PER90

La Liga · Spain

Celta de VigovAthletic Club

Abanca-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.

  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.
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.

PlayerTeamModel /90Exp. minsProjectedOver 1.5nDistribution
Iñigo Ruiz de Galarreta EtxeberriaMIDAthletic Club2.3162provisional1.6046%56
023%
131%
224%
313%
46%
52%
6+1%
Mikel Jauregizar AlbonigaMIDAthletic Club1.7173provisional1.3840%62
028%
132%
222%
311%
44%
51%
6+1%
Benat Prados DíazMIDAthletic Club2.0757provisional1.3037%25
032%
132%
220%
310%
44%
51%
6+1%
Yoel Lago AmilDEFCelta de Vigo1.5078provisional1.2937%18
031%
132%
222%
310%
44%
51%
6+0%
Gorka Guruzeta RodríguezFWDAthletic Club1.9659provisional1.2936%58
032%
132%
220%
310%
44%
51%
6+1%
Alejandro Rego MoraMIDAthletic Club2.5244provisional1.2233%16
037%
131%
217%
39%
44%
52%
6+1%
Daniel Vivian MorenoDEFAthletic Club1.1482provisional1.0428%59
037%
135%
219%
37%
42%
50%
6+0%
Álvaro Djaló Dias FernandesFWDAthletic Club2.3739provisional1.0227%10
040%
133%
217%
37%
42%
51%
6+0%
Moriba Kourouma KouroumaMIDCelta de Vigo1.3667provisional1.0127%54
040%
132%
217%
37%
42%
51%
6+0%
Maroan Sannadi HarrouchFWDAthletic Club2.2640provisional1.0026%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.

