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BFL Bangladesh Prediction Models

2026/2027

Flat Betting Model

Matches w/ Odds

$10

Stake Per Bet

Best: Home Bet

Worst: Home Bet

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 B League Bangladesh. 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	Win %	Staked	Return	P&L	ROI
Home Bet	0%	$0	$0	$0.00	0%
Draw Bet	0%	$0	$0	$0.00	0%
Away Bet	0%	$0	$0	$0.00	0%
Over 2.5	0%	$0	$0	$0.00	0%
Under 2.5	0%	$0	$0	$0.00	0%
BTTS Yes	0%	$0	$0	$0.00	0%
Home Favorite	0%	$0	$0	$0.00	0%
Away Underdog	0%	$0	$0	$0.00	0%
Favorite	0%	$0	$0	$0.00	0%
Underdog	0%	$0	$0	$0.00	0%

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

Team	Win %	P&L	ROI
Abahani Dhaka	0%	$0.00	0%
Arambagh	0%	$0.00	0%
Brothers Union FC	0%	$0.00	0%
Mohammedan Dhaka	0%	$0.00	0%
Rahmatgonj MFS	0%	$0.00	0%
Bashundhara Kings	0%	$0.00	0%
Bangladesh Police	0%	$0.00	0%
Fortis	0%	$0.00	0%
Dhaka Wanderers	0%	$0.00	0%
Fakirerpool	0%	$0.00	0%
PWD Sports Club	0%	$0.00	0%
City Club	0%	$0.00	0%
Chattogram	0%	$0.00	0%

PPG Model

Teams

1.41

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 B League Bangladesh. After each change on the odds range, the system filters qualifying bets and recalculates profits and losses based on those selections.

Recent Results — PPG Predictions vs Actual

How PPG predictions compared to actual match results

Date	Match	PPG Pick	Prob	Fair Odds	Result	✓
24 Oct	Bashundhara Kings vs Chattogram	Bashundhara Kings	95%	1.05	4 – 2	✓
24 Oct	PWD Sports Club vs Bangladesh Police	Bangladesh Police	68.89%	1.45	0 – 1	✓
24 Oct	Mohammedan Dhaka vs Dhaka Wanderers	Mohammedan Dhaka	95%	1.05	4 – 0	✓
24 Oct	Arambagh vs City Club	City Club	59.45%	1.68	0 – 4	✓
23 Oct	Brothers Union FC vs Abahani Dhaka	Abahani Dhaka	76.21%	1.31	2 – 1	✗

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
1Mohammedan Dhaka	3	3	3	3	+1.59
2Bangladesh Police	2.6	2.33	3	2.54	+1.19
3Bashundhara Kings	2.5	3	2	2.61	+1.09
4Fortis	2.33	2	3	2.34	+0.92
5City Club	2	1.5	2.33	1.98	+0.59
6Abahani Dhaka	1.75	3	1.33	1.67	+0.34
7Rahmatgonj MFS	1.2	1	1.33	1.4	-0.21
8Brothers Union FC	1	1	1	1.2	-0.41
9Fakirerpool	0.75	1	0	0.58	-0.66
10PWD Sports Club	0.6	0.5	1	0.5	-0.81
11Arambagh	0.6	0.67	0.5	0.54	-0.81
12Dhaka Wanderers	0	0	0	0	-1.41
13Chattogram	0	0	0	0	-1.41

PPG vs WPPG — Biggest Divergence

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

Rahmatgonj MFS

PPG: 1.2WPPG: 1.4Gap: ↑ 0.20

Recent form better than season average — WPPG rising

Brothers Union FC

PPG: 1WPPG: 1.2Gap: ↑ 0.20

Recent form better than season average — WPPG rising

Fakirerpool

PPG: 0.75WPPG: 0.58Gap: ↓ 0.17

Recent form declining — WPPG dropping below season PPG

Bashundhara Kings

PPG: 2.5WPPG: 2.61Gap: ↑ 0.11

Recent form better than season average — WPPG rising

PWD Sports Club

PPG: 0.6WPPG: 0.5Gap: ↓ 0.10

Recent form declining — WPPG dropping below season PPG

Worked Example — Bashundhara Kings vs Chattogram

P(Bashundhara Kings) = 2.33 / (2.33+0) × 1.08

= 1.000 × 1.08 = 95% → Fair odds 1.05

P(Draw) = 0.268 × (1 − |diff|)

= 3% → Fair odds 33.33

P(Chattogram) = 1 − 95% − 3%

= 2% → Fair odds 50

Poisson / Correct Score

Select Match

0.85

Home xG (λ)

2.44

Away xG (λ)

3.29

Total E[goals]

