Haiti
- Coach
- Sébastien Migné foreign · French
- Elo (model)
- 1,548 world 71st
- Squad value
- €44M
- Power → Reality
- 46th 47th −0.00 pp · neutral draw
§ 01
The forecast
How far Haiti goes — the survival probability at each stage of the bracket, from the tournament Monte-Carlo simulation. Each bar carries its ±1.96·MC-SE interval.
Fig. D1 Fixture-aware · 100k sims
Haiti — stage progression
Haiti is most likely eliminated before the knockout rounds: 12% to clear the group. Champion probability 0.00%.
§ 02
The group & the path
Group C advancement odds, the bracket half Haiti sits in, and the earliest round they could meet each leading side.
| Group C | Confed | Advance (top 2) | Reach R32 | |
|---|---|---|---|---|
| 1 | 🇧🇷Brazil | CONMEBOL | 67.1% | 98.3% |
| 2 | 🇲🇦Morocco | CAF | 44.9% | 88.8% |
| 3 | 🏴Scotland | UEFA | 25.5% | 70.4% |
| 4 | 🇭🇹Haiti | CONCACAF | 1.4% | 11.6% |
Source · Oxford Football Forecasting model
Earliest possible meetings
No collision rows recorded for this team.
Collision = the earliest round the bracket wiring could pit Haiti against that side. Full bracket & collision matrix →
§ 03
Match by match
Haiti's three group fixtures, each with the predicted win / draw / loss split and the single most-likely scoreline. Probabilities are this team's own orientation; they sum to 100%.
How a match forecast is built
Each pairing is scored by the ensemble (Dixon-Coles bivariate-Poisson, the Bayesian hierarchical model and the global LightGBM-Poisson, log-pooled), producing an 11×11 scoreline grid that is marginalised into win/draw/loss, expected goals (λ), over/under 2.5 and both-teams-to-score. These are the same distributions the tournament simulator consumes, oriented here to Haiti. Knockout fixtures are not shown — their occupants are still probabilistic, so there is no single pairing to forecast yet.
§ 04
Strength profile
Where Haiti stands against the median of the 48-team field, metric by metric. The dot is Haiti; the dashed line is the field median (1.0×).
Fig. D2 Relative to the 48-team median
Haiti vs the field
Read each row as a multiple of the field median: dots to the right of the dashed line are above-field, to the left below. Raw values are labelled on the right so the comparison is transparent.
§ 05
History vs squad
The decoupling residual g — whether the squad’s market value sits above, or below, what the team’s record predicts.
Fig. D3 Bayesian projection residual g
Haiti on the decoupling axis
g = −0.17 ± 0.10: the record outruns the squad price — the team has achieved more than its comparatively modest squad value would predict.
What g means — and its limits
g is the residual from regressing a team’s current squad market value on its
history-based strength in the Bayesian hierarchical model. Positive g
means the squad is valued above what the team’s record predicts; negative means the
record outruns the squad’s price (the side achieves more than its market value implies).
Regressed on out-of-sample success the slope is positive — squad-rich sides go a touch
further — but not statistically significant at n = 3 tournaments, so treat
a single team’s g as a descriptive read, not a hard prediction.
The full decoupling essay →
§ 06
The squad
All 26 selected players — club, league (with relative strength), club-season minutes and goals, caps. Sort any column.
