La Liga · Spain

Celta de VigovAthletic Club

Sunday 30 August at 20:30Abanca-Balaídoslineups not announced

Referee

Not appointed

0 matches on record

Fouls per game

—

League average

22.6

fouls per match, both teams

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.

What these numbers are

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 here has been compared to a bookmaker.

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.
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.
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.
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.
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.

Fouls v20260813-1451 · Tackles v20260813-1451 · Shots v20260813-1451 · Fouls won v20260813-1451 · Cards v20260813-1451 · Saves v20260813-1451

Model projections

Fouls43 playersHighest: Iñigo Ruiz de Galarreta Etxeberria, 1.60 expectedshow

What drives it — Who referees the match. A strict official lifts every player on the pitch, which is the part most books price off a season average. See what has actually happened.

Player	Team	Model /90	Exp. mins	Projected	Over 1.5	n	Distribution
Iñigo Ruiz de Galarreta EtxeberriaMID	Athletic Club	2.31	62provisional	1.60	46%	56	023% 131% 224% 313% 46% 52% 6+1%
Mikel Jauregizar AlbonigaMID	Athletic Club	1.71	73provisional	1.38	40%	62	028% 132% 222% 311% 44% 51% 6+1%
Benat Prados DíazMID	Athletic Club	2.07	57provisional	1.30	37%	25	032% 132% 220% 310% 44% 51% 6+1%
Yoel Lago AmilDEF	Celta de Vigo	1.50	78provisional	1.29	37%	18	031% 132% 222% 310% 44% 51% 6+0%
Gorka Guruzeta RodríguezFWD	Athletic Club	1.96	59provisional	1.29	36%	58	032% 132% 220% 310% 44% 51% 6+1%
Alejandro Rego MoraMID	Athletic Club	2.52	44provisional	1.22	33%	16	037% 131% 217% 39% 44% 52% 6+1%
Daniel Vivian MorenoDEF	Athletic Club	1.14	82provisional	1.04	28%	59	037% 135% 219% 37% 42% 50% 6+0%
Álvaro Djaló Dias FernandesFWD	Athletic Club	2.37	39provisional	1.02	27%	10	040% 133% 217% 37% 42% 51% 6+0%
Moriba Kourouma KouroumaMID	Celta de Vigo	1.36	67provisional	1.01	27%	54	040% 132% 217% 37% 42% 51% 6+0%
Maroan Sannadi HarrouchFWD	Athletic Club	2.26	40provisional	1.00	26%	13	043% 131% 215% 37% 43% 51% 6+0%

10 of 43 players shown, ranked by projection. Show all 43 →

Tackles43 playersHighest: Moriba Kourouma Kourouma, 2.27 expectedshow

What drives it — Possession share. A tackle count depends far more on how much of the match is played at your own end than on a player’s own form. See what has actually happened.

Player	Team	Model /90	Exp. mins	Projected	Over 1.5	n	Distribution
Moriba Kourouma KouroumaMID	Celta de Vigo	3.04	67provisional	2.27	58%	54	019% 123% 220% 315% 410% 56% 6+7%
Mikel Jauregizar AlbonigaMID	Athletic Club	2.53	73provisional	2.04	56%	62	019% 125% 222% 316% 49% 55% 6+4%
Andoni Gorosabel EspinosaDEF	Athletic Club	2.49	65provisional	1.79	48%	35	026% 126% 220% 313% 48% 54% 6+3%
Benat Prados DíazMID	Athletic Club	2.83	57provisional	1.78	48%	25	024% 127% 221% 313% 48% 54% 6+3%
Francisco José Beltrán PeinadoMID	Celta de Vigo	2.22	69provisional	1.71	47%	15	025% 128% 221% 313% 47% 53% 6+2%
Iñigo Ruiz de Galarreta EtxeberriaMID	Athletic Club	2.32	62provisional	1.60	45%	56	025% 130% 222% 313% 46% 53% 6+2%
Yoel Lago AmilDEF	Celta de Vigo	1.76	78provisional	1.52	43%	18	028% 129% 221% 312% 46% 52% 6+1%
Miguel Román GonzálezMID	Celta de Vigo	1.93	69provisional	1.48	41%	14	032% 127% 219% 312% 46% 53% 6+2%
Daniel Vivian MorenoDEF	Athletic Club	1.61	82provisional	1.47	42%	59	027% 131% 222% 312% 45% 52% 6+1%
Carlos Domínguez CáceresDEF	Celta de Vigo	1.87	66provisional	1.38	38%	22	033% 129% 219% 311% 45% 52% 6+1%

10 of 43 players shown, ranked by projection. Show all 43 →

Shots43 playersHighest: Gorka Guruzeta Rodríguez, 1.65 expectedshow

What drives it — The player’s own shot rate, shrunk toward others in his position, then adjusted for how many shots the opponent concedes. See what has actually happened.

