Rivermen

GP: 4 | W: 0 | L: 4
GF: 8 | GA: 15 | PP%: 25.00% | PK%: 70.59%
DG: Interim Steve Bourdages | Morale : 50 | Moyenne d'Équipe : 63
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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 SP
1Derek GrantX100.00743892827368705469515775556977045710
2Joel Eriksson EkX100.00923588836773815463505872564869050710
3Stefan NoesenX100.00943784836668645451505867566075050700
4Dale Weise (A)X100.00783991836868665251475668547579050690
5Brendan GaunceX100.00643693817260414951445470525767050640
6Rudolfs Balcers (R)X100.00513393875264435247495565534861047630
7Pascal DupuisX100.00513195826654254742425359529984047620
8Brad BoyesX100.00473195836253324742435157529379047610
9Ben StreetX100.00503495845957254748415264527874047610
10Andy AndreoffX100.00604492836557404746435256516668050610
11Jordan SchroederX100.00493295864655294746425256516968050590
12Anton Blidh (R)X100.00473495826255254548405055505459050570
13Justin FalkX100.0082399281776342495048516650757904069X0
14Steven SantiniX100.00833491836574465248515370525470031690
15Jordan SchmaltzX100.00483295856064254948475057506064050610
16David WarsofskyX100.00452995864356254749475057506968050590
17Jacob Middleton (R)X100.00453295826851254847465057505159050590
Rayé
1Michael RyderX100.00473195836452274641415156509982047610
2Steve BernierX100.00503395807654294644425157518475047610
3Liam O'Brien (R)X100.00453095806950254540405055505760050570
4Danick Martel (R)X100.00493395854657254648425055505761050570
5Yohann AuvituX100.00493195855360314949485357527270047610
6Michael Paliotta (R)X100.00453295827150254548455055506063046590
7Andreas Englund (R)X100.00473295866151254847455057505159050590
8Robbie Russo (R)X100.00453195845550254548455055506063050580
9Riley Stillman (R)X100.00473195846050254847455055504555050580
MOYENNE D'ÉQUIPE100.0057349483635836484845526152666904862
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
1Harri Sateri100.0066257176666667666665567362047630
Rayé
1Cal Petersen (R)100.0080256571847983798265595357045730
2Marcus Hogberg (R)100.0071258179677374716965575353046660
3Jason Kasdorf (R)100.0060256469666060606065556153043580
MOYENNE D'ÉQUIPE100.006925707471707169696557605604565
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Ralph Krueger70707070717155CAN603900,000$


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
1Stefan NoesenRivermen (STL)RW4426-1100108142828.57%38621.66123211000010037.50%843001.3800000100
2Joel Eriksson EkRivermen (STL)C414502012614377.14%19523.85112211000190052.03%14862001.0500000001
3Jordan SchmaltzRivermen (STL)D4022120285320.00%48521.440000700008000.00%006000.4700000000
4Rudolfs BalcersRivermen (STL)LW40220006313260.00%28721.7501121100002000.00%491000.4600000000
5Justin FalkRivermen (STL)D4101-5605598211.11%511729.3210131400019000.00%034000.1700000000
6Steven SantiniRivermen (STL)D4101-56051111149.09%811629.0210131400018000.00%0510000.1700000000
7Andy AndreoffRivermen (STL)LW4011-200724530.00%26716.98011010000010075.00%420000.2900000000
8Jordan SchroederRivermen (STL)LW4011-100227260.00%14711.77000000000000100.00%121000.4200000000
9Brendan GaunceRivermen (STL)C4101-1006581612.50%25112.8100000000010054.84%3141000.3900000000
10Derek GrantRivermen (STL)C4011-30059115140.00%08020.000110100000100051.85%5462000.2500000000
11David WarsofskyRivermen (STL)D4000-240023010.00%45814.530000000000000.00%004000.0000000000
12Jacob MiddletonRivermen (STL)D4000-100102010.00%45614.100000000003000.00%004000.0000000000
13Yohann AuvituRivermen (STL)D1000000011100.00%11818.520000300003000.00%012000.0000000000
14Brad BoyesRivermen (STL)RW4000-200145610.00%2369.250000000000000.00%132000.0000000000
15Dale WeiseRivermen (STL)RW4000-2005411360.00%27218.1900001000014000.00%362000.0000000000
16Pascal DupuisRivermen (STL)RW4000-100227230.00%14912.460000000000000.00%122000.0000000000
17Anton BlidhRivermen (STL)LW4000-200000350.00%1369.110000000000000.00%000000.0000000000
18Ben StreetRivermen (STL)C4000-300547180.00%04411.1800000000060033.33%1852000.0000000000
Stats d'équipe Total ou en Moyenne6981321-30300747613248836.06%43120817.514610121090004700049.45%2735848000.3500000101
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
1Harri SateriRivermen (STL)30210.9342.6118420812264000.000024010
2Cal PetersenRivermen (STL)20100.8115.60750073715100.000020000
Stats d'équipe Total ou en Moyenne50310.9063.48259201515979100.000044010


