Toronto FC II
New York City FC IIToronto FC II 2 x 0 New York City FC II: prediction analysis
The model predicted correctly 1 of 5 settled markets.
Correct predictions
- Double Chance: prediction Toronto FC II or New York City FC II; result Toronto FC II 2–0.
Incorrect predictions
- 1x2: prediction New York City FC II; result Toronto FC II 2–0.
- Over 2.5 goals: prediction Over 2.5; result 2 goals.
- Both Teams to Score: prediction Yes; result No.
- Over 9.5 corners: prediction Over 9.5; result 7 corners.
Final assessment: For this game, more predictions differed from the observed results than matched them.
View the analysis published before kickoff
Before the game, the model Predora Market Median estimated a 35.8% probability of a win for Toronto FC II, 24.3% for a draw, and 39.9% for a win for New York City FC II.
The 1X2 market lists Toronto FC II as the favorite, with odds ranging from 2.1 to 2.34, while NYC FC II is priced in the 2.52 to 2.81 range. The draw appears as an intermediate option, at around 3.46 to 3.75.
Bookmakers' consensus : Most bookmakers put the home side ahead, with a slight preference for a home win.
Deterministic signals : The data present a mixed picture: while recent form and the season favor NYC FC II, the home/away context and head-to-head record point to Toronto.
Comparison with the market : There is general alignment between the odds set by bookmakers and the signals, but the market seems to give home advantage more weight than the data suggest. The gap between the teams' relative strengths is narrow — around 55% for the home side and 45% for the visitors, excluding the draw.
Point to note : The draw accounts for around 25% of the implied probability, reinforcing how evenly matched this contest is. In addition, NYC FC II has shown recent consistency that may not be fully reflected in the odds.
There is considerable uncertainty, as the signals do not point to a clear winner and bookmakers differ somewhat on the strength of the home-side favoritism.
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 | Toronto FC II | Draw | New York City FC II |
|---|---|---|---|
| Predora Market Median | 35.8% / 2.79 | 24.3% / 4.11 | 39.9% / 2.51 |
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 | 60.1% / 1.66 | 64.2% / 1.56 | 75.7% / 1.32 |
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 | Toronto FC II | New York City FC II |
|---|---|---|
| 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. | 3-0-2 | 2-0-3 |
| 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%. | 60 % | 40 % |
Outcome Strength (Season)
Game context (Home/Away)
| Factor | Toronto FC II Home | New York City FC II 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). | 1.7 pts/game | 1.18 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%. | 50 % | 36.4 % |
| Draw % (home/away) Draw percentage in the home/away context. Example: 1 draw in 4 games = 25%. | 20 % | 9.1 % |
| 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. | 0.1 goals/game | -0.09 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. | -0.33 xG/game | 0.03 xG/game |
Season baseline (Overall) Temp
| Factor | Toronto FC II | New York City FC II |
|---|---|---|
| PPG (overall) Average points per game this season (home + away). Example: 12 points in 8 games = 1.5 points/game. | 1.22 pts/game | 1.61 pts/game |
| Win % (overall) Win percentage this season (home + away). Example: 4 wins in 8 games = 50%. | 34.8 % | 47.8 % |
| Draw % (overall) Draw percentage this season (home + away). Example: 2 draws in 8 games = 25%. | 17.4 % | 17.4 % |
| Goal difference (overall) Average goal difference this season: (goals scored − goals conceded) / games. Example: 10−6 in 8 games → +0.5 per game. | -0.39 goals/game | 0.3 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. | -0.44 xG/game | -0.03 xG/game |
Recent form (Last 5) These statistics cover the team's last 5 games, regardless of league or season.Last 5
| Factor | Toronto FC II | New York City FC II |
|---|---|---|
| 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. | 2-1-2 | 3-1-1 |
| PPG (last 5) Average points from the last 5 games. Example: 7 points in 5 games = 1.4 points/game. | 1.4 pts/game | 2 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 | 66.0% / 1.52 | 34.0% / 2.94 |
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. | 3.53 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 | 82 % |
| 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 | 19 % |
Season (baseline)
Game context (Home/Away)
| Factor | Toronto FC II Home | New York City FC II 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. | 1.9 goals/game | 1.64 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. | 1.8 goals/game | 1.73 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. | 1.3 xG/game | 1.55 xG/game |
Overall (Season) Temp
| Factor | Toronto FC II | New York City FC II |
|---|---|---|
| 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 % | 78 % | 70 % |
| Goals scored (overall) Average goals scored per game this season (home + away). Example: 20 goals in 13 games = 1.54 goals/game. | 1.65 goals/game | 1.83 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. | 4.35 shots on target/game | 4.48 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. | 2.04 goals/game | 1.52 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) | 3.29 goals/game |
Recent form (Last 5) These statistics cover the team's last 5 games, regardless of league or season.Last 5
| Factor | Toronto FC II | New York City FC II |
|---|---|---|
| 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. | 2.2 goals/game | 2.6 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. | 2.4 goals/game | 1.2 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 | Toronto FC II | New York City FC II |
|---|---|---|
| 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 | 80 % | 80 % |
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 | 67.8% / 1.47 | 32.2% / 3.11 |
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. | 73 % |
| 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 | 82 % |
Season baseline (Season)
Indicators associated with more BTTS outcomes
| Factor | Toronto FC II | New York City FC II |
|---|---|---|
| BTTS (season) % Percentage of season games in which both teams scored. Example: 7 of 12 games = 58%. | 65 % | 61 % |
| 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%. | 78 % | 83 % |
| 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%. | 83 % | 74 % |
Indicators associated with fewer BTTS outcomes
| Factor | Toronto FC II | New York City FC II |
|---|---|---|
| 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%. | 17 % | 26 % |
| 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%. | 22 % | 17 % |
Recent form (Last 5) These statistics cover the team's last 5 games, regardless of league or season.Last 5
| Factor | Toronto FC II | New York City FC II |
|---|---|---|
| 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%. | 100 % | 100 % |
| 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%. | 100 % | 60 % |
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%. | 20 % |
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 | 53.6% / 1.87 | 46.4% / 2.16 |
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. | 8.06 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. | 48 % |
Season (baseline)
Game context (Home/Away)
| Factor | Toronto FC II Home | New York City FC II 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. | 3.7 corners/game | 4.36 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. | 9.3 corners/game | 9.18 corners/game |
Overall (Season) Temp
| Factor | Toronto FC II | New York City FC II |
|---|---|---|
| Corners for (overall) Average corners won per game this season (home + away). Example: 40 in 10 games = 4.0 per game. | 3.87 corners/game | 4.57 corners/game |
| Total corners (overall) Average total corners per game this season (home + away). Example: 105 in 10 games = 10.5 per game. | 9.04 corners/game | 9.7 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. | 9.52 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. | 2.19 cards/game |
Season baseline (Season) Temp
| Factor | Toronto FC II | New York City FC II |
|---|---|---|
| Total cards (average) Average cards per game this season (home + away). Example: 18 cards in 6 games = 3.0 cards/game. | 1.13 cards/game | 1.13 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. | 9 % | 13 % |
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. | 3.23 cards/game |