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NB I Hungary Prediction Models

2026/2027

Flat Betting Model

Matches w/ Odds

$10

Stake Per Bet

+16.65%

Best: Under 2.5

-62.25%

Worst: Away Underdog

Odds Range Filter

1.0

10.0

Use minimum and maximum odds selection tool to identify the most profitable ranges for the Flat Betting football prediction model for NB I Hungary. After each change on the odds range, the system filters qualifying bets and recalculates profits and losses based on those selections.

Market ROI Summary

Flat $10 stake on every match from start to end of season. Profit/loss and ROI per market.

Market	Bets	Wins	Win %	Staked	Return	P&L	ROI	Best Str.	Worst Str.
Home Bet	58	23	39.66%	$580	$502.5	−$77.50	-13.36%	2	3
Draw Bet	58	15	25.86%	$580	$609.3	+$29.30	+5.05%	3	6
Away Bet	58	20	34.48%	$580	$572.3	−$7.70	-1.33%	3	8
Over 2.5	57	30	52.63%	$570	$494.4	−$75.60	-13.26%	4	5
Under 2.5	57	27	47.37%	$570	$664.9	+$94.90	+16.65%	5	4
BTTS Yes	58	34	58.62%	$580	$533.9	−$46.10	-7.95%	6	3
Home Favorite	43	20	46.51%	$430	$412.3	−$17.70	-4.12%	3	3
Away Underdog	12	1	8.33%	$120	$45.3	−$74.70	-62.25%	1	11
Favorite	58	26	44.83%	$580	$545.1	−$34.90	-6.02%	3	4
Underdog	58	17	29.31%	$580	$529.7	−$50.30	-8.67%	3	10

Staking Plan Comparison

Same bets, different stake sizing. Flat = $10 every bet. Kelly ¼ = stake based on rolling edge estimate (quarter-Kelly for safety). Confidence = stake proportional to implied probability (more on favorites, less on longshots).

Market	Bets	Flat P&L	Flat ROI	Kelly ¼ P&L	Kelly ¼ ROI	Conf P&L	Conf ROI
Home Bet	58	−$77.50	-13.36%	−$39.74	-54.79%	−$67.64	-11.45%
Draw Bet	58	+$29.30	+5.05%	+$8.12	+44.74%	−$6.67	-1.16%
Away Bet	58	−$7.70	-1.33%	−$37.06	-80.93%	+$8.08	+1.35%
Over 2.5	57	−$75.60	-13.26%	−$7.39	-8.09%	−$81.66	-13.55%
Under 2.5	57	+$94.90	+16.65%	+$0.78	+1.53%	+$96.97	+17.1%
BTTS Yes	58	−$46.10	-7.95%	+$2.92	+18.67%	−$50.79	-8.51%
Home Favorite	43	−$17.70	-4.12%	−$17.49	-14.09%	−$28.99	-6.63%
Away Underdog	12	−$74.70	-62.25%	−$1.67	-100%	−$75.03	-62.35%
Favorite	58	−$34.90	-6.02%	−$16.59	-10.83%	−$50.61	-8.46%
Underdog	58	−$50.30	-8.67%	−$15.09	-94.61%	+$0.46	+0.08%

Staking Methods

Flat Stake:: Fixed $10 on every qualifying bet regardless of odds or edge.
Kelly ¼:: Stake = bankroll × (edge / (odds−1)) / 4. Uses rolling win rate as probability estimate. Grows bankroll when winning, shrinks when losing.
Confidence-weighted:: Stake = (implied prob / rolling avg implied prob) × $10. Bets more on favorites, less on longshots. Uses your previous bets' average to calculate each stake — applicable in real time.

Flat $10 on this team's Win result in every match. Sorted by ROI.

