League Two

England• Fleetwood, Lancashire

January 28, 25

2 - 0

Main Tip

1 - 2

or1 - 1

(44%)

Total - Away: Over 0.5 @ 1.22

7°Covercast clouds

85% 6.46 m/s

Fleetwood Town vs Walsall - AI Football Prediction for January 28, 25

Our AI-powered preview for the League Two clash between Fleetwood Town and Walsall on January 28, 25 in England delivers a comprehensive look at both teams' recent form and their head-to-head history. Fleetwood Town have managed 1 win(s), 2 draw(s), and 2 loss(es) in their last 5 matches, averaging 1.0 goals per game. Meanwhile, Walsall have recorded 4 win(s), 1 draw(s), and 0 loss(es) in the same period, with an average of 2.0 goals per match. Looking at their previous encounters, these teams have faced each other 1 time(s): Fleetwood Town have won 1, Walsall have won 0, and 0 match(es) ended in a draw. On average, their meetings have produced 8.0 goals per game. Factoring in current form, historical results, and advanced statistical models, our AI provides actionable insights to help you make smarter betting decisions for this match.

Team Performance Metrics

Average Goals per Game

1.00

Average of 1.00 goals scored per match

Formation

3-5-2

Most commonly used formation

Defensive Efficiency

6.3

Defensive Efficiency rated 6.3/10

Offensive Efficiency

6.7

Offensive Efficiency rated 6.7/10

Overall Team Performance

6.5

Overall team performance rated 6.5/10

Average Shots On Goal

3.0

Average shots on target per match

Goal Conversion Rate

43.8%

Shot-to-goal conversion rate

Average Goals per Game

2.00

Average of 2.00 goals scored per match

Formation

3-5-2

Most commonly used formation

Defensive Efficiency

6.6

Defensive Efficiency rated 6.6/10

Offensive Efficiency

6.7

Offensive Efficiency rated 6.7/10

Overall Team Performance

6.6

Overall team performance rated 6.6/10

Average Shots On Goal

4.2

Average shots on target per match

Goal Conversion Rate

34.8%

Shot-to-goal conversion rate

Recent Matches

Fleetwood Town

Walsall

Insights

Won 80% of last 5 matches

Scored in last 5 match

Highest score in last 5: 4 goals

Goal difference in last 5: +6

Currently unbeaten in the last 5 matches

Head to Head

Prediction Insight

1 - 2

or1 - 1

With a balanced 44% probability rating, this prediction offers moderate value. Our analysis reveals mixed but generally positive indicators, including relevant historical patterns and current form metrics. Consider this a calculated opportunity that requires strategic stake management. Key performance indicators suggest potential upside, though market volatility should be factored into betting decisions.

Balanced Value Play

Confidence Level: Moderate

Fleetwood Town: We predicted 2 correct scores out of the last 6 games (33% accuracy)

Walsall: We predicted 4 correct scores out of the last 7 games (57% accuracy)

44%

Frequently Asked Questions

General, technical, and compliance information about Superior Tips' AI-powered football predictions.

: Superior Tips is a football prediction platform that uses advanced artificial intelligence models to forecast match outcomes. It analyzes data from over 200 leagues worldwide, factoring in recent form, player stats, and team dynamics to generate high-accuracy predictions. These forecasts help users make more informed betting decisions using a data-driven approach.
: We cover all major football leagues, including the English Premier League, La Liga, Bundesliga, Serie A, and Ligue 1, as well as dozens of lower-tier and international competitions. Our system updates daily to ensure full coverage of ongoing matches across over 200 leagues worldwide.
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: Predictions are updated daily, usually before noon GMT. Updates account for lineups, injuries, and other real-time events that impact accuracy.
: Our prediction engine is built on machine learning models trained with historical match data, team statistics, and player-level metrics. The system continuously learns and adapts, identifying hidden patterns and outcome probabilities far beyond what manual analysis can achieve.
: We feed the AI with over 40 parameters per match: team strength, win/loss streaks, player injuries, home/away stats, historical matchups, expected goals (xG), and even weather data. The model then weighs these dynamically to output accurate forecasts.
: xG helps quantify goal-scoring opportunities based on shot quality and position. We integrate xG to better estimate team dominance and attacking efficiency, which improves the reliability of our final predictions.
: Our AI achieves up to 96.8% accuracy on specific match types, tracked using outcome validation against real match results. Accuracy is calculated per market (e.g. match winner, BTTS, over/under) and continuously monitored to improve reliability.
: We use ensemble models, including random forests and gradient boosting, along with neural networks for deeper insights. These models work together to evaluate multiple scenarios and reduce prediction error.
: The model adapts in real-time to data like confirmed injuries, lineup changes, and match-day conditions. This ensures the most up-to-date forecasts for every fixture.
: We source data from premium providers, validate it with cross-checking techniques, and continuously monitor input for inconsistencies. Quality control is built into our pipeline.
: Each percentage reflects the model's confidence in a specific outcome (win, draw, loss). A 70% win chance doesn't mean a guaranteed result but indicates strong statistical advantage.
: 'Accumulator' refers to a group of individually predicted matches bundled into one bet for higher combined odds. 'Bet of the Day' is our highest-confidence single pick, selected using confidence scoring across all models.
: Use the homepage filters or sidebar buttons for quick access by league (e.g. Premier League) or by bet type. Each match card includes sorting options.
: Our xG section shows the likelihood of each team scoring based on shot quality, attacking positions, and past performance. It helps users understand whether a team is underperforming or overperforming relative to expected output.
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: No. While our models provide statistically strong predictions, football matches are inherently uncertain. We do not offer guaranteed wins and recommend responsible use.
: No. All predictions are informational and based on statistical analysis. We do not provide personalized betting advice.
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: Structured data allows search engines and AI models to directly parse content like FAQs and match data. This improves visibility in search features like rich snippets.
: Yes, we provide a public widget for embedding match predictions. API access is in development for B2B use.
: We maintain XML sitemaps, optimized meta tags, fast-loading pages, and ensure mobile-first indexing. We also support llms.txt and robots.txt directives for crawler guidance.

League Two

Fleetwood Town

Walsall

Fleetwood Town vs Walsall - AI Football Prediction for January 28, 25

Team Performance Metrics

Fleetwood Town

Walsall

Recent Matches

Fleetwood Town

Walsall

Insights

Head to Head

Prediction Insight

Frequently Asked Questions

GENERAL

AI & DATA

USER GUIDANCE

COMPLIANCE

TECHNICAL CRAWLABILITY