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A Lyga Lithuania Prediction Models

2026

Flat Betting Model

Matches w/ Odds

$10

Stake Per Bet

+30.18%

Best: Under 2.5

-23.97%

Worst: BTTS Yes

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 A Lyga Lithuania. 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	40	15	37.5%	$400	$311.7	−$88.30	-22.08%	2	6
Draw Bet	40	11	27.5%	$400	$399.7	−$0.30	-0.08%	2	7
Away Bet	40	14	35%	$400	$375	−$25.00	-6.25%	2	4
Over 2.5	38	17	44.74%	$380	$321.7	−$58.30	-15.34%	4	4
Under 2.5	38	21	55.26%	$380	$494.7	+$114.70	+30.18%	4	4
BTTS Yes	40	17	42.5%	$400	$304.1	−$95.90	-23.97%	3	3
Home Favorite	23	12	52.17%	$230	$202.6	−$27.40	-11.91%	5	4
Away Underdog	14	3	21.43%	$140	$138.2	−$1.80	-1.29%	1	6
Favorite	40	20	50%	$400	$350.3	−$49.70	-12.42%	3	4
Underdog	40	9	22.5%	$400	$336.4	−$63.60	-15.9%	2	9

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	40	−$88.30	-22.08%	−$15.77	-56.36%	−$55.55	-13.54%
Draw Bet	40	−$0.30	-0.08%	−$9.61	-69.24%	+$13.67	+3.43%
Away Bet	40	−$25.00	-6.25%	−$15.32	-8.07%	+$0.46	+0.11%
Over 2.5	38	−$58.30	-15.34%	−$0.92	-100%	−$70.61	-18%
Under 2.5	38	+$114.70	+30.18%	+$69.23	+21.09%	+$108.82	+27.66%
BTTS Yes	40	−$95.90	-23.97%	−$8.80	-100%	−$96.16	-23.76%
Home Favorite	23	−$27.40	-11.91%	−$8.23	-48.04%	−$13.05	-5.64%
Away Underdog	14	−$1.80	-1.29%	−$15.17	-53.74%	+$0.95	+0.7%
Favorite	40	−$49.70	-12.42%	−$38.26	-79.34%	−$31.74	-7.82%
Underdog	40	−$63.60	-15.9%	−$26.54	-78.5%	−$31.27	-7.5%

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
Panevėžys	9	5	55.56%	+$116.50	+129.44%
TransINVEST Vilnius	9	5	55.56%	+$21.20	+23.56%
Sūduva	10	5	50%	+$7.80	+7.8%
Kauno Žalgiris	9	6	66.67%	+$6.20	+6.89%
Riteriai	0	0	0%	$0.00	0%
Žalgiris	10	5	50%	−$16.80	-16.8%
Banga	9	2	22.22%	−$33.20	-36.89%
Džiugas Telšiai	9	1	11.11%	−$65.00	-72.22%
Hegelmann	10	0	0%	−$100.00	-100%
FA Šiauliai	5	0	0%	−$50.00	-100%

PPG Model

Teams

1.3

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 A Lyga Lithuania. 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)	38	18	47.37%	−$34.70	-9.13%
PPG Home Pick	15	7	46.67%	−$41.50	-27.67%
PPG Away Pick	23	11	47.83%	+$6.80	+2.96%
WPPG Favorite (1×2)	38	18	47.37%	−$53.90	-14.18%
PPG Value (fair < market)	40	7	17.5%	−$209.60	-52.4%

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)	38	−$34.70	-9.13%	−$1.23	-1.83%	−$22.80	-5.49%
PPG Home Pick	15	−$41.50	-27.67%	+$2.25	+55.56%	−$31.29	-21.46%
PPG Away Pick	23	+$6.80	+2.96%	−$21.07	-31.49%	+$20.51	+8%
WPPG Favorite (1×2)	38	−$53.90	-14.18%	−$10.26	-14.93%	−$35.45	-8.46%
PPG Value (fair < market)	40	−$209.60	-52.4%	−$2.41	-100%	−$198.86	-46.92%

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	✓
26 Oct	Kauno Žalgiris vs Žalgiris	Kauno Žalgiris	46.79%	2.14	0 – 0	✗
25 Oct	Džiugas Telšiai vs Panevėžys	Džiugas Telšiai	45.45%	2.2	2 – 1	✓
25 Oct	Banga vs FA Šiauliai	Banga	66.63%	1.5	0 – 0	✗
24 Oct	TransINVEST Vilnius vs Hegelmann	TransINVEST Vilnius	62.48%	1.6	2 – 0	✓
19 Oct	Sūduva vs Kauno Žalgiris	Sūduva	41.97%	2.38	0 – 1	✗