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 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
Andreas EnglundRivermen (STL)D231996-01-01Yes189 Lbs6 ft3NoNoNo2Pro & Farm750,000$0$0$No750,000$Lien / Lien NHL
Andy AndreoffRivermen (STL)LW281991-01-01No203 Lbs6 ft1NoNoNo1Pro & Farm1,000,000$0$0$NoLien NHL
Anton BlidhRivermen (STL)LW241995-01-01Yes201 Lbs6 ft0NoNoNo2Pro & Farm650,000$0$0$No650,000$Lien NHL
Ben StreetRivermen (STL)C321987-01-01No190 Lbs6 ft0NoNoNo2Pro & Farm500,000$0$0$No500,000$
Brad BoyesRivermen (STL)RW371982-01-01No199 Lbs6 ft0NoNoNo2Pro & Farm500,000$0$0$No500,000$
Brendan GaunceRivermen (STL)C251994-01-01No217 Lbs6 ft2NoNoNo4Pro & Farm600,000$0$0$No600,000$600,000$600,000$Lien NHL
Cal PetersenRivermen (STL)G251994-01-01Yes185 Lbs6 ft1NoNoNo2Pro & Farm700,000$0$0$No700,000$
Dale Weise (Contrat à 1 Volet)Rivermen (STL)RW311988-01-01No206 Lbs6 ft2NoNoNo1Farm Only1,200,000$120,000$0$NoLien NHL
Danick MartelRivermen (STL)LW251994-01-01Yes176 Lbs5 ft8NoNoNo4Pro & Farm500,000$0$0$No500,000$500,000$500,000$Lien NHL
David WarsofskyRivermen (STL)D291990-01-01No170 Lbs5 ft9NoNoNo1Pro & Farm700,000$0$0$NoLien / Lien NHL
Derek GrantRivermen (STL)C291990-01-01No215 Lbs6 ft3NoNoNo1Pro & Farm750,000$0$0$NoLien NHL
Harri SateriRivermen (STL)G301989-01-01No205 Lbs6 ft1NoNoNo3Pro & Farm500,000$0$0$No500,000$500,000$Lien NHL
Jacob MiddletonRivermen (STL)D231996-01-01Yes210 Lbs6 ft3NoNoNo2Pro & Farm550,000$0$0$No550,000$Lien
Jason KasdorfRivermen (STL)G271992-01-01Yes172 Lbs6 ft3NoNoNo1Pro & Farm500,000$0$0$No
Joel Eriksson EkRivermen (STL)C221997-01-01No208 Lbs6 ft1NoNoNo2Pro & Farm1,000,000$0$0$No1,000,000$Lien NHL
Jordan SchmaltzRivermen (STL)D261993-01-01No190 Lbs6 ft2NoNoNo2Pro & Farm775,000$0$0$No775,000$Lien / Lien NHL
Jordan SchroederRivermen (STL)LW291990-01-01No170 Lbs5 ft9NoNoNo1Pro & Farm800,000$0$0$NoLien NHL
Justin FalkRivermen (STL)D311988-01-01No223 Lbs6 ft5NoYesNo1Pro & Farm850,000$0$0$NoLien / Lien NHL
Liam O'BrienRivermen (STL)C251994-01-01Yes215 Lbs6 ft1NoNoNo1Pro & Farm675,000$0$0$NoLien NHL
Marcus HogbergRivermen (STL)G251994-01-01Yes209 Lbs6 ft5NoNoNo2Pro & Farm700,000$0$0$No700,000$
Michael PaliottaRivermen (STL)D261993-01-01Yes212 Lbs6 ft4NoNoNo1Pro & Farm800,000$0$0$NoLien
Michael RyderRivermen (STL)RW391980-01-01No200 Lbs6 ft1NoNoNo2Pro & Farm500,000$0$0$No500,000$
Pascal DupuisRivermen (STL)RW401979-01-01No205 Lbs6 ft1NoNoNo2Pro & Farm500,000$0$0$No500,000$
Riley StillmanRivermen (STL)D211998-01-01Yes196 Lbs6 ft1NoNoNo2Pro & Farm550,000$0$0$No550,000$Lien
Robbie RussoRivermen (STL)D261993-01-01Yes189 Lbs6 ft0NoNoNo2Pro & Farm800,000$0$0$No800,000$Lien
Rudolfs BalcersRivermen (STL)LW221997-01-01Yes175 Lbs5 ft11NoNoNo2Pro & Farm550,000$0$0$No550,000$
Stefan NoesenRivermen (STL)RW261993-01-01No205 Lbs6 ft1NoNoNo1Pro & Farm750,000$0$0$NoLien NHL
Steve BernierRivermen (STL)RW341985-01-01No224 Lbs6 ft3NoNoNo3Pro & Farm500,000$0$0$No500,000$500,000$Lien NHL
Steven SantiniRivermen (STL)D241995-01-01No205 Lbs6 ft2NoNoNo2Pro & Farm700,000$0$0$No700,000$Lien / Lien NHL
Yohann AuvituRivermen (STL)D301989-01-01No191 Lbs5 ft11NoNoNo2Pro & Farm500,000$0$0$No500,000$Lien / Lien NHL
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
3027.80199 Lbs6 ft11.87678,333$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Rudolfs BalcersJoel Eriksson EkStefan Noesen40122
2Andy AndreoffDerek GrantDale Weise30122
3Jordan SchroederBrendan GauncePascal Dupuis20122
4Anton BlidhBen StreetBrad Boyes10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Justin FalkSteven Santini40122
2Jordan Schmaltz30122
3David WarsofskyJacob Middleton20122
4Justin FalkSteven Santini10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Rudolfs BalcersJoel Eriksson EkStefan Noesen60122
2Andy AndreoffDerek GrantDale Weise40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Justin FalkSteven Santini60122
2Jordan Schmaltz40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Joel Eriksson EkDerek Grant60122
2Stefan NoesenDale Weise40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Justin FalkSteven Santini60122
2Jordan Schmaltz40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Joel Eriksson Ek60122Justin FalkSteven Santini60122
2Derek Grant40122Jordan Schmaltz40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Joel Eriksson EkDerek Grant60122
2Stefan NoesenDale Weise40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Justin FalkSteven Santini60122
2Jordan Schmaltz40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Rudolfs BalcersJoel Eriksson EkStefan NoesenJustin FalkSteven Santini
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Rudolfs BalcersJoel Eriksson EkStefan NoesenJustin FalkSteven Santini
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Brendan Gaunce, Pascal Dupuis, Ben StreetBrendan Gaunce, Pascal DupuisBen Street
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
David Warsofsky, Jacob Middleton, Jordan SchmaltzDavid WarsofskyJacob Middleton, Jordan Schmaltz
Tirs de Pénalité
Joel Eriksson Ek, Derek Grant, Stefan Noesen, Dale Weise, Brendan Gaunce
Gardien
#1 : , #2 : Harri Sateri