Team	Bets	Wins	Win %	P&L	ROI
Puskás	10	6	60%	+$59.30	+59.3%
Győri ETO	10	6	60%	+$37.80	+37.8%
Debrecen	10	4	40%	+$0.80	+0.8%
Paks	9	4	44.44%	−$1.80	-2%
Újpest	10	4	40%	−$8.90	-8.9%
Zalaegerszeg	10	3	30%	−$9.80	-9.8%
Vasas	9	3	33.33%	−$14.00	-15.56%
Kisvárda	10	2	20%	−$18.60	-18.6%
Ferencváros	9	4	44.44%	−$17.30	-19.22%
Honvéd	8	2	25%	−$26.70	-33.38%
MTK	11	3	27.27%	−$41.80	-38%
Nyíregyháza Spartacus	10	2	20%	−$44.20	-44.2%

PPG Model

Teams

1.37

League Avg PPG

1.08

Home Factor

λ=0.85

WPPG Decay

Odds Range Filter

1.0

10.0

Use minimum and maximum odds selection tool to identify the most profitable ranges for the PPG football prediction model for NB I Hungary. After each change on the odds range, the system filters qualifying bets and recalculates profits and losses based on those selections.

PPG / WPPG Betting ROI

Backtested ROI betting $10 using incremental PPG — seeded with previous season data, blending into current-season results.

Strategy	Bets	Wins	Win %	P&L	ROI
PPG Favorite (1×2)	46	22	47.83%	+$52.20	+11.35%
PPG Home Pick	25	13	52%	+$20.20	+8.08%
PPG Away Pick	21	9	42.86%	+$32.00	+15.24%
WPPG Favorite (1×2)	49	22	44.9%	+$26.70	+5.45%
PPG Value (fair < market)	50	17	34%	−$102.30	-20.46%

Strategy Guide

PPG Favorite:: Backs the team with the higher PPG to win, whether home or away.
PPG Home Pick:: Bets on the home team only when PPG rates them higher than the visitor.
PPG Away Pick:: Bets on the away team only when PPG rates them higher than the home side.
WPPG Favorite:: Same as PPG Favorite but uses Weighted PPG (recent form weighted more heavily).
PPG Value:: Only bets when the PPG fair odds are lower than the bookmaker's odds — positive expected value. E.g. fair odds 1.80 vs bookmaker 2.10 = value bet.

Staking Plan Comparison

Same PPG bets, different stake sizing. Flat = $10 every bet. Kelly ¼ = stake based on rolling edge estimate. Confidence = stake proportional to implied probability.

Strategy	Bets	Flat P&L	Flat ROI	Kelly ¼ P&L	Kelly ¼ ROI	Conf P&L	Conf ROI
PPG Favorite (1×2)	46	+$52.20	+11.35%	+$22.53	+28.96%	+$31.52	+6.45%
PPG Home Pick	25	+$20.20	+8.08%	−$0.13	-0.36%	+$7.50	+2.74%
PPG Away Pick	21	+$32.00	+15.24%	+$9.58	+34.77%	+$19.71	+9.13%
WPPG Favorite (1×2)	49	+$26.70	+5.45%	+$17.18	+43.08%	+$8.40	+1.6%
PPG Value (fair < market)	50	−$102.30	-20.46%	−$29.16	-89.23%	−$55.43	-10.97%

Staking Methods

Flat Stake:: Fixed $10 on every qualifying bet regardless of odds or edge.
Kelly ¼:: Stake = bankroll × (edge / (odds−1)) / 4. Uses rolling win rate as probability estimate.
Confidence-weighted:: Stake = (implied prob / rolling avg implied prob) × $10. Bets more on favorites, less on longshots. Uses previous bets' average — applicable in real time.