Upcoming Fixtures — PPG Predictions

Win probabilities for upcoming matches based on current PPG ratings

Date	Match	PPG Pick	Prob	Fair Odds
31 Oct	Panevėžys vs TransINVEST Vilnius	TransINVEST Vilnius	41.17%	2.43
31 Oct	FA Šiauliai vs Džiugas Telšiai	***	0%	0
31 Oct	Hegelmann vs Kauno Žalgiris	🔒 Login or register for free to see predictions data.
01 Nov	Sūduva vs Banga
07 Nov	Banga vs Žalgiris

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
1Kauno Žalgiris	1.91	1.88	1.93	2	+0.61
2Sūduva	1.75	2	1.53	1.36	+0.45
3TransINVEST Vilnius	1.72	1.69	1.75	1.91	+0.42
4Žalgiris	1.67	2	1.31	1.86	+0.37
5Džiugas Telšiai	1.5	1.65	1.33	1.17	+0.20
6Banga	1.5	1.44	1.56	1.21	+0.20
7Panevėžys	1.28	1.53	1.06	1.44	-0.02
8Hegelmann	0.84	1	0.69	0.55	-0.46
9FA Šiauliai	0.69	0.88	0.5	0.52	-0.61
10Riteriai	0.18	0.25	0.11	0.11	-1.12

PPG vs WPPG — Biggest Divergence

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

Sūduva

PPG: 1.75WPPG: 1.36Gap: ↓ 0.39

Recent form declining — WPPG dropping below season PPG

Džiugas Telšiai

PPG: 1.5WPPG: 1.17Gap: ↓ 0.33

Recent form declining — WPPG dropping below season PPG

Banga

PPG: 1.5WPPG: 1.21Gap: ↓ 0.29

Recent form declining — WPPG dropping below season PPG

Hegelmann

PPG: 0.84WPPG: 0.55Gap: ↓ 0.29

Recent form declining — WPPG dropping below season PPG

Žalgiris

PPG: 1.67WPPG: 1.86Gap: ↑ 0.19

Recent form better than season average — WPPG rising

Worked Example — Kauno Žalgiris vs Žalgiris

P(Kauno Žalgiris) = 1.94 / (1.94+1.69) × 1.08

= 0.534 × 1.08 = 46.79% → Fair odds 2.14

P(Draw) = 0.268 × (1 − |diff|)

= 23.35% → Fair odds 4.28

P(Žalgiris) = 1 − 46.79% − 23.35%

= 29.86% → Fair odds 3.35

Poisson / Correct Score

Select Match

1.18

Home xG (λ)

1.73

Away xG (λ)

2.91

Total E[goals]

1.46

League Avg Home

1.19

League Avg Away

Dixon-Coles Score Matrix — Panevėžys vs TransINVEST Vilnius

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	6.9%	8.0%	8.2%	4.7%	2.0%	0.7%	0.2%
1	5.0%	12.6%	9.6%	5.6%	2.4%	0.8%	0.2%
2	3.8%	6.6%	5.7%	3.3%	1.4%	0.5%	0.1%
3	1.5%	2.6%	2.2%	1.3%	0.6%	0.2%	0.1%
4	0.4%	0.8%	0.7%	0.4%	0.2%	0.1%	0.0%
5	0.1%	0.2%	0.2%	0.1%	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

24.62%

Fair odds: 4.06

Draw

26.66%

Fair odds: 3.75

Away Win

48.72%

Fair odds: 2.05

Over 0.593.09%/ Under 6.91%Fair: 1.07

Over 1.580.1%/ Under 19.9%Fair: 1.25

Over 2.555.53%/ Under 44.47%Fair: 1.8

Over 3.533.11%/ Under 66.89%Fair: 3.02

Over 4.516.79%/ Under 83.21%Fair: 5.95

BTTS Yes58.41%Fair: 1.71

BTTS No41.59%Fair: 2.4

Correct Score — Top 12

11-1

12.6%D

21-2

9.64%A

30-2

8.17%A

40-1

8%A

50-0

6.91%D

62-1

6.58%H

72-2

5.69%D

81-3

5.56%A

91-0

4.99%H

100-3

4.71%A

112-0

3.8%H

122-3

3.28%A

Dixon-Coles vs Plain Poisson

Where the low-score correction adds value

Plain Poisson

P(0-0) = 5.5%

P(1-0) = 6.4%

P(0-1) = 9.4%

P(1-1) = 11.1%

✗ Underestimates 0-0, 1-0, 0-1

Dixon-Coles (ρ correction)