Player	Team	Model /90	Exp. mins	Projected	Over 1.5	n	Distribution
Gorka Guruzeta RodríguezFWD	Athletic Club	2.50	59provisional	1.65	46%	58	025% 129% 222% 313% 47% 53% 6+2%
Iñaki Williams ArthuerFWD	Athletic Club	1.85	74provisional	1.53	44%	61	025% 131% 223% 312% 46% 52% 6+1%
Nicholas Williams ArthuerFWD	Athletic Club	2.01	68provisional	1.52	43%	50	026% 131% 222% 312% 46% 52% 6+1%
Oihan Sancet TirapuMID	Athletic Club	2.18	60provisional	1.46	41%	49	027% 132% 222% 312% 45% 52% 6+1%
Ferran Jutlgà BlancFWD	Celta de Vigo	2.10	55provisional	1.29	36%	23	033% 131% 220% 310% 44% 52% 6+1%
Alejandro Berenguer RemiroFWD	Athletic Club	1.68	67provisional	1.26	35%	58	032% 133% 220% 310% 44% 51% 6+0%
Borja Iglesias QuintasFWD	Celta de Vigo	2.04	54provisional	1.22	34%	50	036% 130% 218% 39% 44% 51% 6+1%
Iago Aspas JuncalFWD	Celta de Vigo	2.18	47provisional	1.13	30%	34	041% 129% 216% 38% 44% 52% 6+1%
Maroan Sannadi HarrouchFWD	Athletic Club	2.29	40provisional	1.02	26%	13	043% 131% 215% 37% 43% 51% 6+1%
Pablo Durán FernándezFWD	Celta de Vigo	1.84	50provisional	1.02	27%	37	043% 130% 216% 37% 43% 51% 6+0%

10 of 43 players shown, ranked by projection. Show all 43 →

Fouls won43 playersHighest: Moriba Kourouma Kourouma, 1.73 expectedshow

What drives it — How much a player runs at defenders. Dribble volume drives this far more than the referee does. See what has actually happened.

Player	Team	Model /90	Exp. mins	Projected	Over 1.5	n	Distribution
Moriba Kourouma KouroumaMID	Celta de Vigo	2.32	67provisional	1.73	48%	54	025% 127% 221% 314% 47% 54% 6+2%
Nicholas Williams ArthuerFWD	Athletic Club	1.52	68provisional	1.15	32%	50	035% 133% 219% 38% 43% 51% 6+0%
Maroan Sannadi HarrouchFWD	Athletic Club	2.54	40provisional	1.13	30%	13	040% 131% 216% 38% 44% 52% 6+1%
Ferran Jutlgà BlancFWD	Celta de Vigo	1.83	55provisional	1.13	31%	23	037% 132% 218% 38% 43% 51% 6+0%
Williot SwedbergFWD	Celta de Vigo	2.33	43provisional	1.11	30%	36	038% 132% 217% 38% 43% 51% 6+0%
Mikel Jauregizar AlbonigaMID	Athletic Club	1.32	73provisional	1.07	29%	62	037% 134% 218% 37% 42% 51% 6+0%
Borja Iglesias QuintasFWD	Celta de Vigo	1.75	54provisional	1.05	28%	50	041% 131% 217% 37% 43% 51% 6+0%
Alejandro Berenguer RemiroFWD	Athletic Club	1.39	67provisional	1.04	28%	58	039% 134% 218% 37% 42% 51% 6+0%
Iñaki Williams ArthuerFWD	Athletic Club	1.22	74provisional	1.00	27%	61	039% 134% 217% 37% 42% 51% 6+0%
Iñigo Ruiz de Galarreta EtxeberriaMID	Athletic Club	1.41	62provisional	0.97	26%	56	040% 135% 217% 36% 42% 50% 6+0%

10 of 43 players shown, ranked by projection. Show all 43 →

Cards43 playersHighest: Yoel Lago Amil, 0.24 expectedshow

Known defect — Prices ANY card — yellow, second yellow or straight red — matching how books settle "to be shown a card". The trends column counts the same thing.

What drives it — Fouls first, then how readily the referee reaches for a card. Two officials averaging four cards a match can do it for opposite reasons. See what has actually happened.

Player	Team	Model /90	Exp. mins	Projected	Over 0.5	n	Distribution
Yoel Lago AmilDEF	Celta de Vigo	0.28	78provisional	0.24	21%	18	079% 118% 22% 3+0%
Iñigo Ruiz de Galarreta EtxeberriaMID	Athletic Club	0.34	62provisional	0.24	21%	56	079% 118% 22% 3+0%
Daniel Vivian MorenoDEF	Athletic Club	0.21	82provisional	0.19	17%	59	083% 116% 22% 3+0%
Marcos Alonso MendozaDEF	Celta de Vigo	0.19	86provisional	0.19	17%	62	083% 115% 21% 3+0%
Aitor Paredes CasamichanaDEF	Athletic Club	0.20	82provisional	0.18	16%	39	084% 115% 2+1%
Alejandro Rego MoraMID	Athletic Club	0.36	44provisional	0.18	16%	16	084% 114% 22% 3+0%
Moriba Kourouma KouroumaMID	Celta de Vigo	0.24	67provisional	0.18	16%	54	084% 114% 21% 3+0%
Benat Prados DíazMID	Athletic Club	0.27	57provisional	0.17	15%	25	085% 114% 21% 3+0%
Andoni Gorosabel EspinosaDEF	Athletic Club	0.22	65provisional	0.16	15%	35	085% 113% 2+1%
Javier Rodríguez GalianoDEF	Celta de Vigo	0.19	74provisional	0.15	14%	61	086% 113% 2+1%

10 of 43 players shown, ranked by projection. Show all 43 →

Saves2 playersHighest: Unai Simón Mendibil, 2.90 expectedshow

What drives it — Opponent shot volume. A keeper’s own record carries so little that this market shrinks harder than any other on the board. See what has actually happened.

Player	Team	Model /90	Exp. mins	Projected	Over 2.5	n	Distribution
Unai Simón MendibilGK	Athletic Club	2.90	90provisional	2.90	53%	58	07% 117% 222% 320% 415% 59% 6+9%
Ionuț Andrei RaduGK	Celta de Vigo	2.61	90provisional	2.61	47%	38	09% 120% 224% 320% 413% 57% 6+7%

1 of 7 markets have no projection for this fixture.