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Ligue 1 France Prediction Models

2026/2027

Flat Betting Model

Matches w/ Odds

$10

Stake Per Bet

+16.56%

Best: Away Underdog

-18.4%

Worst: 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 Ligue 1 France. 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	72	32	44.44%	$720	$707	−$13.00	-1.81%	8	8
Draw Bet	72	19	26.39%	$720	$742.2	+$22.20	+3.08%	4	14
Away Bet	72	21	29.17%	$720	$637.1	−$82.90	-11.51%	4	8
Over 2.5	72	44	61.11%	$720	$777.5	+$57.50	+7.99%	5	4
Under 2.5	72	28	38.89%	$720	$676.8	−$43.20	-6%	4	5
BTTS Yes	72	45	62.5%	$720	$752.4	+$32.40	+4.5%	7	4
Home Favorite	46	26	56.52%	$460	$502.8	+$42.80	+9.3%	10	6
Away Underdog	25	5	20%	$250	$291.4	+$41.40	+16.56%	2	12
Favorite	72	39	54.17%	$720	$756.6	+$36.60	+5.08%	7	7
Underdog	72	14	19.44%	$720	$587.5	−$132.50	-18.4%	3	14

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	72	−$13.00	-1.81%	−$19.73	-26.89%	+$12.56	+1.73%
Draw Bet	72	+$22.20	+3.08%	−$30.39	-15.48%	+$47.35	+6.5%
Away Bet	72	−$82.90	-11.51%	−$8.59	-5.59%	−$95.87	-12.71%
Over 2.5	72	+$57.50	+7.99%	−$12.46	-8.96%	+$58.21	+7.74%
Under 2.5	72	−$43.20	-6%	−$17.33	-20.3%	−$44.19	-5.92%
BTTS Yes	72	+$32.40	+4.5%	−$15.79	-30.1%	+$33.49	+4.58%
Home Favorite	46	+$42.80	+9.3%	+$18.46	+29.93%	+$29.46	+6.39%
Away Underdog	25	+$41.40	+16.56%	+$4.45	+5.73%	+$37.32	+15.13%
Favorite	72	+$36.60	+5.08%	+$0.69	+0.76%	+$34.98	+4.78%
Underdog	72	−$132.50	-18.4%	−$8.34	-28.97%	−$164.89	-22.31%

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
Monaco	8	4	50%	+$73.90	+92.37%
Lorient	8	3	37.5%	+$62.00	+77.5%
Paris FC	8	4	50%	+$30.40	+38%
Nice	8	3	37.5%	+$13.60	+17%
Rennes	8	5	62.5%	+$8.80	+11%
Auxerre	8	3	37.5%	+$7.00	+8.75%
Lens	8	4	50%	+$4.30	+5.37%
Olympique Lyonnais	8	4	50%	+$2.70	+3.38%
Olympique Marseille	8	4	50%	−$7.90	-9.88%
Lille	8	4	50%	−$10.80	-13.5%
PSG	8	5	62.5%	−$13.20	-16.5%
Angers SCO	8	2	25%	−$15.00	-18.75%
Strasbourg	8	2	25%	−$18.00	-22.5%
Brest	8	2	25%	−$30.70	-38.37%
Troyes	8	1	12.5%	−$32.50	-40.62%
Toulouse	8	2	25%	−$38.30	-47.87%
Le Mans	8	1	12.5%	−$52.20	-65.25%
Le Havre	8	0	0%	−$80.00	-100%

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 Ligue 1 France. 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)	51	20	39.22%	−$42.40	-8.31%
PPG Home Pick	25	11	44%	−$62.00	-24.8%
PPG Away Pick	26	9	34.62%	+$19.60	+7.54%
WPPG Favorite (1×2)	56	23	41.07%	−$32.50	-5.8%
PPG Value (fair < market)	62	24	38.71%	+$31.40	+5.06%

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)	51	−$42.40	-8.31%	+$4.70	+4.09%	−$96.82	-17.24%
PPG Home Pick	25	−$62.00	-24.8%	−$18.77	-100%	−$53.15	-18.35%
PPG Away Pick	26	+$19.60	+7.54%	−$12.25	-12.28%	−$43.88	-16.08%
WPPG Favorite (1×2)	56	−$32.50	-5.8%	−$3.33	-2.66%	−$79.17	-12.86%
PPG Value (fair < market)	62	+$31.40	+5.06%	−$14.37	-8.83%	+$12.39	+1.98%

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	PSG vs Olympique Lyonnais	PSG	42.59%	2.35	2 – 0	✓
25 Oct	Rennes vs Strasbourg	Rennes	61.39%	1.63	3 – 0	✓
25 Oct	Angers SCO vs Lorient	Lorient	47.03%	2.13	0 – 0	✗
25 Oct	Auxerre vs Le Mans	Auxerre	54.98%	1.82	1 – 1	✗
25 Oct	Olympique Marseille vs Le Havre	Olympique Marseille	83.17%	1.2	4 – 3	✓