PlayerTeamModel /90Exp. minsProjectedOver 1.5nDistribution
Moriba Kourouma KouroumaMIDCelta de Vigo3.0467provisional2.2758%54
019%
123%
220%
315%
410%
56%
6+7%
Mikel Jauregizar AlbonigaMIDAthletic Club2.5373provisional2.0456%62
019%
125%
222%
316%
49%
55%
6+4%
Andoni Gorosabel EspinosaDEFAthletic Club2.4965provisional1.7948%35
026%
126%
220%
313%
48%
54%
6+3%
Benat Prados DíazMIDAthletic Club2.8357provisional1.7848%25
024%
127%
221%
313%
48%
54%
6+3%
Francisco José Beltrán PeinadoMIDCelta de Vigo2.2269provisional1.7147%15
025%
128%
221%
313%
47%
53%
6+2%
Iñigo Ruiz de Galarreta EtxeberriaMIDAthletic Club2.3262provisional1.6045%56
025%
130%
222%
313%
46%
53%
6+2%
Yoel Lago AmilDEFCelta de Vigo1.7678provisional1.5243%18
028%
129%
221%
312%
46%
52%
6+1%
Miguel Román GonzálezMIDCelta de Vigo1.9369provisional1.4841%14
032%
127%
219%
312%
46%
53%
6+2%
Daniel Vivian MorenoDEFAthletic Club1.6182provisional1.4742%59
027%
131%
222%
312%
45%
52%
6+1%
Carlos Domínguez CáceresDEFCelta de Vigo1.8766provisional1.3838%22
033%
129%
219%
311%
45%
52%
6+1%
Carl StarfeltDEFCelta de Vigo1.5480provisional1.3739%43
030%
132%
221%
311%
44%
52%
6+1%
Javier Rodríguez GalianoDEFCelta de Vigo1.6774provisional1.3738%61
031%
131%
220%
311%
45%
52%
6+1%
Marcos Alonso MendozaDEFCelta de Vigo1.3486provisional1.2836%62
031%
134%
221%
310%
44%
51%
6+1%
Sergio Carreira VilariñoDEFCelta de Vigo1.4976provisional1.2635%51
033%
132%
220%
310%
44%
51%
6+1%
Yuri Berchiche IzetaDEFAthletic Club1.4877provisional1.2635%56
033%
132%
220%
310%
44%
51%
6+1%
Adama Boiro BoiroDEFAthletic Club1.8860provisional1.2534%25
035%
131%
218%
39%
44%
52%
6+1%
Alejandro Rego MoraMIDAthletic Club2.4644provisional1.1931%16
039%
130%
216%
38%
44%
52%
6+1%
Aymeric LaporteDEFAthletic Club1.2482provisional1.1331%24
035%
134%
219%
38%
43%
51%
6+0%
Damián Rodríguez SousaMIDCelta de Vigo1.7157provisional1.0829%14
041%
130%
216%
38%
43%
51%
6+1%
Manuel Fernández ArroyoDEFCelta de Vigo1.8054provisional1.0829%10
042%
129%
216%
38%
43%
51%
6+1%
Yeray Álvarez LópezDEFAthletic Club1.1682provisional1.0629%27
038%
134%
218%
37%
42%
51%
6+0%
Javier Rueda GarcíaDEFCelta de Vigo1.7654provisional1.0628%19
041%
131%
216%
37%
43%
51%
6+0%
Jesús Areso BlancoDEFAthletic Club1.6358provisional1.0428%18
042%
131%
216%
37%
43%
51%
6+1%
Aitor Paredes CasamichanaDEFAthletic Club1.0182provisional0.9224%39
043%
133%
216%
36%
42%
50%
6+0%
Alejandro Berenguer RemiroFWDAthletic Club1.2267provisional0.9124%58
044%
133%
215%
36%
42%
50%
6+0%
Williot SwedbergFWDCelta de Vigo1.8643provisional0.8923%36
046%
132%
214%
35%
42%
51%
6+0%
Hugo Álvarez AntúnezFWDCelta de Vigo1.4354provisional0.8522%38
048%
130%
214%
35%
42%
51%
6+0%
Nicholas Williams ArthuerFWDAthletic Club1.1268provisional0.8521%50
046%
133%
214%
35%
41%
50%
6+0%
Mikel Vesga ArrutiMIDAthletic Club2.2830provisional0.7618%15
054%
128%
211%
34%
42%
51%
6+0%
Oihan Sancet TirapuMIDAthletic Club1.0960provisional0.7317%49
051%
132%
212%
34%
41%
5+0%
Ferran Jutlgà BlancFWDCelta de Vigo0.9755provisional0.6013%23
058%
129%
210%
33%
41%
5+0%
Pablo Durán FernándezFWDCelta de Vigo1.0750provisional0.5913%37
059%
127%
210%
33%
41%
5+0%
Robert Navarro MuñozFWDAthletic Club1.3041provisional0.5913%18
059%
128%
29%
33%
41%
5+0%
Iñaki Williams ArthuerFWDAthletic Club0.6874provisional0.5612%61
059%
130%
29%
32%
4+0%
Álvaro Djaló Dias FernandesFWDAthletic Club1.2939provisional0.5612%10
060%
128%
29%
32%
41%
5+0%
Gorka Guruzeta RodríguezFWDAthletic Club0.8159provisional0.5311%58
061%
128%
28%
32%
4+1%
Iago Aspas JuncalFWDCelta de Vigo0.9047provisional0.4710%34
066%
124%
27%
32%
40%
5+0%
Jones El-AbdellaouiFWDCelta de Vigo1.3730provisional0.469%7
067%
124%
27%
32%
41%
5+0%
Maroan Sannadi HarrouchFWDAthletic Club0.7640provisional0.346%13
073%
121%
25%
31%
4+0%
Borja Iglesias QuintasFWDCelta de Vigo0.5054provisional0.305%50
075%
120%
24%
3+1%
Nicolás Serrano GaldeanoFWDAthletic Club1.1224provisional0.295%5
078%
117%
24%
31%
4+0%
Unai Simón MendibilGKAthletic Club0.0490provisional0.0458
096%
1+4%
Ionuț Andrei RaduGKCelta de Vigo0.0190provisional0.0138
099%
1+1%

All 43 players shown, ranked by projection. Show fewer ↥

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.

