PER90

La Liga · Spain

ElchevFC Barcelona

Estadio Manuel Martínez Valerolineups not announced

Referee

Not appointed

0 matches on record

Fouls per game

League average

23.2

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

Fouls40 playersHighest: Gavi, 1.37 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
GaviMIDFC Barcelona2.7245provisional1.3738%21
036%
126%
217%
311%
46%
52%
6+1%
Buba SangaréDEFElche2.6945provisional1.3538%7
036%
126%
218%
311%
45%
52%
6+1%
Marc CasadóMIDFC Barcelona2.1755provisional1.3337%33
035%
128%
219%
311%
45%
52%
6+1%
Tete MorenteFWDElche1.6772provisional1.3338%11
029%
133%
222%
311%
44%
51%
6+0%
Fermín LópezMIDFC Barcelona2.2553provisional1.3137%40
032%
132%
220%
310%
44%
52%
6+1%
Víctor ChustDEFElche1.4970provisional1.1632%27
036%
132%
219%
39%
43%
51%
6+0%
Lamine YamalFWDFC Barcelona1.1882provisional1.0729%62
035%
135%
219%
37%
42%
51%
6+0%
Germán ValeraFWDElche1.1980provisional1.0629%33
036%
135%
219%
37%
42%
51%
6+0%
Dani OlmoMIDFC Barcelona1.6757provisional1.0528%43
038%
133%
218%
37%
42%
51%
6+0%
Marc BernalMIDFC Barcelona2.2841provisional1.0428%12
044%
128%
215%
38%
43%
51%
6+1%

10 of 40 players shown, ranked by projection. Show all 40 →

Tackles40 playersHighest: Víctor Chust, 2.00 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
Víctor ChustDEFElche2.5770provisional2.0053%27
022%
125%
220%
314%
49%
55%
6+5%
David AffengruberDEFElche2.1582provisional1.9655%35
018%
127%
223%
316%
49%
54%
6+3%
Jules KoundéDEFFC Barcelona2.1878provisional1.9053%55
021%
126%
222%
315%
48%
54%
6+3%
Eric GarcíaDEFFC Barcelona2.3668provisional1.7949%51
025%
127%
221%
313%
48%
54%
6+3%
PedriMIDFC Barcelona2.1176provisional1.7850%61
022%
128%
223%
314%
47%
53%
6+2%
João CanceloDEFFC Barcelona2.4260provisional1.6043%10
030%
126%
219%
312%
47%
53%
6+2%
Marc AguadoMIDElche1.9172provisional1.5343%31
027%
130%
221%
312%
46%
52%
6+1%
Germán ValeraFWDElche1.7180provisional1.5243%33
027%
130%
222%
312%
46%
52%
6+1%
Marc CasadóMIDFC Barcelona2.4155provisional1.4840%33
034%
126%
218%
311%
46%
53%
6+2%
Buba SangaréDEFElche2.9245provisional1.4740%7
036%
124%
217%
311%
46%
53%
6+2%

10 of 40 players shown, ranked by projection. Show all 40 →

Shots40 playersHighest: Lamine Yamal, 3.55 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
Lamine YamalFWDFC Barcelona3.9182provisional3.5582%62
05%
112%
217%
319%
416%
512%
6+18%
RaphinhaFWDFC Barcelona3.3973provisional2.7571%54
010%
119%
221%
319%
414%
59%
6+9%
Robert LewandowskiFWDFC Barcelona3.2867provisional2.4363%50
016%
121%
220%
317%
412%
57%
6+7%
Ferran TorresFWDFC Barcelona3.3751provisional1.9251%40
023%
126%
220%
314%
49%
55%
6+4%
Dani OlmoMIDFC Barcelona2.8557provisional1.8050%43
022%
128%
222%
314%
48%
54%
6+3%
Fermín LópezMIDFC Barcelona2.9053provisional1.7047%40
025%
129%
221%
313%
47%
53%
6+2%
André SilvaFWDElche2.5060provisional1.6646%22
029%
125%
220%
313%
47%
54%
6+2%
Tete MorenteFWDElche1.3672provisional1.0830%11
037%
134%
219%
38%
42%
51%
6+0%
Lucas CepedaFWDElche2.2140provisional0.9825%4
048%
127%
213%
37%
43%
51%
6+1%
Germán ValeraFWDElche1.0880provisional0.9625%33
041%
134%
217%
36%
42%
50%
6+0%
Grady DianganaFWDElche1.5347provisional0.7920%13
049%
131%
213%
35%
41%
5+0%
Roony BardghjiFWDFC Barcelona2.2831provisional0.7719%8
053%
128%
212%
35%
42%
51%
6+0%
PedriMIDFC Barcelona0.7776provisional0.6514%61
054%
132%
211%
33%
41%
5+0%
João CanceloDEFFC Barcelona0.8460provisional0.5612%10
060%
128%
29%
32%
4+1%
Eric GarcíaDEFFC Barcelona0.7068provisional0.5311%51
060%
129%
29%
32%
4+0%
Gonzalo VillarMIDElche0.7860provisional0.5211%8
062%
127%
28%
32%
4+0%
JosanFWDElche1.5529provisional0.5011%5
065%
124%
27%
32%
41%
5+0%
Marc CasadóMIDFC Barcelona0.7755provisional0.4710%33
065%
126%
27%
32%
4+0%
Martim NetoMIDElche0.7854provisional0.479%20
064%
127%
27%
31%
4+0%
Jules KoundéDEFFC Barcelona0.5378provisional0.469%55
064%
128%
27%
31%
4+0%
GaviMIDFC Barcelona0.7445provisional0.377%21
071%
122%
25%
31%
4+0%
David AffengruberDEFElche0.3982provisional0.355%35
071%
124%
25%
3+1%
Alejandro BaldeDEFFC Barcelona0.4669provisional0.355%53
071%
124%
25%
3+1%
Pedro BigasDEFElche0.4174provisional0.345%25
072%
123%
24%
3+1%
Marc BernalMIDFC Barcelona0.7441provisional0.346%12
073%
121%
25%
31%
4+0%
Frenkie de JongMIDFC Barcelona0.5454provisional0.335%37
073%
121%
24%
31%
4+0%
Víctor ChustDEFElche0.3870provisional0.294%27
075%
121%
24%
3+1%
Pau CubarsíDEFFC Barcelona0.3281provisional0.294%63
075%
121%
23%
3+0%
Gerard MartínDEFFC Barcelona0.4453provisional0.264%40
078%
118%
23%
3+0%
Héctor FortDEFElche0.6635provisional0.264%7
079%
117%
23%
3+1%
Léo PétrotDEFElche0.4449provisional0.243%19
080%
117%
23%
3+0%
Buba SangaréDEFElche0.4445provisional0.223%7
081%
116%
22%
3+0%
John DonaldDEFElche0.6131provisional0.213%7
083%
114%
23%
3+1%
Marc AguadoMIDElche0.2672provisional0.202%31
082%
116%
22%
3+0%
Andreas ChristensenDEFFC Barcelona0.4936provisional0.203%7
083%
114%
22%
3+0%
Federico RedondoMIDElche0.9116provisional0.162%2
086%
112%
22%
3+0%
Wojciech SzczesnyGKFC Barcelona0.0090provisional0.0023
0100%
1+0%
Joan GarcíaGKFC Barcelona0.0090provisional0.0030
0100%
1+0%
Iñaki PeñaGKElche0.0090provisional0.0016
0100%
1+0%
Matías DituroGKElche0.0090provisional0.0022
0100%
1+0%