Upcoming Fixtures — PPG Predictions

Win probabilities for upcoming matches based on current PPG ratings

Date	Match	PPG Pick	Prob	Fair Odds
30 Oct	Le Havre vs PSG	PSG	85.86%	1.16
30 Oct	Lille vs Lens	***	0%	0
31 Oct	Nice vs Rennes	🔒 Login or register for free to see predictions data.
31 Oct	Troyes vs Le Mans
31 Oct	Olympique Lyonnais vs Angers SCO

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
1PSG	2.13	2	2.2	2.44	+0.76
2Rennes	2	2.6	1	1.96	+0.63
3Lille	1.88	2	1.75	1.7	+0.51
4Monaco	1.88	2	1.75	1.55	+0.51
5Paris FC	1.75	2.5	1	1.59	+0.38
6Olympique Lyonnais	1.75	2.5	1	1.56	+0.38
7Lens	1.63	2.25	1	1.9	+0.26
8Olympique Marseille	1.5	1.5	1.5	1.79	+0.13
9Lorient	1.5	1.75	1.25	1.63	+0.13
10Nice	1.38	2	0.75	1.6	+0.01
11Auxerre	1.25	1.75	0.75	1.43	-0.12
12Toulouse	1.25	1	1.5	1.45	-0.12
13Brest	1.13	1	1.25	1.04	-0.24
14Angers SCO	1	0.8	1.33	0.93	-0.37
15Strasbourg	0.88	1.33	0.6	0.62	-0.49
16Le Mans	0.88	1.25	0.5	0.85	-0.49
17Troyes	0.63	0.25	1	0.51	-0.74
18Le Havre	0.25	0.25	0.25	0.19	-1.12

PPG vs WPPG — Biggest Divergence

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

Monaco

PPG: 1.88WPPG: 1.55Gap: ↓ 0.33

Recent form declining — WPPG dropping below season PPG

PSG

PPG: 2.13WPPG: 2.44Gap: ↑ 0.31

Recent form better than season average — WPPG rising

Olympique Marseille

PPG: 1.5WPPG: 1.79Gap: ↑ 0.29

Recent form better than season average — WPPG rising

Lens

PPG: 1.63WPPG: 1.9Gap: ↑ 0.27

Recent form better than season average — WPPG rising

Strasbourg

PPG: 0.88WPPG: 0.62Gap: ↓ 0.26

Recent form declining — WPPG dropping below season PPG

Worked Example — PSG vs Olympique Lyonnais

P(PSG) = 2 / (2+2) × 1.08

= 0.500 × 1.08 = 42.59% → Fair odds 2.35

P(Draw) = 0.268 × (1 − |diff|)

= 26.8% → Fair odds 3.73

P(Olympique Lyonnais) = 1 − 42.59% − 26.8%

= 30.61% → Fair odds 3.27

Poisson / Correct Score

Select Match

0.37

Home xG (λ)

2.22

Away xG (λ)

2.59

Total E[goals]

1.63

League Avg Home

1.35

League Avg Away

Dixon-Coles Score Matrix — Le Havre vs PSG

29 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	8.4%	16.0%	18.6%	13.8%	7.7%	3.4%	1.3%
1	2.0%	7.0%	6.9%	5.1%	2.8%	1.3%	0.5%
2	0.5%	1.1%	1.3%	0.9%	0.5%	0.2%	0.1%
3	0.1%	0.1%	0.2%	0.1%	0.1%	0.0%	0.0%
4	0.0%	0.0%	0.0%	0.0%	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

4.07%

Fair odds: 24.58

Draw

16.78%

Fair odds: 5.96

Away Win

79.15%

Fair odds: 1.26

Over 0.591.63%/ Under 8.37%Fair: 1.09

Over 1.573.66%/ Under 26.34%Fair: 1.36

Over 2.547.5%/ Under 52.5%Fair: 2.11

Over 3.525.6%/ Under 74.4%Fair: 3.91

Over 4.511.42%/ Under 88.58%Fair: 8.75

BTTS Yes28.35%Fair: 3.53

BTTS No71.65%Fair: 1.4

Correct Score — Top 12

10-2

18.63%A

20-1

15.98%A

30-3

13.79%A

40-0

8.37%D

50-4

7.65%A

61-1

7.02%D

71-2

6.89%A

81-3

5.1%A

90-5

3.4%A

101-4

2.83%A

111-0

1.99%H

122-2

1.28%D

Dixon-Coles vs Plain Poisson

Where the low-score correction adds value

Plain Poisson

P(0-0) = 7.5%

P(1-0) = 2.8%

P(0-1) = 16.6%

P(1-1) = 6.2%

✗ Underestimates 0-0, 1-0, 0-1

Dixon-Coles (ρ correction)

P(0-0) = 8.4% (+0.9%)

P(1-0) = 2.0% (-0.8%)

P(0-1) = 16.0% (-0.7%)

P(1-1) = 7.0% (+0.9%)