Recent Results — PPG Predictions vs Actual

How PPG predictions compared to actual match results

Date	Match	PPG Pick	Prob	Fair Odds	Result	✓
25 Oct	Ferencváros vs MTK	Ferencváros	54.12%	1.85	5 – 0	✓
25 Oct	Puskás vs Nyíregyháza Spartacus	Puskás	78.49%	1.27	1 – 2	✗
25 Oct	Vasas vs Paks	Vasas	50.1%	2	0 – 2	✗
24 Oct	Zalaegerszeg vs Kisvárda	Zalaegerszeg	39.73%	2.52	1 – 1	✗
24 Oct	Győri ETO vs Újpest	Győri ETO	46.36%	2.16	1 – 0	✓

Upcoming Fixtures — PPG Predictions

Win probabilities for upcoming matches based on current PPG ratings

Date	Match	PPG Pick	Prob	Fair Odds
31 Oct	Honvéd vs Kisvárda	Honvéd	40.99%	2.44
31 Oct	Zalaegerszeg vs MTK	***	0%	0
31 Oct	Győri ETO vs Vasas	🔒 Login or register for free to see predictions data.
01 Nov	Puskás vs Debrecen
01 Nov	Ferencváros vs Paks

PPG Ratings — All Teams

Points Per Game overall, home, away, and weighted (WPPG with λ=0.85 decay). Click column headers to sort.

Team	PPG ↓	H-PPG	A-PPG	WPPG	vs Avg
1Győri ETO	2	2	2	2.16	+0.63
2Ferencváros	1.89	1.5	2.2	1.84	+0.52
3Puskás	1.8	1.2	2.4	1.77	+0.43
4Debrecen	1.6	1.6	1.6	1.83	+0.23
5Újpest	1.5	2	1	1.17	+0.13
6Vasas	1.4	1.4	1.4	1.15	+0.03
7Paks	1.4	1.4	1.4	1.65	+0.03
8Kisvárda	1.1	0.6	1.6	1.06	-0.27
9MTK	1.09	1.5	0.6	0.95	-0.28
10Honvéd	1	1	1	1.01	-0.37
11Zalaegerszeg	0.91	2	0	0.98	-0.46
12Nyíregyháza Spartacus	0.8	1.25	0.5	0.94	-0.57

PPG vs WPPG — Biggest Divergence

Teams where PPG and Weighted PPG disagree most — indicates recent form shift

Újpest

PPG: 1.5WPPG: 1.17Gap: ↓ 0.33

Recent form declining — WPPG dropping below season PPG

Vasas

PPG: 1.4WPPG: 1.15Gap: ↓ 0.25

Recent form declining — WPPG dropping below season PPG

Paks

PPG: 1.4WPPG: 1.65Gap: ↑ 0.25

Recent form better than season average — WPPG rising

Debrecen

PPG: 1.6WPPG: 1.83Gap: ↑ 0.23

Recent form better than season average — WPPG rising

Győri ETO

PPG: 2WPPG: 2.16Gap: ↑ 0.16

Recent form better than season average — WPPG rising

Worked Example — Ferencváros vs MTK

P(Ferencváros) = 1.75 / (1.75+1.2) × 1.08

= 0.593 × 1.08 = 54.12% → Fair odds 1.85

P(Draw) = 0.268 × (1 − |diff|)

= 18.38% → Fair odds 5.44

P(MTK) = 1 − 54.12% − 18.38%

= 27.5% → Fair odds 3.64

Poisson / Correct Score

Select Match

0.71

Home xG (λ)

1.75

Away xG (λ)

2.46

Total E[goals]

1.68

League Avg Home

1.28

League Avg Away

Dixon-Coles Score Matrix — Honvéd vs Kisvárda

30 Oct · Each cell shows the probability of that exact scoreline. Dixon-Coles corrected (ρ = -0.13). · Upcoming

H \ A	0	1	2	3	4	5	6
0	9.9%	13.6%	13.1%	7.7%	3.4%	1.2%	0.3%
1	4.7%	12.0%	9.3%	5.4%	2.4%	0.8%	0.2%
2	2.2%	3.8%	3.3%	1.9%	0.8%	0.3%	0.1%
3	0.5%	0.9%	0.8%	0.5%	0.2%	0.1%	0.0%
4	0.1%	0.2%	0.1%	0.1%	0.0%	0.0%	0.0%
5	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%
6	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%

