Obolon' Arena · vul. Pivnichna 8
FK Kudrivka
Kolos KovalivkaFK Kudrivka 2 x 3 Kolos Kovalivka: prediction analysis
The model predicted correctly 3 of 5 settled markets.
Correct predictions
- 1x2: prediction Kolos Kovalivka; result Kolos Kovalivka 2–3.
- Double Chance: prediction Draw or Kolos Kovalivka; result Kolos Kovalivka 2–3.
- Over 9.5 corners: prediction Under 9.5; result 5 corners.
Incorrect predictions
- Over 2.5 goals: prediction Under 2.5; result 5 goals.
- Both Teams to Score: prediction No; result Yes.
Final assessment: For this game, most settled predictions matched the observed results.
View the analysis published before kickoff
Before the game, the model Predora Market Median estimated a 25.0% probability of a win for FK Kudrivka, 29.4% for a draw, and 45.6% for a win for Kolos Kovalivka.
The 1X2 market, based on 11 bookmakers, makes Kolos Kovalivka the favorite, with odds ranging from 2.00 to 2.15 (median 2.07). The draw is the second option, with a range of 2.78 to 3.20, while a FK Kudrivka win is the least favored outcome, with odds between 3.25 and 4.04.
The deterministic data points in the same direction as the consensus: the away side has a slight edge in recent form, goal difference and head-to-head record. In a relative comparison, the signals give the away side about 58% of the strength, while the market assigns it approximately 63% when the draw is excluded—in other words, the bookmakers see a slightly greater advantage than the numbers suggest.
There is, however, one caveat: the home/away context indicates that the hosts perform better at home (0.5 PPG) than their rivals do away (0.33 PPG), which could narrow the gap between the teams. In addition, the draw accounts for about 30% of the implied probability, a significant figure that should be considered as a plausible outcome.
In summary, the market and the data are aligned in favor of the away side, but the difference in their assessments is moderate. The uncertainty comes from Kudrivka's home performance and the possibility of a close scoreline, especially given both teams' limited attacking power.
Market 1x2
Formula: 1 ÷ Estimated probability
Formula: 1 ÷ Best market odds (highest-paying bookmaker)
Formula: Probability − Implied probability (Book)
Formula: (Estimated probability × Odds) − 1
Odds Comparison
Bookmakers
Probability Models
| Model | FK Kudrivka | Draw | Kolos Kovalivka |
|---|---|---|---|
| Predora Market Median | 25.0% / 4.00 | 29.4% / 3.40 | 45.6% / 2.19 |
Market Double Chance
Formula: 1 ÷ Estimated probability
Formula: 1 ÷ Best market odds (highest-paying bookmaker)
Formula: Probability − Implied probability (Book)
Formula: (Estimated probability × Odds) − 1
Odds Comparison
Bookmakers
Probability Models
| Model | 1X | X2 | 12 |
|---|---|---|---|
| Predora Market Median | 54.4% / 1.84 | 75.0% / 1.33 | 70.6% / 1.42 |
AI Analysis
Market and data alignedTeam Comparison
Head-to-head (H2H) These statistics use the teams' most recent head-to-head games, generally from the last 10 to 15 years.H2H Last 5
| Factor | FK Kudrivka | Kolos Kovalivka |
|---|---|---|
| H2H: W/D/L (last 5) Results from the last 5 head-to-head games between the teams. Example: 3–1–1 = 3 wins, 1 draw, 1 loss for the team on the left. | 0-0-2 | 2-0-0 |
| H2H: win % (home vs. away) (last 5) Head-to-head win percentage (last 5), split by home and away team. Example: the home team won 3 of 5 = 60%. | 0 % | 100 % |
Outcome Strength (Season)
Game context (Home/Away)
| Factor | FK Kudrivka Home | Kolos Kovalivka Away |
|---|---|---|
| PPG (home/away) Average points per game in the relevant context (home team at home, away team away). Example: 6 points in 4 games = 1.5 points/game.Points per game in context (home team at home / away team away). | 0.33 pts/game | 1 pts/game |
