Always on the scoresheet
1/10PAOK failed to score in only 1 of their last 10 (league 31%).
PAOK vs Kalamata Prediction, Stats & Betting Tips
Super League - Season 2026/2027 (Round 6)
Riding their luck
PAOK are taking more points than their chances usually bring
+4points more than their chances usually bring in their last 10
85% of teams this far ahead of their chances got fewer points in their next 10 games.
Bookmakers: PAOK 81% to winKalamata 7%
PAOK vs Kalamata score prediction
Super League
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 alert2.8 goals expected
2.8 goals in total: more goals than a typical Super League game (average 2.5).
goals expected
PAOK2.0
Kalamata0.8Calculated 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 PAOK vs Kalamata: our model’s probabilities next to the bookmakers’ odds in each market, how often similar predictions came true, and both teams’ recent form.
PAOK vs Kalamata — Our Model vs the Bookmakers
Market check · Super League
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
PAOK to win
Our model 57%Bookmakers 81%
Our track record
In 1,737 matches over the last 12 months where our model gave the same pick a 55–60% chance and the bookmakers agreed, it came true 60.8% of the time (bookmakers said 61.1%).
Both Teams to Score →Agrees with bookmakers
Our model’s pick
No, not both
Our model 57%Bookmakers 56%
Our track record
In 5,496 matches over the last 12 months where our model gave the same pick a 55–60% chance and the bookmakers agreed, it came true 56.9% of the time (bookmakers said 57.7%).
Over/Under 2.5 Goals →Disagrees with bookmakers
Our model’s pick
Under 2.5 goals
Our model 58%Bookmakers 34%
Our track record
In 793 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 47.4% of the time: closer to the bookmakers’ 46.3% than to our 55–60%.
Over/Under 3.5 Goals →Agrees with bookmakers
Our model’s pick
Under 3.5 goals
Our model 79%Bookmakers 56%
Our track record
In 3,597 matches over the last 12 months where our model gave the same pick a 75–80% chance and the bookmakers agreed, it came true 76.3% of the time (bookmakers said 76.4%).
First Half Result →Agrees with bookmakers
Our model’s pick
PAOK ahead at half-time
Our model 43%Bookmakers 62%
Our track record
In 6,500 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%).
PAOK Goals →Disagrees with bookmakers
Our model’s pick
PAOK 0–1 goals
Our model 53%Bookmakers 25%
Our track record
In 1,801 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%.
Kalamata Goals →Agrees with bookmakers
Our model’s pick
Kalamata 0–1 goals
Our model 84%Bookmakers 87%
Our track record
In 1,481 matches over the last 12 months where our model gave the same pick a 80–85% chance and the bookmakers agreed, it came true 78.6% of the time (bookmakers said 80.6%).
Odds can still move before kick-off. The track record uses closing odds.
PAOK vs Kalamata — AI Prediction & Probabilities by Market
Below are our AI-generated match predictions for PAOK vs Kalamata. Each market shows the probability of each outcome based on our model's analysis of team form, historical data and current season performance.
PAOK–
Kalamata–Winner
1 57%
BTTS*
No 57%
Correct Score
1-0 15%
Over/Under 2.5 goals
under 58%
Over/Under 3.5 goals
under 69%
PAOK–Kalamata–Winner
1 57%
BTTS*
No 57%
Correct Score
1-0 15%
Over/Under 2.5 goals
under 58%
Over/Under 3.5 goals
under 69%
Full Time
157%
X27%
216%
Goals Over/Under
| <1.5 | >1.5 | <2.5 | >2.5 | |
|---|---|---|---|---|
| FT | 32% | 68% | 58% | 42% |
| <3.5 | >3.5 | <4.5 | >4.5 | |
|---|---|---|---|---|
| FT | 69% | 31% | 88% | 12% |
Team Goals Over/Under
| <0.5 | >0.5 | <1.5 | >1.5 | |
|---|---|---|---|---|
| 20% | 80% | 53% | 47% |
| 51% | 49% | 84% | 16% |
| <2.5 | >2.5 | <3.5 | >3.5 | |
|---|---|---|---|---|
| 78% | 22% | 92% | 8% |
| 97% | 3% | 99% | 1% |
1st Half
143%
X41%
216%
1st Score
160%
X10%
230%
Half Time/Full Time
1-1
32%
X-X
19%
X-1
16%
2-2
10%
X-2
8%
1-X
6%
2-X
5%
2-1
3%
1-2
2%
Correct Score
1-0
15.0%
1-1
12.2%
2-0
12.0%
0-0
9.9%
2-1
9.3%
0-1
6.7%
3-0
6.4%
3-1
4.7%
1-2
4.4%
2-2
3.8%
*Probability of each predicted outcome is expressed in percentage (%)
*BTTS - Both teams to score
PAOK vs Kalamata: the stats that stand out
Super League
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%PAOK: always on the scoresheet
1/10Calculated 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 →PAOK vs Kalamata: attack vs defence
Super League
How to read it
other Super League teamsleague averagelast 10 games↑ Fewer chances allowed (xGA a game)
More chances created (xG a game) →
- PAOK: weak attack, weak defence (1.37 xG, 1.64 xGA a game)
- Kalamata: weak attack, weak defence (1.16 xG, 1.66 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 →PAOK vs Kalamata form and luck check
Super League
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 Super League gamesPAOK are taking more points than their chances usually bring
- PAOKBookmakers: 81% to win today.Clinical · +5 goals+4.4
- KalamataBookmakers: 7% to win today. · 5 of 10 games−0.7
Last 5 matches
PAOKW
W
L
W
W
KalamataL
W
D
L
L
W
D
L
Strength rank: PAOK 3rd of 14 · Kalamata 9th of 14
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 14 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 →PAOK vs Kalamata: Over 2.5 & BTTS?
Super League
How to read it
a game where it happenedleague averageup to 10 recent Super League gamesBTTS = both teams scoredBoth teams score in PAOK and Kalamata games more often than the Super League average (48%).
Over 2.5 goalsleague 49%
PAOK7 of 10
Kalamata2 of 5
BTTSleague 48%
PAOK7 of 10
Kalamata3 of 5
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 230 games played here in the last 12 months.
How we measure →PAOK vs Kalamata corners, cards and goal times
Super League
How to read it
league averagelast 10 in the league · corners and cards per gameKalamata: last 5 with these statsKalamata score late
PAOK
Kalamata
4.0
Corners won · league 4.4
2.8
5.7
Corners conceded · league 4.4
6.2
2.3
Cards · league 2.6
4.0
1.6
Opponents' cards · league 2.6
2.6
53%
Goals before half-time · league 47%
17%
21%
Goals after 75' · league 21%
33%
38%
Conceded before half-time · league 47%
63%
15%
Conceded after 75' · league 21%
38%
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
PAOK4/5
Kalamata3/5
Both Teams to Score
PAOK3/5
Kalamata3/5
Over/Under 2.5 Goals
PAOK3/5
Kalamata3/5
Over/Under 3.5 Goals
PAOK2/5
Kalamata3/5
First Half Result
PAOK1/5
Kalamata1/5
Correct Score
PAOK0/5
Kalamata1/5
correct predictionwrong prediction