Primary AI Prediction
Home Win
Correct Score
2-1
Over/Under
Over 2.5
BTTS
Yes
PredictorAI v4.2
Quantitative Engine
Evaluating the historical and current data vectors for Asptt Dijon (Team Power (Elo): 1548) against Selongey (Team Power (Elo): 1595) in the Coupe de France, our neural engine processed 10,000 Monte Carlo match simulations.
Across 9 tracked head-to-head meetings, Asptt Dijon holds 5 wins compared to 2 for Selongey and 2 draws. Combined with xG goal indexes (1.36 vs 0.91), penalty-box efficiency is the primary differentiator.
The Coupe de France seventh round brings a genuine David-versus-Goliath subplot to the Stade des Poussots, where ASPTT Dijon of the regional pyramid host Selongey in a single-leg knockout that offers no margin for error.
The ClubElo telemetry frames the hosts as clear favourites: a Team Power rating of 1548 places them around world rank #525, with a positive recent Elo momentum of +0.75 suggesting a squad trending upward at exactly the right moment.
Their Golo goal expectancy of 1.36 per match, calibrated against Selongey's unranked defensive baseline, translates into a projected home xG of 1.48 — modest in isolation, but meaningful when set against the visitors' projected 0.98.
The aggregate expected-goals figure of 2.46 sits just beneath the 2.5 line, which is precisely why the value lies in the hosts' attacking output rather than a blanket goals call.
Tactically, ASPTT Dijon are likely to dominate territory and possession from the first whistle.
Their Elo-derived win probability of 44 percent, against 26 percent for a draw and 30 percent for Selongey, underlines that this is a contest the hosts should control but not necessarily cruise through.
Expect a compact 4-2-3-1 or 4-3-3 shape built on quick ball circulation into the half-spaces, with the full-backs pushing high to pin Selongey's midfield line deep.
The visitors, unranked and without a published Golo expectancy, will almost certainly set up in a low-to-mid block, ceding the ball and looking to spring counter-attacks through direct vertical passes into the channels.
Cup ties of this profile routinely see the underdog survive the opening half-hour before fatigue and quality gaps tell. That dynamic is reflected in the half-time/full-time selection of Draw/Home.
Selongey's best chance of survival is a disciplined, low-tempo first half in which they frustrate the hosts and keep the scoreline level at the interval; the second period is where ASPTT Dijon's superior conditioning, squad depth and home crowd should force the breakthrough.
A 2-1 scoreline captures both realities: the hosts' edge in chance creation and expected goals, and Selongey's capacity to punish a single lapse in concentration on the counter or from a set piece.
Both teams to score is the logical companion bet, since Selongey's projected 0.98 xG implies roughly a one-in-two chance of finding the net at least once. Set-piece delivery and second-ball dominance will be decisive.
ASPTT Dijon's likely advantage in possession and corner count should generate repeated crossing opportunities, while Selongey's route to a shock lies in transitions and dead-ball situations.
With a 61 percent confidence rating, the recommendation is a home win with goals: back the hosts on the handicap and lean into over 2.5 goals and both teams scoring, with the Draw/Home half-time/full-time line offering the sharpest risk-reward profile in a tie where the favourite's superiority should materialise after the interval.
Cross-referencing bivariate Poisson distributions with Elo-adjusted ratings, the model identifies "Home Win" as the primary statistical lean at a 61% confidence index.
In the goals market, Over 1.5 Goals carries a 83% probability and Over 2.5 Goals stands at 69% (Over 2.5). Within the exact score matrix, "2-1" leads the probability cluster (16.9%), followed by 1-0 (12.1%).
Analytical Note: Quantitative football modeling provides an objective mathematical framework for evaluating match probabilities strictly for informational and statistical analysis.
Historical data points and statistical distributions for recent encounters between these teams.
Head to Head Record
Asptt Dijon
2
Draws
1
Selongey
1
Team Performance Metrics
Analyzing the last 10 matches for both teams, weighting recent results 40% higher than older ones to capture momentum shifts.
Expected Goals (xG) data is cross-referenced with actual finishing rates to identify teams that are overperforming or due for a regression.
Our AI evaluates defensive structures, clean sheet probabilities, and the impact of missing key defensive personnel.
Simulated mathematical probabilities for the top final scorelines in Asptt Dijon vs Selongey based on bivariate Poisson distribution (1.48 vs 0.98 xG).
Expected goals variance across 11,237 Monte Carlo match simulations for Asptt Dijon vs Selongey.
Continuous algorithm calibration for live events, momentum swings, and goal probability shifts in Asptt Dijon vs Selongey.
Real-Time Signal Feeds Active
Live telemetry tracks momentum shifts as the match unfolds. Expected Corners: Asptt Dijon (5.6) vs Selongey (3.9).
Run the interactive 3D Monte Carlo match engine and inspect exact Poisson scoreline probabilities for Asptt Dijon vs Selongey.
View all AI match analysis and statistical projections for upcoming Coupe de France fixtures.
Do you agree with the AI prediction?
Key statistical questions and predictive metrics for this fixture
Our PredictorAI mathematical model forecasts Home Win with an estimated statistical confidence level of 61%.
Asptt Dijon enters with a Team Power (Elo) rating of 1548 and an Expected Goals (xG) index of 1.36, while Selongey holds a Team Power (Elo) rating of Null and an xG index of 0.91.
Based on Poisson distribution goal modeling and form regressions, the most statistically probable scoreline is 2-1.
Yes, both teams are statistically favored to find the net based on expected goals (xG) metrics and recent defensive shapes.
The primary goals line recommendation is Over 2.5, calculated from combined expected goal rates.
Disclaimer: Predict Football AI is strictly a sports data science and statistical analysis platform. These analytics are generated by machine learning models based on historical data, mathematical probabilities, and current form. They are for informational and educational purposes only. We are not a gambling platform, we do not offer odds, and we do not provide financial advice. Please use this data responsibly.
Pick: Draw (41%) • Score: 1-1
Pick: Home Win (61%) • Score: 2-1
Pick: Home Win (61%) • Score: 2-1
Pick: Home Win (61%) • Score: 2-1
Pick: Home Win (61%) • Score: 2-1
Pick: Home Win (61%) • Score: 2-1
Pick: Home Win (61%) • Score: 2-1
Pick: Home Win (61%) • Score: 2-1
Pick: Home Win (61%) • Score: 2-1
Pick: Home Win (62%) • Score: 2-1
Pick: Home Win (61%) • Score: 2-1
Pick: Home Win (61%) • Score: 2-1