| Win % (home/away) Win percentage in the relevant context (home for the home team, away for the away team). Example: 2 wins in 4 games = 50%. | 0 % | 25 % |
| Draw % (home/away) Draw percentage in the home/away context. Example: 1 draw in 4 games = 25%. | 33.3 % | 25 % |
| Goal difference (home/away) Average goal difference in context: goals scored minus goals conceded per game. Example: scored 6 and conceded 4 in 4 games → (6−4)/4 = +0.5. | -1.33 goals/game | -0.5 goals/game |
| xG difference (home/away) Average xG difference in context: xG for minus xG against per game. Example: 1.4 − 1.1 = +0.3 xG/game. | 0.03 xG/game | -0.52 xG/game |
Season baseline (Overall) Temp
| Factor | FK Kudrivka | Kolos Kovalivka |
|---|---|---|
| PPG (overall) Average points per game this season (home + away). Example: 12 points in 8 games = 1.5 points/game. | 0.33 pts/game | 0.83 pts/game |
| Win % (overall) Win percentage this season (home + away). Example: 4 wins in 8 games = 50%. | 0 % | 16.7 % |
| Draw % (overall) Draw percentage this season (home + away). Example: 2 draws in 8 games = 25%. | 33.3 % | 33.3 % |
| Goal difference (overall) Average goal difference this season: (goals scored − goals conceded) / games. Example: 10−6 in 8 games → +0.5 per game. | -2 goals/game | -0.67 goals/game |
| xG difference (overall) Average xG difference this season: xG for minus xG against per game. Example: 1.6 − 1.2 = +0.4 xG/game. | -0.73 xG/game | -0.35 xG/game |
Recent form (Last 5) These statistics cover the team's last 5 games, regardless of league or season.Last 5
| Factor | FK Kudrivka | Kolos Kovalivka |
|---|---|---|
| Form (last 5): W/D/L Results from the last 5 games: wins, draws, and losses. Example: 2–2–1 = 2 wins, 2 draws, 1 loss. | 1-0-4 | 1-2-2 |
| PPG (last 5) Average points from the last 5 games. Example: 7 points in 5 games = 1.4 points/game. | 0.6 pts/game | 1 pts/game |
Market Over 2.5 goals
Formula: 1 ÷ Estimated probability
Formula: 1 ÷ Best market odds (highest-paying bookmaker)
Formula: Probability − Implied probability (Book)
Formula: (Estimated probability × Odds) − 1
Odds Comparison
Bookmakers
Probability Models
| Model | Over | Under |
|---|---|---|
| Predora Market Median | 45.9% / 2.18 | 54.1% / 1.85 |
Team Comparison
Predictions (AI) Prev
| Factor | Game |
|---|---|
| Potential: average goals Pregame estimate of total goals, based on historical data and AI, combining both teams. Example: 2.8 goals/game ≈ an estimate of 3 goals. | 2.25 goals |
| Over 2.5 potential Pregame estimated probability of 3+ goals, based on historical data and AI. Example: 52% estimates Over 2.5 in about 52 of 100 similar games.Pregame probability of over 2.5 goals | 59 % |
| Under 2.5 potential Pregame estimated probability of under 2.5 goals, based on historical data and AI. Example: 55% estimates Under 2.5 in about 55 of 100 similar games.Pregame probability of under 2.5 goals | 42 % |
Season (baseline)
Game context (Home/Away)
| Factor | FK Kudrivka Home | Kolos Kovalivka Away |
|---|---|---|
| Goals scored (home/away) Average goals scored per game in the relevant context (home team at home, away team away). Example: 6 goals in 4 games = 1.5 goals/game. | 0.67 goals/game | 1.5 goals/game |
| Goals conceded (home/away) Average goals conceded per game in the home/away context. Example: 5 goals conceded in 4 games = 1.25 goals/game. | 2 goals/game | 2 goals/game |
| xG for (home/away) Average chance quality created per game (xG) in the home/away context. Example: 1.6 xG per game means the team’s shots add up to 1.6 expected goals per game on average. | 0.63 xG/game | 0.92 xG/game |