Most likely High Medium Low

Derived Markets

Home Win

13.37%

Fair odds: 7.48

Draw

25.77%

Fair odds: 3.88

Away Win

60.87%

Fair odds: 1.64

Over 0.590.05%/ Under 9.95%Fair: 1.11

Over 1.571.76%/ Under 28.24%Fair: 1.39

Over 2.544.47%/ Under 55.53%Fair: 2.25

Over 3.523.22%/ Under 76.78%Fair: 4.31

Over 4.510.16%/ Under 89.84%Fair: 9.85

BTTS Yes43.36%Fair: 2.31

BTTS No56.64%Fair: 1.77

Correct Score — Top 12

10-1

13.6%A

20-2

13.11%A

31-1

12.02%D

40-0

9.95%D

51-2

9.31%A

60-3

7.65%A

71-3

5.43%A

81-0

4.7%H

92-1

3.78%H

100-4

3.35%A

112-2

3.3%D

121-4

2.38%A

Dixon-Coles vs Plain Poisson

Where the low-score correction adds value

Plain Poisson

P(0-0) = 8.5%

P(1-0) = 6.1%

P(0-1) = 14.9%

P(1-1) = 10.6%

✗ Underestimates 0-0, 1-0, 0-1

Dixon-Coles (ρ correction)

P(0-0) = 9.9% (+1.4%)

P(1-0) = 4.7% (-1.4%)

P(0-1) = 13.6% (-1.3%)

P(1-1) = 12.0% (+1.4%)

✓ Fixes low-score underestimation

💡 Why does this matter? Draws in football are dominated by 0-0 and 1-1. Plain Poisson underprices these by 15–20%. Dixon-Coles corrects this, generating better ROI on draw markets.

Dixon-Coles Betting ROI

Backtested ROI using incremental Poisson/Dixon-Coles model — xG computed only from matches played before each bet.

Strategy	Bets	Wins	Win %	P&L	ROI
DC Value (1X2 edge > 3%)	31	15	48.39%	+$108.60	+35.03%
DC Home Pick (>50%)	11	7	63.64%	+$38.40	+34.91%
DC Away Pick (>50%)	6	1	16.67%	−$40.30	-67.17%
DC Draw (>28%)	12	4	33.33%	+$48.20	+40.17%
DC Over 2.5 Value	12	6	50%	−$20.10	-16.75%
DC BTTS Value	4	2	50%	−$9.30	-23.25%

Staking Plan Comparison

Same Dixon-Coles bets, different stake sizing. Flat = $10 every bet. Kelly ¼ and Confidence-weighted alternatives.

Strategy	Bets	Flat P&L	Flat ROI	Kelly ¼ P&L	Kelly ¼ ROI	Conf P&L	Conf ROI
DC Value (1X2 edge > 3%)	31	+$108.60	+35.03%	+$55.62	+16.33%	+$67.50	+22.24%
DC Home Pick (>50%)	11	+$38.40	+34.91%	+$0.72	+0.69%	+$34.41	+30.64%
DC Away Pick (>50%)	6	−$40.30	-67.17%	$0.00	0%	−$43.79	-68.97%
DC Draw (>28%)	12	+$48.20	+40.17%	+$8.77	+22.33%	+$36.09	+30.97%
DC Over 2.5 Value	12	−$20.10	-16.75%	−$2.20	-19.5%	−$23.80	-18.66%
DC BTTS Value	4	−$9.30	-23.25%	$0.00	0%	−$11.25	-27.08%

Staking Methods

Flat Stake:: Fixed $10 on every qualifying bet regardless of odds or edge.
Kelly ¼:: Stake = bankroll × (edge / (odds−1)) / 4. Uses rolling win rate as probability estimate. Grows bankroll when winning, shrinks when losing.
Confidence-weighted:: Stake = (implied prob / rolling avg implied prob) × $10. Bets more on favorites, less on longshots. Uses your previous bets' average to calculate each stake — applicable in real time.

