
Toronto to win
Our model 41%Bookmakers 40%
Our track record
In 3,529 matches over the last 12 months where our model gave the same pick a 40–45% chance and the bookmakers agreed, it came true 46.8% of the time (bookmakers said 46.8%).
Both Teams to Score →Agrees with bookmakers
Our model’s pick
Yes, both score
Our model 62%Bookmakers 72%
Our track record
In 2,404 matches over the last 12 months where our model gave the same pick a 60–65% chance and the bookmakers agreed, it came true 62.6% of the time (bookmakers said 61.5%).
Over/Under 2.5 Goals →Agrees with bookmakers
Our model’s pick
Over 2.5 goals
Our model 60%Bookmakers 71%
Our track record
In 5,206 matches over the last 12 months where our model gave the same pick a 55–60% chance and the bookmakers agreed, it came true 58.6% of the time (bookmakers said 59.1%).
Over/Under 3.5 Goals →Disagrees with bookmakers
Our model’s pick
Under 3.5 goals
Our model 62%Bookmakers 50%
Our track record
In 230 matches over the last 12 months where our model gave the same pick a 60–65% chance but the bookmakers favoured a different outcome, it came true 47.4% of the time: closer to the bookmakers’ 47.0% than to our 60–65%.
First Half Result →Agrees with bookmakers
Our model’s pick
Draw at half-time
Our model 41%Bookmakers 36%
Our track record
In 6,581 matches over the last 12 months where our model gave the same pick a 40–45% chance and the bookmakers agreed, it came true 44.8% of the time (bookmakers said 44.2%).
Toronto Goals →Disagrees with bookmakers
Our model’s pick
Toronto 0–1 goals
Our model 55%Bookmakers 44%
Our track record
In 1,823 matches over the last 12 months where our model gave the same pick a 50–55% chance but the bookmakers favoured a different outcome, it came true 41.9% of the time: closer to the bookmakers’ 43.8% than to our 50–55%.
Orlando City Goals →Disagrees with bookmakers
Our model’s pick
Orlando City 0–1 goals
Our model 61%Bookmakers 46%
Our track record
In 325 matches over the last 12 months where our model gave the same pick a 60–65% chance but the bookmakers favoured a different outcome, it came true 44.6% of the time: closer to the bookmakers’ 45.9% than to our 60–65%.
Odds can still move before kick-off. The track record uses closing odds.
Toronto vs Orlando City — AI Prediction & Probabilities by Market
Below are our AI-generated match predictions for Toronto vs Orlando City. Each market shows the probability of each outcome based on our model's analysis of team form, historical data and current season performance.
Toronto–
Orlando City–Winner
1X 67%
BTTS*
Yes 61%
Correct Score
1-1 11%
Over/Under 2.5 goals
over 59%
Over/Under 3.5 goals
under 52%
Toronto–Orlando City–Winner
1X 67%
BTTS*
Yes 61%
Correct Score
1-1 11%
Over/Under 2.5 goals
over 59%
Over/Under 3.5 goals
under 52%
Full Time
141%
X26%
233%
Goals Over/Under
| <1.5 | >1.5 | <2.5 | >2.5 | |
|---|---|---|---|---|
| FT | 20% | 80% | 41% | 59% |
| <3.5 | >3.5 | <4.5 | >4.5 | |
|---|---|---|---|---|
| FT | 52% | 48% | 76% | 24% |
Team Goals Over/Under
| <0.5 | >0.5 | <1.5 | >1.5 | |
|---|---|---|---|---|
| 25% | 75% | 55% | 45% |
| 31% | 69% | 61% | 39% |
| <2.5 | >2.5 | <3.5 | >3.5 | |
|---|---|---|---|---|
| 78% | 22% | 91% | 9% |
| 83% | 17% | 93% | 7% |
1st Half
133%
X41%
226%
1st Score
152%
X6%
242%
Half Time/Full Time
1-1
24%
2-2
17%
X-1
13%
X-X
12%
X-2
11%
2-X
9%
1-X
5%
1-2
4%
2-1
4%
Correct Score
1-1
10.6%
2-1
8.6%
1-2
7.9%
1-0
7.7%
0-1
6.5%
2-2
6.5%
0-0
6.3%
2-0
5.3%
3-1
4.4%
0-2
4.2%
3-2
3.4%
1-3
3.2%
3-0
3.1%
*Probability of each predicted outcome is expressed in percentage (%)
*BTTS - Both teams to score
Toronto vs Orlando City: the stats that stand out
Major League Soccer
Where each side is most unusual compared with the rest of the league: clean sheets, scoring first, wins as favourites and more.
How to read it
the teamleague averageshare of games, 0 to 100%Toronto: always chasing and leaky · Orlando City: always on the scoresheet
8/10Leaky
0/10Toronto kept no clean sheet in their last 10 (league 21%).
