Statistics / Football / Hungary. NB I

Hungary Hungary NB I Statistics (18)

Predictions

NB I 2025/26 Season Overview

07-25
100%
05-16
  • League goals trend: Average goals per match 3.02
  • Home win rate: About 40%
  • Away win rate: About 35%
  • BTTS rate (both teams to score): About 60%
  • Over 2.5 average hit rate: About 60%
  • Most attacking teams: Ferencvarosi TC
  • Best defensive teams: Gyori ETO FC
May 16
15:15
Ferencvarosi TC Ferencvarosi TC
Zalaegerszegi TE Zalaegerszegi TE
47%
May 16
15:15
Debreceni VSC Debreceni VSC
Ujpest Ujpest
79%
May 16
15:15
Diosgyori VTK Diosgyori VTK
Paks Paks
52%
May 16
15:15
Kisvarda FC Kisvarda FC
Gyori ETO FC Gyori ETO FC
69%
May 15
18:00
Puskas Academy Puskas Academy
MTK Budapest MTK Budapest
60%
May 15
15:45
Nyiregyhaza Nyiregyhaza
Kazincbarcikai Kazincbarcikai
63%
May 03
14:00
Ujpest Ujpest
Ferencvarosi TC Ferencvarosi TC
27%
May 03
11:30
Paks Paks
Debreceni VSC Debreceni VSC
27%
May 02
17:15
Gyori ETO FC Gyori ETO FC
Diosgyori VTK Diosgyori VTK
36%
May 02
14:00
Kazincbarcikai Kazincbarcikai
Kisvarda FC Kisvarda FC
81%
May 02
11:00
MTK Budapest MTK Budapest
Nyiregyhaza Nyiregyhaza
91%
May 01
18:00
Zalaegerszegi TE Zalaegerszegi TE
Puskas Academy Puskas Academy
50%
Apr 26
17:30
Debreceni VSC Debreceni VSC
Gyori ETO FC Gyori ETO FC
82%
Apr 26
15:00
Ferencvarosi TC Ferencvarosi TC
Paks Paks
68%
Apr 25
17:30
Nyiregyhaza Nyiregyhaza
Zalaegerszegi TE Zalaegerszegi TE
80%
Apr 25
15:00
Puskas Academy Puskas Academy
Ujpest Ujpest
61%
Apr 25
12:30
Kisvarda FC Kisvarda FC
Diosgyori VTK Diosgyori VTK
75%
Apr 24
18:00
Kazincbarcikai Kazincbarcikai
MTK Budapest MTK Budapest
48%

Hungary NB I Betting & Prediction Guides

Want to understand how AI identifies value in Hungary NB I matches? Explore our strategy guides:

NB I Predictions FAQ

Q1: How do upset patterns and odds ranges in the Hungary NB I 2025/26 season differ from typical European top-flight competitions?
Hungary NB I is structurally unique because it lacks the traditional home-field dominance seen in most European leagues. With a home win rate of just 37% trailing behind a 39% away win rate, the typical "home favorite" bias is completely inverted. This creates a landscape where visiting teams are statistically more likely to secure three points than their hosts, a rarity that challenges standard pricing and creates frequent value on the road.

The 3.07 goals per game average suggests that even when favorites struggle, they do so in high-scoring affairs. In this environment, "upsets" aren't just about defensive grit but about away teams out-gunning their hosts. While probability never guarantees a specific result, the narrow gap between home and away success means risk management is essential when navigating these volatile moneyline markets.
Q2: What defines the Over/Under and BTTS structure in the Hungary NB I during the 2025/26 campaign?
Hungary NB I is structurally more explosive than its regional neighbors, characterized by a staggering 61% BTTS rate. While typical leagues often see defensive caginess, the 2025/26 season thrives on end-to-end volatility. With 60% of matches finishing Over 2.5 goals, the league sits among the most reliably high-scoring competitions in Europe. This 3.07 goals-per-game average ensures that goal-based markets are rarely priced for low-scoring stalemates or defensive masterclasses.

This statistical profile suggests that clean sheets are a luxury, not a standard. Analysts should prioritize offensive metrics over defensive reputation, as the high BTTS frequency indicates that even bottom-table sides find the net regularly. However, since probability does not equate to certainty, maintaining a focus on long-term data trends is necessary to navigate these high-scoring outcomes safely without over-committing to any single match.
Q3: How does the specific statistical profile of the Hungary NB I 2025/26 season shape the odds structure for analytical models?
Because Hungary NB I features a 39% away win rate that exceeds the 37% home win rate, the odds landscape is fundamentally different from leagues with a strong home bias. This inversion compresses the spreads, often leading to inflated prices on home teams that the data suggests they haven't earned. When combined with a 60% Over 2.5 rate, the market must account for high-scoring volatility that often favors the visiting side's counter-attacking efficiency.

This 3.07 goals-per-game environment means that total goals lines are frequently pushed higher, yet the 61% BTTS rate keeps "Both Teams to Score" prices relatively short. Models find edges by identifying matchups where the away-side's scoring consistency outweighs the nominal home advantage. Success relies on understanding these specific data fingerprints, though disciplined risk management remains vital as no statistical trend offers a guaranteed outcome.
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