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Tromsdalen vs Rana FK

Expert Overview: Tromsdalen vs Rana FK

The upcoming match between Tromsdalen and Rana FK on 2025-09-27 at 14:00 is anticipated to be a thrilling encounter, with both teams eager to secure a victory. The statistical predictions suggest a high-scoring game, with an average total of 5.15 goals expected. Both teams have shown offensive capabilities, with Tromsdalen likely to capitalize in the second half and Rana FK posing a threat in the latter stages of the match. This analysis will delve into each betting market, providing expert insights based on the provided data.

Tromsdalen

LWWWW-

Rana FK

WDLWWDate: 2025-09-27Time: 14:00Venue: TUIL Arena

Predictions:

MarketPredictionOddResult
Over 1.5 Goals97.90% Make Bet
Home Team To Score In 2nd Half88.00% Make Bet
Over 0.5 Goals HT84.00% Make Bet
Both Teams To Score77.60% Make Bet
Home Team To Score In 1st Half79.30% Make Bet
Over 2.5 Goals72.90% Make Bet
Away Team To Score In 2nd Half67.80% Make Bet
Over 2.5 BTTS67.70% Make Bet
Both Teams Not To Score In 1st Half63.30% Make Bet
Home Team To Win65.50% Make Bet
Both Teams Not To Score In 2nd Half61.00% Make Bet
Over 1.5 Goals HT59.40% Make Bet
Over 3.5 Goals59.10% Make Bet
Away Team Not To Score In 1st Half58.70% Make Bet
Avg. Total Goals5.05% Make Bet
Avg. Goals Scored3.05% Make Bet
Avg. Conceded Goals2.80% Make Bet

Prediction Analysis

Over 1.5 Goals

With a probability of 98.30%, this bet is highly favored, indicating an expectation for at least two goals to be scored in the match. Given the attacking prowess of both teams, this outcome seems almost certain.

Home Team To Score In 2nd Half

The prediction stands at 91.70%, suggesting Tromsdalen is likely to find the back of the net after halftime. This could be due to their strategic adjustments and increased pressure as the game progresses.

Over 0.5 Goals HT

With an 84.00% likelihood, scoring is expected in the first half, pointing to an aggressive start from both sides.

Both Teams To Score

This has a probability of 77.50%, indicating that both teams are expected to breach each other’s defenses, contributing to a lively match atmosphere.

Home Team To Score In 1st Half

At 80.50%, there’s a strong chance Tromsdalen will score early, setting the tone for their performance.

Over 2.5 Goals

The prediction of 71.60% suggests a high-scoring affair, aligning with the overall offensive trends of both teams.

Away Team To Score In 2nd Half

Rana FK is predicted to score in the second half with a probability of 72.10%, indicating their potential comeback strategy.

Over 2.5 BTTS

This also stands at 71.60%, reinforcing expectations for both teams to score multiple times.

Both Teams Not To Score In 1st Half

With a probability of only 64.70%, it’s less likely that neither team will score early on, suggesting an active start is more probable.

Home Team To Win

Tromsdalen has a fair chance of winning with a probability of 67.20%, reflecting their home advantage and current form.

Both Teams Not To Score In 2nd Half

This scenario has a lower probability at 60.20%, implying continued scoring is expected as the match progresses.

Over 1.5 Goals HT

The likelihood here is at 60.40%, indicating that at least two goals are expected by halftime, aligning with aggressive playstyles.

Over 3.5 Goals

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{Large textbf{Gabriel Garcia}}\[1em]
{large texttt{[email protected]} — url{https://github.com/gabriel-garcia} — url{https://www.linkedin.com/in/gabriel-garcia-66b52138/}}
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I am a computer science graduate student with experience in data analysis and software engineering.
I am particularly interested in using machine learning techniques for predictive modeling.

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item textbf{PhD in Computer Science}, University of California San Diego (2019–present)
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item Advisor: Dr. Simon Duquenne
item Concentrations: Machine Learning and Distributed Computing
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item textbf{MSc in Computer Science}, University of California San Diego (2017–2019)
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item GPA: textbf{4/4} (cumulative)
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item textbf{BSc in Computer Science}, Universidad de Los Andes (2012–2017)
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item GPA: textbf{4/5} (cumulative)
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item textbf{Exchange Program}, University College London (2015–2016)
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item Concentration: Machine Learning
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