Overall (Season) Temp
| Factor | FK Kudrivka | Kolos Kovalivka |
|---|---|---|
| Over 2.5 (season) Percentage of season games with over 2.5 goals. Example: 7 of 13 games = 54%.Season games with Over 2.5 % | 67 % | 50 % |
| Goals scored (overall) Average goals scored per game this season (home + away). Example: 20 goals in 13 games = 1.54 goals/game. | 0.67 goals/game | 1 goals/game |
| Shots on target / game Average shots on target per game this season (home + away). Example: 48 shots on target in 10 games = 4.8 per game. | 1 shots on target/game | 3.17 shots on target/game |
| Goals conceded (overall) Average goals conceded per game this season (home + away). Example: 15 goals in 13 games = 1.15 goals/game. | 2.67 goals/game | 1.67 goals/game |
League (baseline) League
| Factor | League |
|---|---|
| League average goals Average goals per game in the league this season (competition baseline). Example: 2.68 goals/game ≈ 2–3 goals per game.Average league goals per game (baseline) | 2.27 goals/game |
Recent form (Last 5) These statistics cover the team's last 5 games, regardless of league or season.Last 5
| Factor | FK Kudrivka | Kolos Kovalivka |
|---|---|---|
| Goals scored (last 5) Average goals scored per game in the last 5 games (recent form). Example: 9 goals in 5 games = 1.8 goals/game. | 0.6 goals/game | 1.2 goals/game |
| Goals conceded (last 5) Average goals conceded per game in the last 5 games (recent form). Example: 6 goals conceded in 5 games = 1.2 goals/game. | 2.2 goals/game | 1.6 goals/game |
Head-to-head (H2H) These statistics use the teams' most recent head-to-head games, generally from the last 10 to 15 years.H2H Last 5
| Factor | FK Kudrivka | Kolos Kovalivka |
|---|---|---|
| H2H: Over 2.5 % (last 5) Percentage of the last 5 head-to-head games with over 2.5 goals. Example: 3 of 5 games = 60%.Recent H2H games with Over 2.5 | 50 % | 50 % |
Market Both Teams to Score
Formula: 1 ÷ Estimated probability
Formula: 1 ÷ Best market odds (highest-paying bookmaker)
Formula: Probability − Implied probability (Book)
Formula: (Estimated probability × Odds) − 1
Odds Comparison
Bookmakers
Probability Models
| Model | Yes | No |
|---|---|---|
| Predora Market Median | 49.3% / 2.03 | 50.7% / 1.97 |
Team Comparison
Predictions (AI) Prev
| Factor | Game |
|---|---|
| Potential: BTTS (%) Pregame estimated probability of both teams scoring, based on historical data and AI. Example: 58% estimates that about 58 of 100 similar games would have goals from both teams. | 34 % |
| Over 2.5 potential Pregame estimated probability of 3+ goals, based on historical data and AI. Example: 52% estimates Over 2.5 in about 52 of 100 similar games.Pregame probability of over 2.5 goals | 59 % |
Season baseline (Season)
Indicators associated with more BTTS outcomes
| Factor | FK Kudrivka | Kolos Kovalivka |
|---|---|---|
| BTTS (season) % Percentage of season games in which both teams scored. Example: 7 of 12 games = 58%. | 50 % | 50 % |
| Games scoring 1+ goal % (season) Percentage of season games in which the team scored at least 1 goal. Example: scored in 10 of 12 games = 83%. | 50 % | 50 % |
| Games conceding 1+ goal % (season) Percentage of season games in which the team conceded at least 1 goal. Example: conceded in 8 of 12 games = 67%. | 67 % | 83 % |
Indicators associated with fewer BTTS outcomes
| Factor | FK Kudrivka | Kolos Kovalivka |
|---|---|---|
| Clean sheet % (season) Percentage of clean sheets, a factor associated with fewer Both Teams to Score outcomes. Example: 4 clean sheets in 12 games = 33%. | 33 % | 17 % |
