Always on the scoresheet
0/10Paksi SE scored in all of their last 10 (league 23% fail to score).
Paksi SE vs MTK Prediction, Stats & Betting Tips
NB I. - Season 2026/2027 (Round 9)
Goal-fest alert
More goals than usual expected in Paksi SE vs MTK
3.6goals expected · NB I. average 3.0
Since July 2025, games with an alert like this averaged 3.2 goals, and 62% went over 2.5.
Bookmakers: over 2.5 goals 74%
Paksi SE vs MTK score prediction
NB I.
The goals we expect each side to score, not an exact score: built from both teams' chances, the bookmakers' view and real goals here.
Goal-fest alert3.6 goals expected
3.6 goals in total: more goals than a typical NB I. game (average 3.0).
goals expected
Paksi SE2.1
MTK1.5Calculated 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.
Goal-fest alert: we expect at least 2.7 goals, clearly more than usual in this league (8.5% above the average). Since July 2025, these games averaged 3.2 goals, and 62% went over 2.5.
Bore draw alert: we expect 2.3 goals or fewer, clearly less than usual (11% below the average). These games averaged 2.2 goals, and 63% stayed under 2.5.
Bookmakers usually see these coming too, so use the alert to know what kind of game to expect, not as a betting edge.
How we measure →Get our AI football prediction and stats for Paksi SE vs MTK: our model’s probabilities next to the bookmakers’ odds in each market, how often similar predictions came true, and both teams’ recent form.
Paksi SE vs MTK — Our Model vs the Bookmakers
Market check · NB I.
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
Paksi SE to win
Our model 43%Bookmakers 46%
Our track record
In 3,484 matches over the last 12 months where our model gave the same pick a 40–45% chance and the bookmakers agreed, it came true 46.7% of the time (bookmakers said 46.9%).
Both Teams to Score →Agrees with bookmakers
Our model’s pick
Yes, both score
Our model 67%Bookmakers 75%
Our track record
In 387 matches over the last 12 months where our model gave the same pick a 65–70% chance and the bookmakers agreed, it came true 62.8% of the time (bookmakers said 65.1%).
Over/Under 2.5 Goals →Agrees with bookmakers
Our model’s pick
Over 2.5 goals
Our model 65%Bookmakers 74%
Our track record
In 1,094 matches over the last 12 months where our model gave the same pick a 65–70% chance and the bookmakers agreed, it came true 67.9% of the time (bookmakers said 66.7%).
Over/Under 3.5 Goals →Disagrees with bookmakers
Our model’s pick
Under 3.5 goals
Our model 57%Bookmakers 46%
Our track record
In 236 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 44.9% of the time: closer to the bookmakers’ 46.2% than to our 55–60%.
First Half Result →Disagrees with bookmakers
Our model’s pick
Draw at half-time
Our model 36%Bookmakers 34%
Our track record
In 1,157 matches over the last 12 months where our model gave the same pick a 35–40% chance but the bookmakers favoured a different outcome, it came true 36.0% of the time (bookmakers said 35.2%).
Paksi SE Goals →Agrees with bookmakers
Our model’s pick
Paksi SE 2+ goals
Our model 51%Bookmakers 63%
Our track record
In 2,715 matches over the last 12 months where our model gave the same pick a 50–55% chance and the bookmakers agreed, it came true 59.3% of the time (bookmakers said 58.6%).
MTK Goals →Disagrees with bookmakers
Our model’s pick
MTK 0–1 goals
Our model 58%Bookmakers 49%
Our track record
In 589 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 45.3% of the time: closer to the bookmakers’ 44.6% than to our 55–60%.
Odds can still move before kick-off. The track record uses closing odds.
Paksi SE vs MTK — AI Prediction & Probabilities by Market
Below are our AI-generated match predictions for Paksi SE vs MTK. Each market shows the probability of each outcome based on our model's analysis of team form, historical data and current season performance.