2.03

League Avg Home

1.66

League Avg Away

Dixon-Coles Score Matrix — Arambagh vs City Club

23 Oct · Each cell shows the probability of that exact scoreline. Dixon-Coles corrected (ρ = -0.13). Actual result: 0–4

H \ A	0	1	2	3	4	5	6
0	4.8%	8.2%	11.2%	9.1%	5.6%	2.7%	1.1%
1	2.2%	8.8%	9.6%	7.8%	4.7%	2.3%	0.9%
2	1.4%	3.3%	4.1%	3.3%	2.0%	1.0%	0.4%
3	0.4%	0.9%	1.1%	0.9%	0.6%	0.3%	0.1%
4	0.1%	0.2%	0.2%	0.2%	0.1%	0.1%	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

10.25%

Fair odds: 9.76

Draw

18.76%

Fair odds: 5.33

Away Win

71%

Fair odds: 1.41

Over 0.595.21%/ Under 4.79%Fair: 1.05

Over 1.584.83%/ Under 15.17%Fair: 1.18

Over 2.563.39%/ Under 36.61%Fair: 1.58

Over 3.541%/ Under 59%Fair: 2.44

Over 4.522.58%/ Under 77.42%Fair: 4.43

BTTS Yes53.22%Fair: 1.88

BTTS No46.78%Fair: 2.14

Correct Score — Top 12

10-2

11.23%A

21-2

9.55%A

30-3

9.13%A

41-1

8.84%D

50-1

8.19%A

61-3

7.76%A

70-4

5.57%A

80-0

4.79%D

91-4

4.74%A

102-2

4.06%D

112-1

3.33%H

122-3

3.3%A

Dixon-Coles vs Plain Poisson

Where the low-score correction adds value

Plain Poisson

P(0-0) = 3.7%

P(1-0) = 3.2%

P(0-1) = 9.1%

P(1-1) = 7.7%

✗ Underestimates 0-0, 1-0, 0-1

Dixon-Coles (ρ correction)

P(0-0) = 4.8% (+1.1%)

P(1-0) = 2.2% (-1.0%)

P(0-1) = 8.2% (-0.9%)

P(1-1) = 8.8% (+1.1%)

✓ 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.

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
Fortis	1.48	0.61	1.9	0.53	2	1
Bashundhara Kings	2.02	0.57	1.69	0.72	2	2
Mohammedan Dhaka	1.88	0.55	0.73	0.58	2	2
Bangladesh Police	1.21	0.56	0.95	0.27	3	2
City Club	0.83	1.07	1.51	0.75	2	3
Abahani Dhaka	1.37	0.71	1.52	0.53	1	3
Rahmatgonj MFS	0.93	0.61	0.87	1.21	2	3
Brothers Union FC	0.6	1.65	0.73	1.04	3	2
Fakirerpool	0.65	1.6	0.38	1.98	3	1
Chattogram	0.83	1.14	0.73	1.57	1	4
Arambagh	0.41	1.35	0.59	1.31	3	2
Dhaka Wanderers	0.92	1.34	0.6	1.57	1	3
PWD Sports Club	0.29	0.83	0.63	1.01	4	1

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.

1Mohammedan Dhaka

1558

2Bangladesh Police

1553

3Bashundhara Kings

1544

4City Club

1531

5Fortis

1528

6Abahani Dhaka

1516

7Rahmatgonj MFS

1503

8Brothers Union FC

1487

9Arambagh

1469

10Fakirerpool

1463

11PWD Sports Club

1463

12Dhaka Wanderers

1448

13Chattogram

1439

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	Mohammedan Dhaka vs Chattogram

Elo Rating History — Top 6

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

Mohammedan DhakaBangladesh PoliceBashundhara KingsCity ClubFortisAbahani Dhaka

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	Mohammedan Dhaka	1558	1558	+58	4	4	0	0
2	Bangladesh Police	1553	1553	+53	5	4	1	0
3	Bashundhara Kings	1544	1544	+44	4	3	1	0
4	City Club	1531	1532	+31	5	3	1	1
5	Fortis	1528	1528	+28	3	2	1	0
6	Abahani Dhaka	1516	1532	+16	4	2	1	1
7	Rahmatgonj MFS	1503	1503	+3	5	1	3	1
8	Brothers Union FC	1487	1500	-13	5	1	2	2
9	Arambagh	1469	1500	-31	5	0	3	2
10	Fakirerpool	1463	1513	-37	4	1	0	3
11	PWD Sports Club	1463	1500	-38	5	0	3	2
12	Dhaka Wanderers	1448	1500	-52	4	0	0	4
13	Chattogram	1439	1500	-61	5	0	0	5

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

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BFL Bangladesh Prediction Models

Flat Betting Model

Odds Range Filter

Market ROI Summary

By Team Bets

PPG Model

Odds Range Filter

Recent Results — PPG Predictions vs Actual

PPG Ratings — All Teams

PPG vs WPPG — Biggest Divergence

Worked Example — Bashundhara Kings vs Chattogram

Poisson / Correct Score

Select Match

Dixon-Coles Score Matrix — Arambagh vs City Club

Derived Markets

Correct Score — Top 12

Dixon-Coles vs Plain Poisson

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

How Elo Ratings Work

Value Scanner