Kalamata vs OFI Prediction, Stats & Betting Tips

Super League - Season 2026/2027 (Round 7)

Clinical

OFI are scoring more goals than their chances (xG) usually bring

+4goals 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: OFI 31% to winKalamata 40%

Kalamata vs OFI 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.

Evenly matched in front of goal

2.7 goals in total, a little over the Super League average of 2.5.

goals expected

Calculated 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 Kalamata vs OFI: our model’s probabilities next to the bookmakers’ odds in each market, how often similar predictions came true, and both teams’ recent form.

Kalamata vs OFI — 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

Kalamata to win

Our model 44%Bookmakers 40%

Our track record

In 3,483 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 →Disagrees with bookmakers

Our model’s pick

Yes, both score

Our model 55%Bookmakers 48%

Our track record

In 542 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 44.6% of the time: closer to the bookmakers’ 46.8% than to our 55–60%.

Over/Under 3.5 Goals →Agrees with bookmakers

Our model’s pick

Under 3.5 goals

Our model 67%Bookmakers 79%

Our track record

In 3,819 matches over the last 12 months where our model gave the same pick a 65–70% chance and the bookmakers agreed, it came true 68.2% of the time (bookmakers said 66.9%).

First Half Result →Agrees with bookmakers

Our model’s pick

Draw at half-time

Our model 46%Bookmakers 46%

Our track record

In 4,145 matches over the last 12 months where our model gave the same pick a 45–50% chance and the bookmakers agreed, it came true 47.8% of the time (bookmakers said 47.3%).

Kalamata Goals →Agrees with bookmakers

Our model’s pick

Kalamata 0–1 goals

Our model 54%Bookmakers 63%

Our track record

In 2,713 matches over the last 12 months where our model gave the same pick a 50–55% chance and the bookmakers agreed, it came true 59.2% of the time (bookmakers said 58.6%).

OFI Goals →Agrees with bookmakers

Our model’s pick

OFI 0–1 goals

Our model 66%Bookmakers 70%

Our track record

In 3,159 matches over the last 12 months where our model gave the same pick a 65–70% chance and the bookmakers agreed, it came true 68.1% of the time (bookmakers said 67.8%).

Odds can still move before kick-off. The track record uses closing odds.

Kalamata vs OFI — AI Prediction & Probabilities by Market

Below are our AI-generated match predictions for Kalamata vs OFI. Each market shows the probability of each outcome based on our model's analysis of team form, historical data and current season performance.

KalamataKalamata–
OFIOFI–

Winner

1X 70%

BTTS*

Yes 55%

Correct Score

1-1 11%

Over/Under 2.5 goals

over 55%

Over/Under 3.5 goals

under 57%

Full Time

144%
X26%
230%

Goals Over/Under

<1.5>1.5<2.5>2.5
FT22%78%45%55%
<3.5>3.5<4.5>4.5
FT57%43%81%19%

Team Goals Over/Under

<0.5>0.5<1.5>1.5
Kalamata24%76%54%46%
OFI34%66%66%34%
<2.5>2.5<3.5>3.5
Kalamata79%21%92%8%
OFI86%14%95%5%

1st Half

135%
X46%
219%

1st Score

155%
X6%
239%

Half Time/Full Time

1-1

29%

X-1

17%

X-X

17%

2-2

12%

X-2

10%

1-X

5%

2-X

5%

2-1

3%

1-2

2%

Correct Score

1-1

11.4%

1-0

8.9%

2-1

8.9%

2-0

7.1%

0-1

7.0%

1-2

6.9%

0-0

6.5%

2-2

6.0%

3-1

4.8%

0-2

4.3%

3-0

3.9%

1-3

3.1%

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

*BTTS - Both teams to score

Kalamata vs OFI: 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%

OFI: fast starters and always on the scoresheet

Fast starters
OFI7/10

OFI scored first in 7 of their last 10 (league 45%).

Always on the scoresheet
OFI1/10

OFI failed to score in only 1 of their last 10 (league 31%).

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 →

Kalamata vs OFI: 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) →

  • KalamataKalamata: weak attack, weak defence (1.16 xG, 1.66 xGA a game)
  • OFIOFI: weak attack, good defence (1.34 xG, 1.38 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 →

Kalamata vs OFI 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 games

Both results in line with their chances

  • Kalamata
    KalamataBookmakers: 40% to win today. · 5 of 10 games
    −0.7
  • OFI
    OFIBookmakers: 31% to win today.Clinical · +4 goals
    +3.7

Last 5 matches

OFIOFI
D
W
W
L
W
4th in table
KalamataKalamata
L
W
D
L
L
10th in table
W
D
L
Last 5 Matches

Strength rank: Kalamata 9th of 14 · OFI 11th 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 →

Kalamata vs OFI: Over 2.5 & BTTS?

Super League

How to read it

a game where it happenedleague averageup to 10 recent Super League gamesBTTS = both teams scored

Both teams score in Kalamata and OFI games more often than the Super League average (48%).

Over 2.5 goalsleague 49%
Kalamata2 of 5
OFI5 of 10
BTTSleague 48%
Kalamata3 of 5
OFI5 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 230 games played here in the last 12 months.

How we measure →

Kalamata vs OFI 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 statsPro · free for now

OFI score early, Kalamata late

Kalamata

OFI

2.8

Corners won · league 4.4

3.0

6.2

Corners conceded · league 4.4

4.5

4.0

Cards · league 2.6

2.4

2.6

Opponents' cards · league 2.6

2.9

17%

Goals before half-time · league 47%

63%

33%

Goals after 75' · league 21%

19%

63%

Conceded before half-time · league 47%

46%

38%

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

OFIOFI
3/5
KalamataKalamata
3/5

Both Teams to Score

OFIOFI
2/5
KalamataKalamata
3/5

Over/Under 2.5 Goals

OFIOFI
1/5
KalamataKalamata
3/5

Over/Under 3.5 Goals

OFIOFI
4/5
KalamataKalamata
3/5

First Half Result

OFIOFI
2/5
KalamataKalamata
1/5

Correct Score

OFIOFI
0/5
KalamataKalamata
1/5
correct predictionwrong prediction

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