Paksi SE–
MTK–Winner
1X 68%
BTTS*
Yes 67%
Correct Score
1-1 10%
Over/Under 2.5 goals
over 65%
Over/Under 3.5 goals
over 53%
Paksi SE–MTK–Winner
1X 68%
BTTS*
Yes 67%
Correct Score
1-1 10%
Over/Under 2.5 goals
over 65%
Over/Under 3.5 goals
over 53%
Full Time
143%
X25%
231%
Goals Over/Under
| <1.5 | >1.5 | <2.5 | >2.5 | |
|---|---|---|---|---|
| FT | 16% | 84% | 35% | 65% |
| <3.5 | >3.5 | <4.5 | >4.5 | |
|---|---|---|---|---|
| FT | 47% | 53% | 74% | 26% |
Team Goals Over/Under
| <0.5 | >0.5 | <1.5 | >1.5 | |
|---|---|---|---|---|
| 21% | 79% | 49% | 51% |
| 30% | 70% | 58% | 42% |
| <2.5 | >2.5 | <3.5 | >3.5 | |
|---|---|---|---|---|
| 75% | 25% | 90% | 10% |
| 82% | 18% | 94% | 6% |
1st Half
133%
X36%
231%
1st Score
149%
X4%
247%
Half Time/Full Time
1-1
25%
2-2
19%
X-1
15%
X-X
13%
X-2
10%
1-X
6%
2-X
6%
2-1
4%
1-2
3%
Correct Score
1-1
10.0%
2-1
9.2%
2-2
8.0%
1-2
7.6%
1-0
6.5%
2-0
5.3%
0-1
4.9%
3-1
4.7%
0-0
4.3%
3-2
4.2%
0-2
3.9%
1-3
3.8%
3-0
3.6%
2-3
3.2%
*Probability of each predicted outcome is expressed in percentage (%)
*BTTS - Both teams to score
Paksi SE vs MTK: the stats that stand out
NB I.
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%Paksi SE: always on the scoresheet
0/10Calculated 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 →Paksi SE vs MTK: attack vs defence
NB I.
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 NB I. teamsleague averagelast 10 games↑ Fewer chances allowed (xGA a game)
More chances created (xG a game) →
- Paksi SE: good attack, weak defence (1.99 xG, 1.67 xGA a game)
- MTK: good attack, weak defence (1.87 xG, 1.83 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 →Paksi SE vs MTK form and luck check
NB I.
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 NB I. gamesBoth results in line with their chances
- Paksi SEBookmakers: 46% to win today.Clinical · +3 goals+0.7
- MTKBookmakers: 31% to win today.−3.3
Last 5 matches
Paksi SEW
L
D
W
L
MTKL
L
D
W
D
W
D
L
Strength rank: Paksi SE 3rd of 12 · MTK 10th of 12
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 12 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 →Paksi SE vs MTK: Over 2.5 & BTTS?
NB I.
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 NB I. gamesBTTS = both teams scoredBoth teams score in Paksi SE and MTK games more often than the NB I. average (59%).
Over 2.5 goalsleague 59%
Paksi SE7 of 10
MTK8 of 10
BTTSleague 59%
Paksi SE8 of 10
MTK9 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 193 games played here in the last 12 months.
How we measure →Paksi SE vs MTK corners, cards and goal times
NB I.
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 gamePaksi SE score early
Paksi SE
MTK
6.2
Corners won · league 4.9
4.4
4.4
Corners conceded · league 4.9
5.0
2.1
Cards · league 2.3
1.9
1.9
Opponents' cards · league 2.3
2.4
54%
Goals before half-time · league 42%
33%
13%
Goals after 75' · league 25%
22%
60%
Conceded before half-time · league 42%
41%
25%
Conceded after 75' · league 25%
35%
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
Paksi SE3/5
MTK2/5
Both Teams to Score
Paksi SE3/5
MTK5/5
Over/Under 2.5 Goals
Paksi SE2/5
MTK4/5
Over/Under 3.5 Goals
Paksi SE3/5
MTK4/5
First Half Result
Paksi SE2/5
MTK4/5
Correct Score
Paksi SE1/5
MTK1/5
correct predictionwrong prediction