AI
OddsFlow AI Analysis
Powered by Machine Learning
53Geral
Total football
⚡Ataque
51
⚙️Meio-campo
53
🛡️Defesa
46
🧤Goleiro
67
25Tamanho
27.6Idade Méd.
59.8OVR Méd.
86.0Prof. Elenco
53Geral
Total football
⚡Ataque
51
⚙️Meio-campo
53
🛡️Defesa
46
🧤Goleiro
67
25Tamanho
27.6Idade Méd.
59.8OVR Méd.
86.0Prof. Elenco
Jogadores Estrela
68
F. Grillitsch
Midfielder
3G 3A (2056min)

F. Wiegele
Goalkeeper
OPR 67

P. Wanner
Midfielder
5G 4A (2407min)

A. Schlager
Goalkeeper
OPR 66

X. Schlager
Midfielder
3G 2A (2207min)
Probabilidade do Torneio
1.3%CampeãoCampeão
1.3%
78.8%Avançar do GrupoAvançar do Grupo
78.8%
Pontos Fortes
Top-class goalkeeper
Deep squad rotation
Manager & Tactical Profile
· Appointed
Team Strength & Intelligence
50
ATK
53
MID
46
DEF
76
GK
1.42
λ Attack
0.96
λ Defense
35
Chemistry
86
Depth
3.4
Star Gap
27.6
Avg Age
Top Scorer
M. Gregoritsch
7 goals
Best Rated
F. Wiegele
7.73
Club Clusters
RB Leipzig (2)FSV Mainz 05 (2)Borussia Dortmund (2)Werder Bremen (2)
WC Experience
Appearances7
Best Finish3rd 1954
Last WC1998
Physical Resilience
Avg Mins/Season2,448
FatigueGood recovery — peak physical years
MiamiMODERATE
MonterreyMODERATE
Hot Climate %0%
Cooperation
Score39/100
Total Clubs21
Same-Club Pairs4
Same-League80
Average — typical international squad
H2H Matchup Predictions(47)
WinDrawLoss
Curaçau
1-0▼
54%
25%
21%
xG 1.6 – 0.9O2.5 45%BTTS 47%
Iraque
0-1▼
54%
26%
21%
xG 1.6 – 0.9O2.5 44%BTTS 47%
Haiti
0-1▼
53%
25%
22%
xG 1.5 – 0.9O2.5 44%BTTS 46%
Iran
0-1▼
53%
25%
22%
xG 1.6 – 0.9O2.5 45%BTTS 47%
South Korea
1-0▼
52%
26%
22%
xG 1.5 – 0.9O2.5 44%BTTS 46%
África do Sul
0-1▼
52%
26%
22%
xG 1.5 – 0.9O2.5 43%BTTS 46%
Uzbequistão
0-1▼
52%
26%
23%
xG 1.5 – 0.9O2.5 43%BTTS 45%
Cape Verde Islands
1-1▼
51%
25%
25%
xG 1.6 – 1.1O2.5 50%BTTS 53%
Catar
0-1▼
50%
24%
25%
xG 1.6 – 1.0O2.5 48%BTTS 51%
Egito
1-1▼
48%
25%
27%
xG 1.6 – 1.2O2.5 53%BTTS 56%
Tunísia
1-1▼
47%
26%
27%
xG 1.4 – 1.0O2.5 45%BTTS 49%
Gana
1-1▼
47%
26%
27%
xG 1.5 – 1.1O2.5 47%BTTS 50%
Jordânia
1-1▼
46%
27%
27%
xG 1.4 – 1.0O2.5 45%BTTS 49%
Bosnia & Herzegovina
1-1▼
45%
26%
29%
xG 1.5 – 1.1O2.5 47%BTTS 51%
Panamá
1-1▼
45%
27%
28%
xG 1.4 – 1.0O2.5 43%BTTS 47%
Noruega
1-1▼
44%
26%
31%
xG 1.5 – 1.2O2.5 50%BTTS 54%
Escócia
1-1▼
43%
26%
31%
xG 1.4 – 1.1O2.5 47%BTTS 52%
Equador
1-1▼
43%
27%
29%
xG 1.3 – 1.1O2.5 43%BTTS 49%
Canadá
1-1▼
43%
26%
31%
xG 1.5 – 1.2O2.5 50%BTTS 54%
Austrália
1-1▼
43%
26%
31%
xG 1.4 – 1.2O2.5 48%BTTS 52%
Arábia Saudita
1-1▼
43%
25%
32%
xG 1.4 – 1.2O2.5 49%BTTS 53%
Argélia
1-1▼
43%
24%
33%
xG 1.5 – 1.3O2.5 53%BTTS 57%
México
1-1▼
43%
24%
33%