PlayerTeamModel /90Exp. minsProjectedOver 1.5nDistribution
Gorka Guruzeta RodríguezFWDAthletic Club2.5059provisional1.6546%58
025%
129%
222%
313%
47%
53%
6+2%
Iñaki Williams ArthuerFWDAthletic Club1.8574provisional1.5344%61
025%
131%
223%
312%
46%
52%
6+1%
Nicholas Williams ArthuerFWDAthletic Club2.0168provisional1.5243%50
026%
131%
222%
312%
46%
52%
6+1%
Oihan Sancet TirapuMIDAthletic Club2.1860provisional1.4641%49
027%
132%
222%
312%
45%
52%
6+1%
Ferran Jutlgà BlancFWDCelta de Vigo2.1055provisional1.2936%23
033%
131%
220%
310%
44%
52%
6+1%
Alejandro Berenguer RemiroFWDAthletic Club1.6867provisional1.2635%58
032%
133%
220%
310%
44%
51%
6+0%
Borja Iglesias QuintasFWDCelta de Vigo2.0454provisional1.2234%50
036%
130%
218%
39%
44%
51%
6+1%
Iago Aspas JuncalFWDCelta de Vigo2.1847provisional1.1330%34
041%
129%
216%
38%
44%
52%
6+1%
Maroan Sannadi HarrouchFWDAthletic Club2.2940provisional1.0226%13
043%
131%
215%
37%
43%
51%
6+1%
Pablo Durán FernándezFWDCelta de Vigo1.8450provisional1.0227%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.

PlayerTeamModel /90Exp. minsProjectedOver 1.5nDistribution
Moriba Kourouma KouroumaMIDCelta de Vigo2.3267provisional1.7348%54
025%
127%
221%
314%
47%
54%
6+2%
Nicholas Williams ArthuerFWDAthletic Club1.5268provisional1.1532%50
035%
133%
219%
38%
43%
51%
6+0%
Maroan Sannadi HarrouchFWDAthletic Club2.5440provisional1.1330%13
040%
131%
216%
38%
44%
52%
6+1%
Ferran Jutlgà BlancFWDCelta de Vigo1.8355provisional1.1331%23
037%
132%
218%
38%
43%
51%
6+0%
Williot SwedbergFWDCelta de Vigo2.3343provisional1.1130%36
038%
132%
217%
38%
43%
51%
6+0%
Mikel Jauregizar AlbonigaMIDAthletic Club1.3273provisional1.0729%62
037%
134%
218%
37%
42%
51%
6+0%
Borja Iglesias QuintasFWDCelta de Vigo1.7554provisional1.0528%50
041%
131%
217%
37%
43%
51%
6+0%
Alejandro Berenguer RemiroFWDAthletic Club1.3967provisional1.0428%58
039%
134%
218%
37%
42%
51%
6+0%
Iñaki Williams ArthuerFWDAthletic Club1.2274provisional1.0027%61
039%
134%
217%
37%
42%
51%
6+0%
Iñigo Ruiz de Galarreta EtxeberriaMIDAthletic Club1.4162provisional0.9726%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.

PlayerTeamModel /90Exp. minsProjectedOver 0.5nDistribution
Yoel Lago AmilDEFCelta de Vigo0.2878provisional0.2421%18
079%
118%
22%
3+0%
Iñigo Ruiz de Galarreta EtxeberriaMIDAthletic Club0.3462provisional0.2421%56
079%
118%
22%
3+0%
Daniel Vivian MorenoDEFAthletic Club0.2182provisional0.1917%59
083%
116%
22%
3+0%
Marcos Alonso MendozaDEFCelta de Vigo0.1986provisional0.1917%62
083%
115%
21%
3+0%
Aitor Paredes CasamichanaDEFAthletic Club0.2082provisional0.1816%39
084%
115%
2+1%
Alejandro Rego MoraMIDAthletic Club0.3644provisional0.1816%16
084%
114%
22%
3+0%
Moriba Kourouma KouroumaMIDCelta de Vigo0.2467provisional0.1816%54
084%
114%
21%
3+0%
Benat Prados DíazMIDAthletic Club0.2757provisional0.1715%25
085%
114%
21%
3+0%
Andoni Gorosabel EspinosaDEFAthletic Club0.2265provisional0.1615%35
085%
113%
2+1%
Javier Rodríguez GalianoDEFCelta de Vigo0.1974provisional0.1514%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.

PlayerTeamModel /90Exp. minsProjectedOver 2.5nDistribution
Unai Simón MendibilGKAthletic Club2.9090provisional2.9053%58
07%
117%
222%
320%
415%
59%
6+9%
Ionuț Andrei RaduGKCelta de Vigo2.6190provisional2.6147%38
09%
120%
224%
320%
413%
57%
6+7%

1 of 7 markets have no projection for this fixture.