All 40 players shown, ranked by projection. Show fewer ↥

Fouls won40 playersHighest: Lamine Yamal, 1.85 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
Lamine YamalFWDFC Barcelona2.0482provisional1.8553%62
018%
128%
225%
316%
48%
53%
6+2%
Germán ValeraFWDElche2.0080provisional1.7751%33
021%
128%
224%
315%
47%
53%
6+2%
PedriMIDFC Barcelona1.7376provisional1.4642%61
026%
132%
223%
312%
45%
52%
6+1%
Gonzalo VillarMIDElche2.1760provisional1.4440%8
032%
128%
219%
311%
46%
52%
6+1%
Dani OlmoMIDFC Barcelona1.9457provisional1.2234%43
034%
132%
219%
39%
44%
51%
6+1%
Marc CasadóMIDFC Barcelona1.8755provisional1.1532%33
040%
129%
217%
39%
44%
51%
6+1%
André SilvaFWDElche1.6160provisional1.0729%22
041%
130%
217%
38%
43%
51%
6+0%
GaviMIDFC Barcelona2.1245provisional1.0629%21
044%
127%
216%
38%
43%
51%
6+1%
Alejandro BaldeDEFFC Barcelona1.3769provisional1.0629%53
038%
134%
218%
37%
42%
51%
6+0%
Robert LewandowskiFWDFC Barcelona1.3267provisional0.9826%50
042%
132%
217%
37%
42%
51%
6+0%

10 of 40 players shown, ranked by projection. Show all 40 →

Cards40 playersHighest: Víctor Chust, 0.22 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
Víctor ChustDEFElche0.2970provisional0.2220%27
080%
117%
22%
3+0%
Buba SangaréDEFElche0.4245provisional0.2118%7
082%
116%
22%
3+0%
GaviMIDFC Barcelona0.3945provisional0.1917%21
083%
115%
22%
3+0%
David AffengruberDEFElche0.2182provisional0.1917%35
083%
116%
22%
3+0%
Marc BernalMIDFC Barcelona0.4141provisional0.1916%12
084%
114%
22%
3+0%
Marc CasadóMIDFC Barcelona0.3055provisional0.1816%33
084%
114%
22%
3+0%
Eric GarcíaDEFFC Barcelona0.2368provisional0.1716%51
084%
114%
21%
3+0%
Fermín LópezMIDFC Barcelona0.2853provisional0.1615%40
085%
113%
21%
3+0%
Pedro BigasDEFElche0.2074provisional0.1615%25
085%
113%
2+1%
Jules KoundéDEFFC Barcelona0.1878provisional0.1615%55
085%
113%
2+1%

10 of 40 players shown, ranked by projection. Show all 40 →

Saves4 playersHighest: Joan García, 2.88 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
Joan GarcíaGKFC Barcelona2.8890provisional2.8853%30
07%
117%
222%
320%
415%
59%
6+9%
Iñaki PeñaGKElche2.8190provisional2.8151%16
08%
118%
223%
320%
414%
59%
6+8%
Wojciech SzczesnyGKFC Barcelona2.6990provisional2.6949%23
09%
119%
223%
320%
414%
58%
6+7%
Matías DituroGKElche2.6790provisional2.6748%22
09%
119%
223%
320%
414%
58%
6+7%

1 of 7 markets have no projection for this fixture.