| Failed to score % (season) Percentage of games without scoring, a factor associated with fewer Both Teams to Score outcomes. Example: no goals scored in 3 of 12 games = 25%. | 50 % | 50 % |
Recent form (Last 5) These statistics cover the team's last 5 games, regardless of league or season.Last 5
| Factor | FK Kudrivka | Kolos Kovalivka |
|---|---|---|
| Games scoring 1+ goal % (last 5) Percentage of the last 5 games in which the team scored at least 1 goal. Example: scored in 4 of 5 = 80%. | 40 % | 60 % |
| Games conceding 1+ goal % (last 5) Percentage of the last 5 games in which the team conceded at least 1 goal. Example: conceded in 3 of 5 = 60%. | 60 % | 80 % |
Head-to-head (H2H) These statistics use the teams' most recent head-to-head games, generally from the last 10 to 15 years.H2H Last 5
| Factor | Head-to-head (H2H) |
|---|---|
| H2H: BTTS % (last 5) Percentage of the last 5 head-to-head games in which both teams scored. Example: 3 of 5 games = 60%. | 50 % |
Market Over 9.5 corners
Formula: 1 ÷ Estimated probability
Formula: 1 ÷ Best market odds (highest-paying bookmaker)
Formula: Probability − Implied probability (Book)
Formula: (Estimated probability × Odds) − 1
Odds Comparison
Bookmakers
Probability Models
| Model | Over | Under |
|---|---|---|
| Predora Market Median | 39.9% / 2.51 | 60.1% / 1.66 |
Team Comparison
Predictions (AI) Prev
| Factor | Game |
|---|---|
| Potential: average corners Pregame estimate of total corners, based on historical data and AI. Example: 10.2 corners ≈ an estimate of 10 corners. | 6.33 corners |
| Potential Over 9.5 corners (%) Pregame estimated probability of 10+ corners, based on historical data and AI. Example: 58% estimates Over 9.5 in about 58 of 100 similar games. | 17 % |
Season (baseline)
Game context (Home/Away)
| Factor | FK Kudrivka Home | Kolos Kovalivka Away |
|---|---|---|
| Corners for (home/away) Average corners won per game in context (home team at home, away team away). Example: 24 corners in 6 games = 4.0 per game. | 2.67 corners/game | 3.25 corners/game |
| Total corners (home/away) Average total corners per game in context (both teams combined). Example: 60 corners in 6 games = 10.0 per game. | 5 corners/game | 7.25 corners/game |
Overall (Season) Temp
| Factor | FK Kudrivka | Kolos Kovalivka |
|---|---|---|
| Corners for (overall) Average corners won per game this season (home + away). Example: 40 in 10 games = 4.0 per game. | 2.67 corners/game | 3.83 corners/game |
| Total corners (overall) Average total corners per game this season (home + away). Example: 105 in 10 games = 10.5 per game. | 6 corners/game | 7.83 corners/game |
League (baseline) League
| Factor | League |
|---|---|
| League average corners (corners/game) Average corners per game in the league this season (competition baseline). Example: 9.3 corners/game ≈ 9–10 corners per game. | 8.77 corners/game |
Cards
Team Comparison
Predictions (AI) Prev
| Factor | Game |
|---|---|
| Potential: average cards Pregame estimate of total cards, based on historical data and AI. Example: 4.8 cards ≈ an estimate of 5 cards. | 7.33 cards/game |
Season baseline (Season) Temp
| Factor | FK Kudrivka | Kolos Kovalivka |
|---|---|---|
| Total cards (average) Average cards per game this season (home + away). Example: 18 cards in 6 games = 3.0 cards/game. | 3.67 cards/game | 3.5 cards/game |
| Over 4.5 cards % Probability (or observed percentage, depending on the source) of 5+ cards in the game. Example: 60% estimates Over 4.5 in about 60 of 100 similar games. | 67 % | 83 % |
League (baseline) League
| Factor | League |
|---|---|
| League average cards Average cards per game in the league this season (competition baseline). Example: 4.3 cards/game ≈ 4–5 cards per game. | 4.02 cards/game |