Team Attack & Defense Strength

Attack/defense strength relative to league average (1.00 = average). Used to derive expected goals (xG) for each match.

Team	Att (H)	Def (H)	Att (A)	Def (A)	H GP	A GP
Debrecen	1.07	1.09	1.41	0.83	5	5
Paks	1.19	1.25	1.25	1.07	5	5
Ferencváros	1.19	0.59	1.25	0.36	4	5
Újpest	1.19	0.94	1.09	0.95	5	5
Győri ETO	1.09	0.78	1.17	0.6	6	4
Vasas	1.07	0.94	1.09	0.83	5	5
MTK	0.99	1.04	0.94	1.67	6	5
Puskás	0.95	1.41	0.94	0.36	5	5
Honvéd	0.71	1.25	1.17	1.19	5	4
Zalaegerszeg	1.43	0.78	0.13	1.69	5	6
Kisvárda	0.48	1.09	1.09	0.6	5	5
Nyíregyháza Spartacus	0.6	0.78	0.78	1.59	4	6

How Poisson Predictions Work

Step 1 — Expected Goals:: Home xG = Home Attack Strength × Away Defense Weakness × League Avg Home Goals. Each team's attack and defense ratings are calculated relative to the league average.
Step 2 — Poisson Formula:: P(k goals) = e⁻λ × λᵏ / k! — models the probability of scoring exactly k goals given the expected goals (λ).
Step 3 — Score Matrix:: Multiply home and away goal probabilities for every combination (0-0 through 6-6) to build a full probability grid for every possible scoreline.
Step 4 — Dixon-Coles:: Apply ρ correction to fix Poisson's underestimation of low-scoring draws (0-0, 1-1, 1-0, 0-1). This is the key improvement over basic Poisson.
Step 5 — Derive Markets:: Sum probabilities from the matrix to derive 1X2, Over/Under, BTTS, and correct score probabilities — then convert to fair odds for value identification.

Elo Rating

Current Elo Ratings

All teams ranked by Elo. Start rating: 1500. K-factor: 32. Home advantage: +65 Elo.

1Ferencváros

1554

2Győri ETO

1551

3Debrecen

1531

4Puskás

1527

5Újpest

1508

6Paks

1506

7Vasas

1491

8Kisvárda

1488

9Honvéd

1470

10MTK

1470

11Nyíregyháza Spartacus

1455

12Zalaegerszeg

1453

Elo → Win Probability Table

How Elo difference translates to win probability.

Elo Diff	P(Higher wins)	Fair Odds	Typical Matchup
0	50.0%	2.00	Evenly matched
50	57.1%	1.75	Mid vs mid-lower
100	64.0%	1.56	Top-8 vs bottom-8
150	70.3%	1.42	Top-4 vs relegation
200	76.0%	1.32	Leader vs bottom half
250	80.8%	1.24	Leader vs bottom 3
300	84.9%	1.18	Ferencváros vs Zalaegerszeg

Elo Rating History — Top 6

How the top 6 teams' Elo ratings evolved across the season.

FerencvárosGyőri ETODebrecenPuskásÚjpestPaks

Elo Ratings — All Teams

Current Elo rating, peak Elo this season, and results. Start rating: 1500.

#	Team	Elo	Peak	Δ	GP	W	D	L
1	Ferencváros	1554	1554	+54	9	4	5	0
2	Győri ETO	1551	1551	+51	10	6	2	2
3	Debrecen	1531	1531	+31	10	4	4	2
4	Puskás	1527	1550	+27	10	6	0	4
5	Újpest	1508	1540	+8	10	4	3	3
6	Paks	1506	1506	+6	10	4	2	4
7	Vasas	1491	1534	-9	10	4	2	4
8	Kisvárda	1488	1519	-12	10	2	5	3
9	Honvéd	1470	1500	-30	9	2	3	4
10	MTK	1470	1515	-30	11	3	3	5
11	Nyíregyháza Spartacus	1455	1500	-45	10	2	2	6
12	Zalaegerszeg	1453	1501	-47	11	3	1	7

Elo Betting ROI

Backtested ROI using incremental Elo ratings — ratings computed from matches played before each bet.