Always on the scoresheet
0/10Orlando City scored in all of their last 10 (league 21% fail to score).
Calculated by MyGameOdds
How it works
We compare each team's last 10 games in this competition with how often the same thing happens across the whole league (last 12 months). A fact only shows when the team is noticeably different from a typical team. For example, if teams here score first in half their games, a team needs 7 or more out of 10 (or 3 or fewer). We show up to three facts, the most unusual first, never two about the same thing. They describe what happened, not a forecast.
How we measure →Toronto vs Orlando City: attack vs defence
Major League Soccer
Both sides' chances created and allowed a game, next to the rest of the league, measured with our own xG.
How to read it
other Major League Soccer teamsleague averagelast 10 games↑ Fewer chances allowed (xGA a game)
More chances created (xG a game) →
- Toronto: weak attack, weak defence (1.24 xG, 1.79 xGA a game)
- Orlando City: good attack, weak defence (1.64 xG, 1.74 xGA)
Calculated by MyGameOdds · xG: our own model
How it works
xG is our estimate of how many goals a team's chances were worth, from the shots in each match; xGA is the same for the chances it allowed. The dashed lines are the average of the teams shown. A team close to a line is about average. Teams with fewer than 5 games here aren't in the chart yet.
How we measure →Toronto vs Orlando City form and luck check
Major League Soccer
Whether each side is taking more or fewer points than its chances usually bring.
How to read it
what their chances usually bringoutside the normal range (±4)last 10 Major League Soccer gamesBoth results in line with their chances
- TorontoBookmakers: 40% to win today.Clinical · +3 goals+3.5
- Orlando CityBookmakers: 36% to win today.+0.6
Last 5 matches
Orlando CityL
L
W
W
L
TorontoW
L
L
L
W
W
D
L
Strength rank: Toronto 28th of 30 · Orlando City 22nd of 30
Calculated by MyGameOdds · xG: our own model
How it works
For each of a team's last 10 games, we work out how many points a team usually gets from a game with those chances (xG) for and against, add them up and compare with the points it actually got. We do the same for goals. Strong teams often get a bit more than their chances suggest, so we compare each team with sides of similar strength in this league. That way nobody is flagged just for being good.
We flag a team when the gap is 4 points or more (or 3 goals or more). If some games have no xG data, we use the ones that do.
Does it mean anything? 85% of teams 4+ points ahead of their chances got fewer points in their next 10 games, and 83% of teams 4+ points behind got more. Bookmakers already expect these gaps to even out, so it's a fan's read, not a betting edge.
Strength rank: we rank this season's 30 teams by how much better their attack is than their defence, using chances (xG), the odds and goals. Does it work? Over the first half of a season, this rank predicted the second half better than the league table did.
How we measure →Toronto vs Orlando City: Over 2.5 & BTTS?
Major League Soccer
How often each side's recent league games had over 2.5 goals and both teams scoring.
How to read it
a game where it happenedleague averagelast 10 Major League Soccer gamesBTTS = both teams scoredBoth teams score in Toronto and Orlando City games more often than the Major League Soccer average (63%).
Over 2.5 goalsleague 64%
Toronto7 of 10
Orlando City8 of 10
BTTSleague 63%
Toronto8 of 10
Orlando City8 of 10
Calculated by MyGameOdds
How it works
For each team we take its last 10 games in this competition from the past 12 months (fewer if it hasn't played 10) and count how many went over 2.5 goals and how many had both teams scoring. The league figure uses all 455 games played here in the last 12 months.
How we measure →Toronto vs Orlando City corners, cards and goal times
Major League Soccer
Each side's corners and cards a game, and when it scores and concedes, from its recent league games.
How to read it
league averagelast 10 in the league · corners and cards per gameOrlando City score late
Toronto
Orlando City
3.6
Corners won · league 5.0
4.8
5.4
Corners conceded · league 5.0
5.4
1.9
Cards · league 2.1
2.0
1.6
Opponents' cards · league 2.1
2.3
38%
Goals before half-time · league 46%
20%
31%
Goals after 75' · league 24%
40%
50%
Conceded before half-time · league 46%
45%
20%
Conceded after 75' · league 24%
15%
Calculated by MyGameOdds
How it works
We use each team's last 10 games here. Corners and cards only count games where those stats were recorded, and goal times only count games with reliable goal minutes, so some teams have fewer than 10. We compare with the whole league over the last 12 months.
How we measure →Our prediction record
Our last 5 predictions in each team’s matches, by market.
Full-Time Result
Toronto4/5
Orlando City4/5
Both Teams to Score
Toronto3/5
Orlando City3/5
Over/Under 2.5 Goals
Toronto3/5
Orlando City4/5
Over/Under 3.5 Goals
Toronto4/5
Orlando City2/5
First Half Result
Toronto4/5
Orlando City2/5
Correct Score
Toronto0/5
Orlando City0/5
correct predictionwrong prediction