| # | Player | Pos | Club | League | Club min | Gls | Caps | NT gls |
|---|---|---|---|---|---|---|---|---|
| 1 | Johny Placide (captain) | GK | Bastia | Ligue 2 +1.70z | 2,128 | 0 | 81 | 0 |
| 2 | Carlens Arcus | DF | Angers | Ligue 1 +1.70z | 2,157 | 0 | 53 | 1 |
| 3 | Keeto Thermoncy | DF | Young Boys | — | — no club data | — | 1 | 0 |
| 4 | Ricardo Adé | DF | LDU Quito | Liga Pro −0.72z | 4,783 | 2 | 59 | 2 |
| 5 | Hannes Delcroix | DF | Lugano | Super League −0.07z | 1,155 | 1 | 7 | 0 |
| 6 | Carl Sainté | MF | El Paso Locomotive FC | — | — no club data | — | 26 | 0 |
| 7 | Derrick Etienne Jr. | FW | Toronto FC | Major League Soccer −0.71z | 1,007 | 0 | 48 | 8 |
| 8 | Martin Expérience | DF | Nancy | Ligue 2 +1.70z | 1,452 | 1 | 21 | 0 |
| 9 | Duckens Nazon | FW | Esteghlal | Persian Gulf Pro League −0.98z | 148 | 1 | 78 | 44 |
| 10 | Jean-Ricner Bellegarde | MF | Wolverhampton Wanderers | — | — no club data | — | 10 | 0 |
| 11 | Louicius Deedson | FW | FC Dallas | Major League Soccer −0.71z | 22 | 0 | 32 | 10 |
| 12 | Alexandre Pierre | GK | Sochaux | — | — no club data | — | 15 | 0 |
| 13 | Duke Lacroix | DF | Colorado Springs Switchbacks FC | USL Championship −0.71z | 658 | 0 | 16 | 3 |
| 14 | Leverton Pierre | MF | Vizela | Segunda Liga +1.14z | 17 | 0 | 33 | 0 |
| 15 | Ruben Providence | FW | Almere City | Eerste Divisie +0.74z | 1,102 | 1 | 15 | 3 |
| 16 | Lenny Joseph | FW | Ferencváros | NB I | 1,825 | 11 | 2 | 1 |
| 17 | Danley Jean Jacques | MF | Philadelphia Union | Major League Soccer −0.71z | 4,905 | 3 | 30 | 6 |
| 18 | Wilson Isidor | FW | Sunderland | Premier League +2.21z | 1,365 | 6 | 4 | 2 |
| 19 | Yassin Fortuné | FW | Vizela | Segunda Liga +1.14z | 414 | 1 | 4 | 0 |
| 20 | Frantzdy Pierrot | FW | Çaykur Rizespor | Süper Lig +0.49z | 127 | 0 | 51 | 34 |
| 21 | Josué Casimir | FW | Auxerre | Ligue 1 +1.70z | 1,532 | 1 | 7 | 0 |
| 22 | Jean-Kévin Duverne | DF | Gent | Jupiler Pro League −0.07z | 1,174 | 1 | 17 | 1 |
| 23 | Josué Duverger | GK | Cosmos Koblenz | — | — no club data | — | 6 | 0 |
| 24 | Wilguens Paugain | DF | Zulte Waregem | Jupiler Pro League −0.07z | 1,298 | 1 | 8 | 0 |
| 25 | Dominique Simon | MF | Tatran Prešov | Super Liga | 576 | 0 | 2 | 0 |
| 26 | Woodensky Pierre | MF | Violette | — | — no club data | — | 1 | 0 |
Source · Official squad announcements · API-Football (global club coverage). 6 of 26 players have no club season matched in API-Football — shown as “— no club data”, not imputed. Form coverage for this squad: 77%.
§ 07
Tournament context
The host-nation environment this team meets — diaspora support, climate and altitude exposure at their venues, language familiarity.
Diaspora in the hosts
811,820
69.0 per 1,000 of home population
Host-language familiarity
Shared
primary language French · spoken in a host
Climate adaptation gap
+4.7°C
home-vs-venue heat differential
Venue extremes
37°C
peak heat index · altitude up to 313 m
Travel
1h
max time-zone shift · nearest venue 1,159 km
Source · UN DESA international migrant stock · US Census Bureau · Open-Meteo & venue records
§ 08
Elo trajectory
Haiti's long-run strength against the qualified-field median, 1950–2026.
Fig. D4 eloratings.net method · year-end values
Haiti — Elo since 1950
Haiti ends the series at 1707 Elo, the world’s 71st-ranked side — below the qualified-field median.
Which Elo is this?
This line is the public eloratings.net series (year-end ratings), which terminates exactly at the current rating and world rank shown on the marker. It is a different number from the Elo shown in the header band (a panel-normalised rating used inside the forecast); the two are ~0.99 correlated but on different scales. We keep them distinct rather than blend them.
§ 09
Data coverage
Validated on n=3 held-out tournaments; coverage below 1.0 means part of this squad's club-form/fitness is imputed (the global de-biasing layer). For Haiti, 6 of 26 players are shown as “— no club data”. Full validation, calibration & conformal coverage →