PER90

Ligue 1 · France

lineups not announced

Estac Troyesno record v Paris FCno record

Referee M. BollengierExpected XI →Referee record →

Top value

Ranked by edge over the model's fair price.

Value

No edges published on this fixture. An edge is published only when a bookmaker's price beats the model's fair price by that market's full bar — most fixtures never produce one. The value board explains every gate a candidate has to clear.

RefereeM. Bollengier0 on record
Fouls/game
Cards/game
module →
Availability0 players projectedlineups not announced
Minutes
0 confirmed
0 expected
0 provisional

No lineup yet. Minutes come from each player’s start rate, which is the widest of the three states — and why rows are marked provisional.

Value — 0 live calls

Published at the price shown, scored against the closing line.

No edges published on this fixture. An edge is published only when a bookmaker's price beats the model's fair price by that market's full bar — most fixtures never produce one. The value board explains every gate a candidate has to clear.

Lineups and form

Who the feed expects on the pitch, and what each side has just done.

Player props
lineups not announced

The feed has published no teamsheet for this fixture yet.

Lineups are captured every fifteen minutes from three hours before kick-off. An expected XI normally lands well before that; a confirmed one about an hour out. Until one does, every projection on this page takes its minutes from each player’s start rate — which is what the provisional marks in the props table mean.

Recent results

Last six completed matches per side, newest first. Half-time score in brackets where the feed carries one.

Estac Troyesno record

No completed matches on record for this club.

Paris FCno record

No completed matches on record for this club.

Player props

Model projections. Nothing here has been compared to a bookmaker.

How this is calculated

No projections for this fixture yet. The projection job runs against fixtures inside the odds window, and only for players with at least 10 completed matches on record.

Referee

§5.1: the dominant covariate for fouls, and the reason two identical players price differently on different days.

M. Bollengier

0 matches on record

Fouls per game

Cards per game

Cards, home side

Estac Troyes

Cards, away side

Paris FC

Fouls — every foul committed by both teams in a match he refereed, averaged over his completed matches. The match being previewed is never in it. Under 15 matches on record, so the model itself falls back toward the league mean here.

Cards — any card, yellow or red, both teams. The same definition the card props settle against, so this figure and the Cards market count the same events. A dismissal that the feed records as a second yellow counts as two.

Both league averages are the mean across all five competitions Per90 covers, not this fixture's league alone — the fouls comparison has always been that, and the cards comparison is built the same way so the two percentages beside each other mean the same thing.

The model

What the numbers on this page are, and what they are not.

How are these projections calculated?Open

Not tips and not prices. Each row is the model's expected count for one player in this match — how many fouls, tackles or shots it thinks he records — plus the full spread of outcomes around it. Nothing in the projections has been compared to a bookmaker; that comparison is what the Value tab is.

  1. Step 1

    His own record

    Every completed match in the dataset, as a rate per 90 minutes. The n column is how many matches that rests on.

  2. Step 2

    Pulled toward his position

    A thin record gets pulled hard toward other players in his position, in his league — a goalkeeper toward goalkeepers, not toward the outfielders around him. How hard is fitted per market, not chosen: tackles pull about four times harder than shots on target.

  3. Step 3

    This fixture's conditions

    How much of the stat the opponent concedes, what the referee’s matches look like, and home or away. This is where a projection stops being a season average.

  4. Step 4

    Scaled to expected minutes

    A rate becomes a count only once you say how long he plays. 60 minutes carries two-thirds the exposure of 90, and the distribution is built at that exposure.

How to read each column

Model /90
The model’s rate for this match with the minutes taken back out — steps 1 to 3 already applied. It moves with the opponent and the referee, so it is not his raw career rate; the builder shows career and model rates side by side. Open any row to see it.
Exp. mins
Minutes the model expects. Confirmed means the lineup is out; provisional means it is guessing from his start rate, and is the widest of the three.
Projected
The expected count in this match, at those minutes. This is the number a line is set against.
Over 1.5, etc.
Read straight off the distribution beside it, not off how often he has beaten that line before. It answers what the model thinks, not what has happened.
n
Matches behind his own rate. Under 30 it turns amber: the projection is mostly his position group speaking, and §6.3 will not publish an edge on it.
Distribution
The whole spread, not just the average. The dashed amber cut is the line; jade bars beat it. An expected 1.8 fouls made of 2 every week and an expected 1.8 made of a 0 and a 5 are different bets, and this is where you see which one you have.

Counts are modelled as negative binomial rather than Poisson, because fouls and tackles are overdispersed and a Poisson would systematically underprice the tails — which is exactly where over bets live. Every market on this page cleared its calibration gate before it was allowed to produce a projection: when the model says 60%, it lands within a point or so of 60% out of sample.

The full write-up — every gate, every fitted parameter and what the model refuses to price — is on the methodology page.