Shot-shy
4/10New York RB failed to score in 4 of their last 10 (league 21%).
New York RB vs San Diego Prediction, Stats & Betting Tips
Major League Soccer - Season 2026
Wasteful
New York RB are scoring fewer goals than their chances (xG) usually bring
−5goals fewer than their chances (xG) in their last 10
77% of teams scoring this many fewer goals than their chances scored more in their next 10 games.
Bookmakers: New York RB 37% to winSan Diego 38%
New York RB vs San Diego 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
3.2 goals in total, in line with the Major League Soccer average of 3.2.
goals expected
New York RB1.6
San Diego1.6Calculated 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 New York RB vs San Diego: our model’s probabilities next to the bookmakers’ odds in each market, how often similar predictions came true, and both teams’ recent form.
New York RB vs San Diego — 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
San Diego to win
Our model 38%Bookmakers 38%
Our track record
In 2,060 matches over the last 12 months where our model gave the same pick a 35–40% chance and the bookmakers agreed, it came true 43.5% of the time (bookmakers said 43.9%).
Both Teams to Score →Agrees with bookmakers
Our model’s pick
Yes, both score
Our model 61%Bookmakers 72%
Our track record
In 2,395 matches over the last 12 months where our model gave the same pick a 60–65% chance and the bookmakers agreed, it came true 62.8% 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 73%
Our track record
In 5,197 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 63%Bookmakers 49%
Our track record
In 228 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 46.9% 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 37%Bookmakers 36%
Our track record
In 1,983 matches over the last 12 months where our model gave the same pick a 35–40% chance and the bookmakers agreed, it came true 40.3% of the time (bookmakers said 41.2%).
New York RB Goals →Disagrees with bookmakers
Our model’s pick
New York RB 0–1 goals
Our model 57%Bookmakers 46%
Our track record
In 980 matches over the last 12 months where our model gave the same pick a 55–60% chance but the bookmakers favoured a different outcome, it came true 43.8% of the time: closer to the bookmakers’ 45.2% than to our 55–60%.
San Diego Goals →Disagrees with bookmakers
Our model’s pick
San Diego 0–1 goals
Our model 57%Bookmakers 44%
Our track record
In 600 matches over the last 12 months where our model gave the same pick a 55–60% chance but the bookmakers favoured a different outcome, it came true 45.2% of the time: closer to the bookmakers’ 44.7% than to our 55–60%.
Odds can still move before kick-off. The track record uses closing odds.
New York RB vs San Diego — AI Prediction & Probabilities by Market
Below are our AI-generated match predictions for New York RB vs San Diego. Each market shows the probability of each outcome based on our model's analysis of team form, historical data and current season performance.
New York RB–
San Diego–Winner
12 76%
BTTS*
Yes 61%
Correct Score
1-1 11%
Over/Under 2.5 goals
over 60%
Over/Under 3.5 goals
under 53%
New York RB–San Diego–Winner
12 76%
BTTS*
Yes 61%
Correct Score
1-1 11%
Over/Under 2.5 goals
over 60%
Over/Under 3.5 goals
under 53%
Full Time
138%
X24%
238%
Goals Over/Under
| <1.5 | >1.5 | <2.5 | >2.5 | |
|---|---|---|---|---|
| FT | 19% | 81% | 40% | 60% |
| <3.5 | >3.5 | <4.5 | >4.5 | |
|---|---|---|---|---|
| FT | 53% | 47% | 77% | 23% |
Team Goals Over/Under
| <0.5 | >0.5 | <1.5 | >1.5 | |
|---|---|---|---|---|
| 27% | 73% | 57% | 43% |
| 27% | 73% | 57% | 43% |
| <2.5 | >2.5 | <3.5 | >3.5 | |
|---|---|---|---|---|
| 81% | 19% | 93% | 7% |
| 80% | 20% | 93% | 7% |
1st Half
136%
X37%
227%
1st Score
153%
X5%
242%
Half Time/Full Time
1-1
26%
2-2
18%
X-1
13%
X-X
13%
X-2
11%
1-X
6%
2-X
6%
1-2
3%
2-1
3%
Correct Score
1-1
10.7%
2-1
8.3%
1-2
8.2%
0-1
7.1%
1-0
6.9%
2-2
6.5%
0-2
5.5%
2-0
5.4%
0-0
4.9%
1-3
4.3%
3-1
4.2%
2-3
3.4%
3-2
3.4%
*Probability of each predicted outcome is expressed in percentage (%)
*BTTS - Both teams to score
New York RB vs San Diego: 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%New York RB: shot-shy
4/10Calculated 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 →New York RB vs San Diego: 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) →
- New York RB: weak attack, weak defence (1.19 xG, 1.65 xGA a game)
- San Diego: weak attack, weak defence (1.45 xG, 1.56 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 →New York RB vs San Diego 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
- New York RBBookmakers: 37% to win today.Wasteful · −5 goals+1.4
- San DiegoBookmakers: 38% to win today.−0.7
Last 5 matches
New York RBL
W
W
L
D
San DiegoD
D
L
L
L
W
D
L
Strength rank: New York RB 27th of 30 · San Diego 14th 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 →New York RB vs San Diego: 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 scoredNew York RB games go over 2.5 goals less often than the Major League Soccer average (64%), San Diego games more often.
Over 2.5 goalsleague 64%
New York RB4 of 10
San Diego7 of 10
BTTSleague 63%
New York RB4 of 10
San Diego6 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 →New York RB vs San Diego 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 gameGoal times close to the Major League Soccer average
New York RB
San Diego
5.0
Corners won · league 5.0
4.5
6.0
Corners conceded · league 5.0
4.8
1.8
Cards · league 2.1
2.0
2.0
Opponents' cards · league 2.1
2.6
38%
Goals before half-time · league 46%
38%
25%
Goals after 75' · league 24%
19%
29%
Conceded before half-time · league 46%
42%
36%
Conceded after 75' · league 24%
21%
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
New York RB1/5
San Diego1/5
Both Teams to Score
New York RB0/5
San Diego3/5
Over/Under 2.5 Goals
New York RB1/5
San Diego4/5
Over/Under 3.5 Goals
New York RB5/5
San Diego1/5
First Half Result
New York RB2/5
San Diego1/5
Correct Score
New York RB0/5
San Diego0/5
correct predictionwrong prediction