P(0-0) = 6.9% (+1.5%)

P(1-0) = 5.0% (-1.4%)

P(0-1) = 8.0% (-1.4%)

P(1-1) = 12.6% (+1.5%)

✓ 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%)	34	11	32.35%	−$66.20	-19.47%
DC Home Pick (>50%)	14	8	57.14%	−$11.50	-8.21%
DC Away Pick (>50%)	7	5	71.43%	+$34.40	+49.14%
DC Draw (>28%)	16	3	18.75%	−$57.50	-35.94%
DC Over 2.5 Value	11	6	54.55%	+$0.10	+0.09%
DC BTTS Value	7	3	42.86%	−$16.00	-22.86%

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%)	34	−$66.20	-19.47%	−$21.09	-47.88%	−$51.05	-14.87%
DC Home Pick (>50%)	14	−$11.50	-8.21%	+$8.99	+88.92%	−$8.50	-6.24%
DC Away Pick (>50%)	7	+$34.40	+49.14%	−$12.86	-100%	+$22.20	+27%
DC Draw (>28%)	16	−$57.50	-35.94%	−$2.47	-100%	−$55.90	-34.53%
DC Over 2.5 Value	11	+$0.10	+0.09%	$0.00	0%	+$1.96	+1.77%
DC BTTS Value	7	−$16.00	-22.86%	$0.00	0%	−$15.14	-21.66%

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
Kauno Žalgiris	1.53	0.44	1.4	0.55	17	15
TransINVEST Vilnius	0.98	0.79	1.73	0.98	16	16
Žalgiris	1.53	1.14	0.74	0.6	17	16
Sūduva	1.05	0.39	1.19	0.93	15	17
Džiugas Telšiai	1.05	1.04	1.01	1.05	17	15
Banga	0.94	0.95	1.05	0.51	16	16
Panevėžys	0.82	0.84	0.94	1.29	15	17
Hegelmann	0.81	1.16	0.68	1.37	16	16
FA Šiauliai	0.6	1.68	0.68	1.16	16	16
Riteriai	0.17	2.1	0.28	1.9	8	9

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.

1Kauno Žalgiris

1612

2Sūduva

1586

3Žalgiris

1579

4TransINVEST Vilnius

1574

5Banga

1515

6Džiugas Telšiai

1505

7Panevėžys

1496

8Hegelmann

1422

9FA Šiauliai

1370

10Riteriai

1340

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	Kauno Žalgiris vs Riteriai

Elo Rating History — Top 6

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

Kauno ŽalgirisSūduvaŽalgirisTransINVEST VilniusBangaDžiugas Telšiai

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	Kauno Žalgiris	1612	1617	+112	32	17	10	5
2	Sūduva	1586	1651	+86	32	15	11	6
3	Žalgiris	1579	1579	+79	33	16	7	10
4	TransINVEST Vilnius	1574	1574	+74	32	16	7	9
5	Banga	1515	1580	+15	32	13	9	10
6	Džiugas Telšiai	1505	1566	+5	32	13	9	10
7	Panevėžys	1496	1510	-4	32	12	5	15
8	Hegelmann	1422	1500	-78	32	4	15	13
9	FA Šiauliai	1370	1506	-130	32	4	10	18
10	Riteriai	1340	1500	-160	17	0	3	14

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%)	30	5	17%	−$106.50	-35.5%
Elo Favourite	40	17	43%	−$93.60	-23.4%
Elo Home Pick (>55%)	10	5	50%	−$30.90	-30.9%
Elo Away Pick (>50%)	3	2	67%	−$0.10	-0.33%
Elo Draw (>28%)	15	3	20%	−$44.60	-29.73%

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%)	30	−$106.50	-35.5%	−$4.60	-100%	−$94.62	-30.14%
Elo Favourite	40	−$93.60	-23.4%	−$23.79	-75.5%	−$62.82	-15.26%
Elo Home Pick (>55%)	10	−$30.90	-30.9%	−$3.88	-100%	−$19.59	-19.79%
Elo Away Pick (>50%)	3	−$0.10	-0.33%	$0.00	0%	+$1.18	+3.75%
Elo Draw (>28%)	15	−$44.60	-29.73%	$0.00	0%	−$45.38	-29.61%

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.

A Lyga Lithuania 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 — Kauno Žalgiris vs Žalgiris

Poisson / Correct Score

Select Match

Dixon-Coles Score Matrix — Panevėžys vs TransINVEST Vilnius

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