BINGHAMTON Devils
GP: 1 | W: 1 | L: 0
GF: 3 | GA: 2 | PP%: 0.00% | PK%: 100.00%
DG: Maxime Joseph | Morale : 99 | Moyenne d'Équipe : 66
Prochain matchs #12 vs GRAND RAPIDS Griffins
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Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du Joueur #C L R D CON CK FG DI SK ST EN DU PH FO PA SC DF PS EX LD PO MO OV TA SPÂgeContratSalaire
1Jeremy Bracco0X100.005339876958868467736857596665636799670233750,000$
2Lane Pederson0X100.005849836372888261736062586365616399670231950,000$
3Joel L'Esperance0X100.006546896483787562585963616469655399670255950,000$
4Joachim Blichfeld (R)0X100.006542896376777362566061666463655699670223750,000$
5Ryan McLeod (R)0X100.006847876382868561675954565861637699670203750,000$
6Aleksi Saarela (R)0X100.005941906370847962566061596265636499660233750,000$
7Matthew Peca0X100.0054398664667877637462616564736658996602711,300,000$
8Zack MacEwen0X100.006553816284737263666062616467635299660245950,000$
9Karson Kuhlman (R)0X100.005841826269797859635860615969645599650244750,000$
10Kole Lind (R)0X100.005751856073868258545956615863627799650214750,000$
11Jakob Stukel (R)0X100.005639845771757256535558595665636299620233750,000$
12Juuso Riikola0X100.008239906472797763306556614873673699680262750,000$
13Keaton Middleton (R)0X100.008659795699878355305454624663626499680223750,000$
14Cale Fleury0X100.007243886378837762306158645362616499670211950,000$
15Dylan Coghlan0X100.006245905978878958305757604563626499660221950,000$
16Nelson Nogier0X100.006247885979777658305756605367645999650245950,000$
17Kale Clague0X100.005743896370817261306058625463617299650221950,000$
18Sergey Zborovskiy (R)0X100.005141775082442750304444605050504499500233750,000$
Rayé
1Ryan Donato0X100.0063398772738278696367705872676568997002422,000,000$
MOYENNE D'ÉQUIPE100.00634486627679766151595861586563619965
Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du Gardien CON SK DU EN SZ AG RB SC HS RT PH PS EX LD PO MO OV TA SP
1Patrik Rybar (R)100.00766681787574767574757050634299660
Rayé
MOYENNE D'ÉQUIPE100.0076668178757476757475705063429966
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire


Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du Joueur Nom de l'ÉquipePOSGP G A P +/- PIM PIM5 HIT HTT SHT OSB OSM SHT% SB MP AMG PPG PPA PPP PPS PPM PKG PKA PKP PKS PKM GW GT FO% FOT GA TA EG HT P/20 PSG PSS FW FL FT S1 S2 S3
1Matthew PecaBINGHAMTON Devils (NJD)C12023000480125.00%01818.4300000000001036.84%1900002.1700000100
2Jeremy BraccoBINGHAMTON Devils (NJD)RW1022100252130.00%23131.9200005000010040.00%500001.2500000001
3Kole LindBINGHAMTON Devils (NJD)RW111230011103100.00%01818.430000000000000.00%200002.1700000010
4Aleksi SaarelaBINGHAMTON Devils (NJD)C1011100111010.00%077.28000000000000100.00%300002.7500000000
5Cale FleuryBINGHAMTON Devils (NJD)D1011000001000.00%01212.970000000000000.00%000001.5400000000
6Keaton MiddletonBINGHAMTON Devils (NJD)D1011100203000.00%01616.630001200000000.00%000001.2000000000
7Lane PedersonBINGHAMTON Devils (NJD)C1000000026240.00%02222.0300034000000050.00%3000000.0000000000
8Zack MacEwenBINGHAMTON Devils (NJD)RW1000-100001020.00%01111.200000000000000.00%100000.0000000000
9Dylan CoghlanBINGHAMTON Devils (NJD)D1000000200000.00%01010.620000000000000.00%000000.0000000000
10Joel L'EsperanceBINGHAMTON Devils (NJD)C1000-220111330.00%22828.2800015000010032.00%2500000.0000000000
11Juuso RiikolaBINGHAMTON Devils (NJD)D1000000100010.00%11212.970000000000000.00%000000.0000000000
12Kale ClagueBINGHAMTON Devils (NJD)D1000000010000.00%11010.620000000000000.00%000000.0000000000
13Karson KuhlmanBINGHAMTON Devils (NJD)C1000000000000.00%011.720000000000000.00%000000.0000000000
14Jakob StukelBINGHAMTON Devils (NJD)LW1000-100005000.00%11616.15000350000000100.00%100000.0000000000
15Joachim BlichfeldBINGHAMTON Devils (NJD)RW1000020202240.00%02020.270000400000000.00%000000.0000000000
16Ryan McLeodBINGHAMTON Devils (NJD)C1000-100304160.00%03030.3800004000000053.85%1300000.0000000000
Stats d'équipe Total ou en Moyenne163694401515359288.57%726916.87000831000031043.43%9900000.6700000111
Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du Gardien Nom de l'ÉquipeGP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA ST BG S1 S2 S3
1Patrik RybarBINGHAMTON Devils (NJD)11000.9351.7170002310000.000010000
Stats d'équipe Total ou en Moyenne11000.9351.7170002310000.000010000


Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
Nom du Joueur Nom de l'ÉquipePOS Âge Date de Naissance Nouveau Joueur Poids Taille Non-Échange Disponible pour Échange Ballotage Forcé Contrat Type Salaire Actuel Salaire RestantSalaire MoyenSalaire Moyen RestantCap Salariale Cap Salariale Restant Exclus du Cap Salarial Salaire Année 2Salaire Année 3Salaire Année 4Salaire Année 5Salaire Année 6Salaire Année 7Salaire Année 8Salaire Année 9Salaire Année 10Link
Aleksi SaarelaBINGHAMTON Devils (NJD)C231/7/1997Yes91 Kg178 CMNoNoNo3Pro & Farm750,000$642,857$750,000$642,857$0$0$No750,000$750,000$
Cale FleuryBINGHAMTON Devils (NJD)D2110/19/1998No93 Kg185 CMNoNoNo1Pro & Farm950,000$814,286$750,000$642,857$0$0$NoLien
Dylan CoghlanBINGHAMTON Devils (NJD)D222/19/1998No86 Kg188 CMNoNoNo1Pro & Farm950,000$814,286$750,000$642,857$0$0$NoLien
Jakob StukelBINGHAMTON Devils (NJD)LW233/6/1997Yes83 Kg183 CMNoNoNo3Pro & Farm750,000$642,857$750,000$642,857$0$0$No750,000$750,000$
Jeremy BraccoBINGHAMTON Devils (NJD)RW233/17/1997No82 Kg155 CMNoNoNo3Pro & Farm750,000$642,857$750,000$642,857$0$0$No750,000$750,000$
Joachim BlichfeldBINGHAMTON Devils (NJD)RW227/17/1998Yes82 Kg188 CMNoNoNo3Pro & Farm750,000$642,857$750,000$642,857$0$0$No750,000$750,000$
Joel L'EsperanceBINGHAMTON Devils (NJD)C258/18/1995No98 Kg188 CMNoNoNo5Pro & Farm950,000$814,286$750,000$642,857$0$0$No950,000$950,000$950,000$950,000$Lien
Juuso RiikolaBINGHAMTON Devils (NJD)D2611/9/1993No86 Kg183 CMNoNoNo2Pro & Farm750,000$642,857$750,000$642,857$0$0$No750,000$Lien
Kale ClagueBINGHAMTON Devils (NJD)D226/5/1998No80 Kg183 CMNoNoNo1Pro & Farm950,000$814,286$750,000$642,857$0$0$NoLien
Karson KuhlmanBINGHAMTON Devils (NJD)C249/26/1995Yes84 Kg180 CMNoNoNo4Pro & Farm750,000$642,857$750,000$642,857$0$0$No750,000$750,000$750,000$
Keaton MiddletonBINGHAMTON Devils (NJD)D222/10/1998Yes109 Kg198 CMNoNoNo3Pro & Farm750,000$642,857$750,000$642,857$0$0$No750,000$750,000$
Kole LindBINGHAMTON Devils (NJD)RW2110/16/1998Yes81 Kg185 CMNoNoNo4Pro & Farm750,000$642,857$750,000$642,857$0$0$No750,000$750,000$750,000$
Lane PedersonBINGHAMTON Devils (NJD)C238/4/1997No86 Kg183 CMNoNoNo1Pro & Farm950,000$814,286$750,000$642,857$0$0$NoLien
Matthew PecaBINGHAMTON Devils (NJD)C274/27/1993No83 Kg175 CMNoNoNo1Pro & Farm1,300,000$1,114,286$1,300,000$1,114,286$0$0$NoLien
Nelson NogierBINGHAMTON Devils (NJD)D245/27/1996No87 Kg188 CMNoNoNo5Pro & Farm950,000$814,286$750,000$642,857$0$0$No950,000$950,000$950,000$950,000$Lien
Patrik RybarBINGHAMTON Devils (NJD)G2611/9/1993Yes86 Kg188 CMNoNoNo2Pro & Farm900,000$771,429$750,000$642,857$0$0$No900,000$Lien
Ryan DonatoBINGHAMTON Devils (NJD)C244/9/1996No87 Kg183 CMNoNoNo2Pro & Farm2,000,000$1,714,286$750,000$642,857$0$0$No2,000,000$Lien
Ryan McLeodBINGHAMTON Devils (NJD)C209/21/1999Yes94 Kg188 CMNoNoNo3Pro & Farm750,000$642,857$750,000$642,857$0$0$No750,000$750,000$
Sergey ZborovskiyBINGHAMTON Devils (NJD)D232/21/1997Yes95 Kg193 CMNoNoNo3Pro & Farm750,000$642,857$750,000$642,857$0$0$No750,000$750,000$
Zack MacEwenBINGHAMTON Devils (NJD)RW247/8/1996No93 Kg191 CMNoNoNo5Pro & Farm950,000$814,286$750,000$642,857$0$0$No950,000$950,000$950,000$950,000$Lien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2023.2588 Kg185 CM2.75917,500$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Jakob StukelJoel L'EsperanceJeremy Bracco31122
2Ryan McLeodLane PedersonJoachim Blichfeld26122
3Joel L'EsperanceRyan McLeodZack MacEwen23122
4Jeremy BraccoMatthew PecaKole Lind20122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
131122
2Keaton Middleton26122
3Juuso RiikolaCale Fleury23122
4Dylan CoghlanKale Clague20122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Jakob StukelJoel L'EsperanceJeremy Bracco55122
2Ryan McLeodLane PedersonJoachim Blichfeld45122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
155122
2Keaton Middleton45122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Joel L'EsperanceJeremy Bracco55122
2Lane PedersonRyan McLeod45122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
155122
2Keaton Middleton45122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Joel L'Esperance5512255122
2Jeremy Bracco45122Keaton Middleton45122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Joel L'EsperanceJeremy Bracco55122
2Lane PedersonRyan McLeod45122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
155122
2Keaton Middleton45122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Jakob StukelJoel L'EsperanceJeremy Bracco
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Jakob StukelJoel L'EsperanceJeremy Bracco
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Aleksi Saarela, Karson Kuhlman, Zack MacEwenAleksi Saarela, Karson KuhlmanZack MacEwen
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Nelson Nogier, Sergey Zborovskiy, Juuso RiikolaNelson NogierSergey Zborovskiy, Juuso Riikola
Tirs de Pénalité
Joel L'Esperance, Jeremy Bracco, Lane Pederson, Ryan McLeod, Joachim Blichfeld
Gardien
#1 : Patrik Rybar, #2 :
Lignes d'Attaque Perso. en Prol.
Joel L'Esperance, Jeremy Bracco, Lane Pederson, Ryan McLeod, Joachim Blichfeld, Zack MacEwen, Zack MacEwen, Matthew Peca, Aleksi Saarela, Karson Kuhlman, Kole Lind
Lignes de Défense Perso. en Prol.
, , , Keaton Middleton, Juuso Riikola


Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
LigueDomicileVisiteur
# VS Équipe GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff P PCT G A TP SO EG GP1 GP2 GP3 GP4 SHF SH1 SP2 SP3 SP4 SHA SHB Pim Hit PPA PPG PP% PKA PK GA PK% PK GF W OF FO T OF FO OF FO% W DF FO T DF FO DF FO% W NT FO T NT FO NT FO% PZ DF PZ OF PZ NT PC DF PC OF PC NT
1GRAND RAPIDS Griffins11000000321110000003210000000000021.00036900110135141173317416500.00%10100.00%0204247.62%133834.21%101952.63%2921278146
Total11000000321110000003210000000000021.00036900110135141173317416500.00%10100.00%0204247.62%133834.21%101952.63%2921278146
_Since Last GM Reset11000000321110000003210000000000021.00036900110135141173317416500.00%10100.00%0204247.62%133834.21%101952.63%2921278146
_Vs Conference11000000321110000003210000000000021.00036900110135141173317416500.00%10100.00%0204247.62%133834.21%101952.63%2921278146

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
12W13693531741600
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
110000032
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
110000032
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
000000000
Derniers 10 Matchs
WLOTWOTL SOWSOL
100000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
500.00%10100.00%0
Tirs en 1e PériodeTirs en 2e PériodeTirs en 3e PériodeTirs en 4e PériodeButs en 1e PériodeButs en 2e PériodeButs en 3e PériodeButs en 4e Période
1411731101
Mises en Jeu
Gagnées en Zone OffensiveTotal en Zone Offensive% Gagnées en Zone Offensive Gagnées en Zone DéfensiveTotal en Zone Défensive% Gagnées en Zone DéfensiveGagnées en Zone NeutreTotal en Zone Neutre% Gagnées en Zone Neutre
204247.62%133834.21%101952.63%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
2921278146


Derniers Match Joués
Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
JourMatch Équipe Visiteuse Score Équipe Locale Score ST OT SO RI Lien
1 - 2021-05-154GRAND RAPIDS Griffins2BINGHAMTON Devils3WXSommaire du Match
3 - 2021-05-1712GRAND RAPIDS Griffins-BINGHAMTON Devils-
5 - 2021-05-1920BINGHAMTON Devils-GRAND RAPIDS Griffins-
7 - 2021-05-2128BINGHAMTON Devils-GRAND RAPIDS Griffins-
9 - 2021-05-2336GRAND RAPIDS Griffins-BINGHAMTON Devils-
11 - 2021-05-2544BINGHAMTON Devils-GRAND RAPIDS Griffins-
13 - 2021-05-2752GRAND RAPIDS Griffins-BINGHAMTON Devils-



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des Billets3515
Assistance00
Assistance PCT0.00%0.00%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacitéPopularité de l'Équipe
39 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
0$ 1,835,000$ 1,555,000$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 0$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 12 0$ 0$




LigueDomicileVisiteur
Année GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff P G A TP SO EG GP1 GP2 GP3 GP4 SHF SH1 SP2 SP3 SP4 SHA SHB Pim Hit PPA PPG PP% PKA PK GA PK% PK GF W OF FO T OF FO OF FO% W DF FO T DF FO DF FO% W NT FO T NT FO NT FO% PZ DF PZ OF PZ NT PC DF PC OF PC NT