Strategy	Bets	Wins	Win %	P&L	ROI
Elo Value (edge > 3%)	28	7	25%	−$57.80	-20.64%
Elo Favourite	47	17	36%	−$116.40	-24.77%
Elo Home Pick (>55%)	1	0	0%	−$10.00	-100%
Elo Draw (>28%)	15	5	33%	+$44.30	+29.53%

Staking Plan Comparison

Same Elo bets, different stake sizing. Flat = $10 every bet. Kelly ¼ and Confidence-weighted alternatives.

Strategy	Bets	Flat P&L	Flat ROI	Kelly ¼ P&L	Kelly ¼ ROI	Conf P&L	Conf ROI
Elo Value (edge > 3%)	28	−$57.80	-20.64%	−$6.98	-100%	−$31.72	-11.07%
Elo Favourite	47	−$116.40	-24.77%	−$31.93	-98.92%	−$103.48	-20.69%
Elo Home Pick (>55%)	1	−$10.00	-100%	$0.00	0%	−$10.00	-100%
Elo Draw (>28%)	15	+$44.30	+29.53%	+$0.68	+14.26%	+$40.30	+27.09%

Staking Methods

Flat Stake:: Fixed $10 on every qualifying bet regardless of odds or edge.
Kelly ¼:: Stake = bankroll × (edge / (odds−1)) / 4. Uses rolling win rate as probability estimate. Grows bankroll when winning, shrinks when losing.
Confidence-weighted:: Stake = (implied prob / rolling avg implied prob) × $10. Bets more on favorites, less on longshots. Uses your previous bets' average to calculate each stake — applicable in real time.

How Elo Ratings Work

Step 1 — Starting Rating:: Every team starts at 1500. Higher Elo means a stronger team.
Step 2 — Expected Score:: E(A) = 1 / (1 + 10^(R_B − R_A) / 400). If Arsenal is rated 1600 and Wolves is 1450, Arsenal's expected score is 0.71.
Step 3 — Update After Match:: R_new = R_old + K × (S − E), where S is the actual result (1 = win, 0.5 = draw, 0 = loss) and K=32 controls sensitivity.
Step 4 — Home Advantage:: Home team gets +65 Elo boost when calculating expected scores, reflecting the statistical home advantage in football.
Step 5 — Betting:: Convert Elo difference into win/draw/loss probabilities, compare against bookmaker odds, and bet when the model spots value.

Value Scanner

No upcoming matches with odds available. Please check back later.

NB I Hungary Prediction Models

Flat Betting Model

Odds Range Filter

Market ROI Summary

Staking Plan Comparison

By Team Bets

PPG Model

Odds Range Filter

PPG / WPPG Betting ROI

Staking Plan Comparison

Recent Results — PPG Predictions vs Actual

Upcoming Fixtures — PPG Predictions

PPG Ratings — All Teams

PPG vs WPPG — Biggest Divergence

Worked Example — Ferencváros vs MTK

Poisson / Correct Score

Select Match

Dixon-Coles Score Matrix — Honvéd vs Kisvárda

Derived Markets

Correct Score — Top 12

Dixon-Coles vs Plain Poisson

Dixon-Coles Betting ROI

Staking Plan Comparison

Team Attack & Defense Strength

How Poisson Predictions Work

Elo Rating

Current Elo Ratings

Elo → Win Probability Table

Elo Rating History — Top 6

Elo Ratings — All Teams

Elo Betting ROI

Staking Plan Comparison

How Elo Ratings Work

Value Scanner