✓ 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%)	26	9	34.62%	−$30.20	-11.62%
DC Home Pick (>50%)	11	7	63.64%	+$13.90	+12.64%
DC Away Pick (>50%)	7	1	14.29%	−$51.50	-73.57%
DC Draw (>28%)	14	3	21.43%	−$33.00	-23.57%
DC Over 2.5 Value	10	7	70%	+$9.70	+9.7%
DC BTTS Value	5	2	40%	−$17.60	-35.2%

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%)	26	−$30.20	-11.62%	−$5.38	-63.29%	+$1.69	+0.65%
DC Home Pick (>50%)	11	+$13.90	+12.64%	−$5.93	-15.57%	+$17.96	+16.2%
DC Away Pick (>50%)	7	−$51.50	-73.57%	$0.00	0%	−$54.61	-65.63%
DC Draw (>28%)	14	−$33.00	-23.57%	−$1.72	-100%	−$23.48	-17.26%
DC Over 2.5 Value	10	+$9.70	+9.7%	−$6.15	-33.26%	+$13.97	+13.52%
DC BTTS Value	5	−$17.60	-35.2%	$0.00	0%	−$18.40	-36.17%

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
Olympique Marseille	1.69	1.48	1.3	0.77	4	4
Rennes	1.6	0.74	1.23	1.84	5	3
Lens	1.38	0.93	1.3	1.07	4	4
PSG	1.23	0.74	1.48	0.74	3	5
Brest	1.23	1.11	1.11	0.92	4	4
Paris FC	1.38	0.74	0.74	0.77	4	4
Olympique Lyonnais	1.53	0.56	0.56	0.61	4	4
Strasbourg	0.82	1.23	1.19	1.6	3	5
Auxerre	0.77	0.93	1.3	1.99	4	4
Toulouse	0.46	0.93	1.67	0.92	4	4
Le Mans	0.92	1.48	0.93	1.23	4	4
Lille	0.92	0.56	0.93	0.46	4	4
Monaco	1.07	0.74	0.74	0.46	4	4
Angers SCO	0.61	1.33	0.99	1.23	5	3
Nice	0.77	0.56	0.56	1.07	4	4
Le Havre	0.31	1.11	1.11	1.38	4	4
Lorient	0.77	0.74	0.37	0.31	4	4
Troyes	0.46	2.04	0.37	0.77	4	4

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.

1PSG

1567

2Monaco

1536

3Lille

1536

4Rennes

1535

5Paris FC

1526

6Olympique Lyonnais

1526

7Lens

1521

8Lorient

1517

9Nice

1506

10Toulouse

1503

11Olympique Marseille

1503

12Auxerre

1487

13Brest

1482

14Le Mans

1471

15Strasbourg

1465

16Angers SCO

1463

17Troyes

1441

18Le Havre

1415

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	PSG vs Le Havre

Elo Rating History — Top 6

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

PSGMonacoLilleRennesParis FCOlympique Lyonnais

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	PSG	1567	1567	+67	8	5	2	1
2	Monaco	1536	1561	+36	8	4	3	1
3	Lille	1536	1544	+36	8	4	3	1
4	Rennes	1535	1540	+35	8	5	1	2
5	Paris FC	1526	1543	+26	8	4	2	2
6	Olympique Lyonnais	1526	1542	+26	8	4	2	2
7	Lens	1521	1521	+21	8	4	1	3
8	Lorient	1517	1517	+17	8	3	3	2
9	Nice	1506	1506	+6	8	3	2	3
10	Toulouse	1503	1510	+3	8	2	4	2
11	Olympique Marseille	1503	1513	+3	8	4	0	4
12	Auxerre	1487	1500	-13	8	3	1	4
13	Brest	1482	1517	-18	8	2	3	3
14	Le Mans	1471	1500	-29	8	1	4	3
15	Strasbourg	1465	1521	-35	8	2	1	5
16	Angers SCO	1463	1500	-37	8	2	2	4
17	Troyes	1441	1516	-59	8	1	2	5
18	Le Havre	1415	1500	-85	8	0	2	6

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%)	40	7	18%	−$188.30	-47.07%
Elo Favourite	54	24	44%	−$29.20	-5.41%
Elo Home Pick (>55%)	3	1	33%	−$15.20	-50.67%
Elo Draw (>28%)	18	2	11%	−$108.00	-60%

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%)	40	−$188.30	-47.07%	−$11.84	-100%	−$128.00	-32.3%
Elo Favourite	54	−$29.20	-5.41%	−$17.20	-26.82%	+$15.90	+2.84%
Elo Home Pick (>55%)	3	−$15.20	-50.67%	$0.00	0%	−$13.92	-48.47%
Elo Draw (>28%)	18	−$108.00	-60%	$0.00	0%	−$103.21	-55.75%

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.

Ligue 1 France 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 — PSG vs Olympique Lyonnais

Poisson / Correct Score

Select Match

Dixon-Coles Score Matrix — Le Havre vs PSG

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