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Toronto vs Charlotte 3-3 Score & Prediction Review

Major League Soccer - Season 2026

Fair result
TorontoToronto

3–3

CharlotteCharlotte
1.6Chances (xG)2.0

On these chances Toronto would usually take 1.1 points and Charlotte 1.7; they took 1 and 1. Bookmakers' favourite: Toronto.

Toronto −0.1 pts vs chancesCharlotte −0.7 pts vs chances

Calculated by MyGameOdds · xG: our own model

How it works

Chances (xG): every shot gets a value for how likely it was to go in, and we add them up (our own model). Points their chances were worth: how many points teams usually get from chances like these.

Smash-and-grab: the winner created at least 0.8 xG less than the loser. Robbed: a draw where one side created at least 0.8 xG more. Anything else is a fair result. No verdict after extra time or when there's no xG.

Can you trust it? In these games, SportMonks' own xG agreed on who created more in 95% of the wins and 98% of the draws, and Flashscore agreed in 16 of the 20 games we checked by hand.

How we measure →

Toronto vs Charlotte stats: how the match was played

Major League Soccer

Whether the result matched the chances each side created, measured with our own xG.

Charlotte had clearly more shots on target

Toronto

Charlotte

6

Shots on target

10

1

Big chances

4

6

Corners

5

1

Yellow cards

0

1

Red cards

0

46%

Possession

55%

The match between Toronto and Charlotte ended 3-3. Our AI model predicted a Toronto win at 42% confidence — the final result went a different way, but individual market predictions still offer useful insight. Overall a solid read on this match, with 2 out of 4 key markets predicted correctly, including Both Teams To Score & Over/Under 2.5 Goals.
This match is finished — the model has already priced the next one: Portland Timbers – Charlotte prediction & betting tips (Oct 25, 2026).

Toronto vs Charlotte — Our Model vs the Bookmakers

Market check · Major League Soccer

How our model’s pick did in each market, next to the bookmakers’ last odds before kick-off (margin removed): what was correct, what was wrong, and how often our predictions like this one came true over the last 12 months.

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

Wrong
Our model 42%Bookmakers 41%

Our track record

In 3,626 matches over the last 12 months where our model gave the same pick a 40–45% chance and the bookmakers agreed, it came true 47.0% of the time (bookmakers said 46.9%).

Both Teams to Score →Agrees with bookmakers

Our model’s pick

Yes, both score

Correct
Our model 55%Bookmakers 60%

Our track record

In 6,501 matches over the last 12 months where our model gave the same pick a 50–55% chance and the bookmakers agreed, it came true 55.3% of the time (bookmakers said 55.0%).

Over/Under 2.5 Goals →Agrees with bookmakers

Our model’s pick

Over 2.5 goals

Correct
Our model 50%Bookmakers 59%

Our track record

In 5,191 matches over the last 12 months where our model gave the same pick a 50–55% chance and the bookmakers agreed, it came true 57.0% of the time (bookmakers said 56.4%).

Over/Under 3.5 Goals →Agrees with bookmakers

Our model’s pick

Under 3.5 goals

Wrong
Our model 72%Bookmakers 63%

Our track record

In 4,587 matches over the last 12 months where our model gave the same pick a 70–75% chance and the bookmakers agreed, it came true 72.3% of the time (bookmakers said 71.6%).

First Half Result →Agrees with bookmakers

Our model’s pick

Draw at half-time

Wrong
Our model 42%Bookmakers 41%

Our track record

In 6,723 matches over the last 12 months where our model gave the same pick a 40–45% chance and the bookmakers agreed, it came true 44.7% of the time (bookmakers said 44.2%).

Toronto Goals →Agrees with bookmakers

Our model’s pick

Toronto 0–1 goals

Wrong
Our model 60%Bookmakers 52%

Our track record

In 3,480 matches over the last 12 months where our model gave the same pick a 55–60% chance and the bookmakers agreed, it came true 61.8% of the time (bookmakers said 61.1%).

Charlotte Goals →Agrees with bookmakers

Our model’s pick

Charlotte 0–1 goals

Wrong
Our model 67%Bookmakers 56%

Our track record

In 3,280 matches over the last 12 months where our model gave the same pick a 65–70% chance and the bookmakers agreed, it came true 68.3% of the time (bookmakers said 67.7%).

Odds: the last ones before kick-off. Picks are marked on the result after 90 minutes. The track record uses closing odds.

Toronto vs Charlotte 3-3 — How Our Predictions Performed

The prediction cards below show the pre-match probabilities our AI model generated for Toronto vs Charlotte. Correct predictions are highlighted in green, so you can quickly see where the model read this match well.

· FT
Major League Soccer - USA
TorontoToronto3
CharlotteCharlotte3

Winner

1X 67%

BTTS*

Yes 55%

Correct Score

1-1 12%

Over/Under 2.5 goals

over 50%

Over/Under 3.5 goals

under 62%

Full Time

142%
X26%
233%

Goals Over/Under

<1.5>1.5<2.5>2.5
FT26%74%50%50%
<3.5>3.5<4.5>4.5
FT62%38%85%15%

Team Goals Over/Under

<0.5>0.5<1.5>1.5
Toronto27%73%60%40%
Charlotte33%67%66%34%
<2.5>2.5<3.5>3.5
Toronto83%17%95%5%
Charlotte88%12%96%4%

1st Half

134%
X42%
223%

1st Score

154%
X7%
239%

Half Time/Full Time

1-1

24%

2-2

17%

X-1

15%

X-X

15%

X-2

12%

1-X

6%

2-X

5%

1-2

3%

2-1

3%

Correct Score

1-1

12.0%

1-0

10.0%

2-1

8.8%

0-1

8.5%

1-2

7.8%

0-0

7.3%

2-0

7.0%

2-2

5.4%

0-2

5.2%

3-1

4.2%

3-0

3.3%

1-3

3.1%

*Probability of each predicted outcome is expressed in percentage (%)

*BTTS - Both teams to score

This match is finished — the model has already priced the next one: Portland Timbers – Charlotte prediction & betting tips (Oct 25, 2026).

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