xG 1.5 – 1.3O2.5 54%BTTS 56%
Colômbia
1-1▼
43%
27%
31%
xG 1.4 – 1.1O2.5 47%BTTS 52%
Ivory Coast
1-1▼
43%
26%
31%
xG 1.4 – 1.1O2.5 46%BTTS 50%
Paraguai
1-1▼
42%
27%
31%
xG 1.4 – 1.1O2.5 46%BTTS 51%
Marrocos
1-1▼
42%
27%
31%
xG 1.4 – 1.1O2.5 46%BTTS 50%
Nova Zelândia
1-1▼
42%
26%
32%
xG 1.4 – 1.2O2.5 50%BTTS 53%
EUA
1-1▼
41%
26%
33%
xG 1.4 – 1.2O2.5 47%BTTS 52%
Suécia
1-1▼
41%
27%
32%
xG 1.3 – 1.2O2.5 45%BTTS 50%
Suíça
1-1▼
40%
27%
33%
xG 1.4 – 1.2O2.5 46%BTTS 52%
RD Congo
1-1▼
40%
26%
34%
xG 1.4 – 1.3O2.5 50%BTTS 54%
Bélgica
1-1▼
39%
27%
34%
xG 1.3 – 1.2O2.5 46%BTTS 52%
Czech Republic
1-1▼
39%
26%
35%
xG 1.3 – 1.3O2.5 48%BTTS 53%
Países Baixos
1-1▼
38%
26%
35%
xG 1.3 – 1.3O2.5 47%BTTS 52%
Senegal
1-1▼
38%
27%
35%
xG 1.3 – 1.2O2.5 47%BTTS 52%
Croácia
1-1▼
38%
27%
35%
xG 1.3 – 1.3O2.5 48%BTTS 53%
Brasil
1-1▼
38%
26%
36%
xG 1.3 – 1.3O2.5 48%BTTS 52%
Uruguai
1-1▼
38%
27%
35%
xG 1.3 – 1.2O2.5 46%BTTS 51%
Japão
1-1▼
38%
26%
36%
xG 1.4 – 1.3O2.5 50%BTTS 54%
Argentina
1-1▼
37%
26%
36%
xG 1.3 – 1.3O2.5 48%BTTS 53%
Espanha
1-1▼
37%
27%
36%
xG 1.3 – 1.3O2.5 47%BTTS 52%
Alemanha
1-1▼
36%
26%
38%
xG 1.3 – 1.3O2.5 48%BTTS 53%
Turquia
1-1▼
35%
26%
39%
xG 1.3 – 1.4O2.5 49%BTTS 52%
Inglaterra
1-1▼
33%
26%
41%
xG 1.2 – 1.4O2.5 49%BTTS 53%
França
1-1▼
32%
26%
42%
xG 1.2 – 1.4O2.5 48%BTTS 53%
Portugal
1-1▼
32%
26%
41%
xG 1.2 – 1.4O2.5 47%BTTS 51%
Sensitivity Analysis(51 scenarios)
Rank Distribution Across Scenarios
Baseline—
#5
Heat ×0.75—
#5
Heat ×2—
#5
Heat ×2.5—
#5
Heat ×0.25—
#5
Heat ×1.75—
#5
Altitude ×0.75—
#5
Altitude ×1.25—
#5
Altitude ×1.5—
#5
Altitude ×2.5—
#5
Altitude ×0.25—
#5
Host ×0.5—
#5
Mismatch t=0.1 a=0.5—
#5
Spread 1—
#5
Spread 1.5—
#5
Uplift 1.15—
#5
Heat ×0▲1
#6
Heat ×0.5▲1
#6
Heat ×1.5▲1
#6
Heat ×3▲1
#6
Altitude ×0▲1
#6
Altitude ×2▲1
#6
Altitude ×3▲1
#6
Travel ×0▲1
#6
Travel ×0.25▲1
#6
Host ×0▲1
#6
Penalty rand=0.5▲1
#6
Uplift 1▲1
#6
Heat ×1.25▲2
#7
Altitude ×0.5▲2
#7
Altitude ×1.75▲2
#7
Travel ×0.5▲2
#7
Travel ×1.5▲2
#7
Travel ×1.75▲2
#7
Host ×1.5▲2
#7
Host ×2▲2
#7
Host ×3▲2
#7
Mismatch t=0.05 a=0.3▲2
#7
Mismatch t=0.15 a=0.7▲2
#7
Mismatch t=0.2 a=0.9▲2
#7
Mismatch t=0.3 a=1.2▲2
#7
Spread 3▲2
#7
Penalty rand=0.3▲2
#7
Penalty rand=0.7▲2
#7
Travel ×0.75▲3
#8
Travel ×2▲3
#8
Travel ×2.5▲3
#8
Travel ×3▲3
#8
Spread 2.1▲3
#8
Spread 2.5▲3
#8
Travel ×1.25▲4
#9
Baseline: #5·Lower rank = stronger
baseline
1 scenarios · #5
heat
10 scenarios · #5–#7
altitude
10 scenarios · #5–#7
travel
10 scenarios · #6–#9
host
5 scenarios · #5–#7
mismatch
5 scenarios · #5–#7
spread
5 scenarios · #5–#8
penalty
3 scenarios · #6–#7
uplift
2 scenarios · #5–#6