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
Total40400000815-72020000026-42020000069-300.00081321002240133254560315944347616425.00%17570.59%04110041.00%5710554.29%376854.41%864794397838
2Walleye40400000815-72020000026-42020000069-300.00081321002240133254560315944347616425.00%17570.59%04110041.00%5710554.29%376854.41%864794397838
_Since Last GM Reset40400000815-72020000026-42020000069-300.00081321002240133254560315944347616425.00%17570.59%04110041.00%5710554.29%376854.41%864794397838
_Vs Conference40400000815-72020000026-42020000069-300.00081321002240133254560315944347616425.00%17570.59%04110041.00%5710554.29%376854.41%864794397838
_Vs Division40400000815-72020000026-42020000069-300.00081321002240133254560315944347616425.00%17570.59%04110041.00%5710554.29%376854.41%864794397838

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
40L28132113315944347600
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
4040000815
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
202000026
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
202000069
Derniers 10 Matchs
WLOTWOTL SOWSOL
030100
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
16425.00%17570.59%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
25456032240
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
4110041.00%5710554.29%376854.41%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
864794397838


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 - 2020-01-097Rivermen3Walleye5LSommaire du Match
2 - 2020-01-1015Rivermen3Walleye4LXSommaire du Match
3 - 2020-01-1123Walleye3Rivermen1LSommaire du Match
4 - 2020-01-1231Walleye3Rivermen1LSommaire du Match



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité de l'Aréna20001000
Prix des Billets5530
Assistance2,6351,189
Assistance PCT65.88%59.45%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
39 1912 - 63.73% 103,842$207,684$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
0$ 1,915,000$ 1,915,000$ 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$ 0 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
Saison Régulière
117886302311162418-256393300221180210-130395330010082208-12616162303465202959713193456865769222228479111409052286428.07%47926844.05%8513133738.37%517141736.49%556136740.67%1693108116917801318543
12823725024682591996041231202211129963341141300257130103277425940866726481031001928398341029940922479816599182728712643.90%26311357.03%3963176254.65%985182953.85%660117656.12%1842105116707371488771
1382382902184285237484120130014314511233411816020411401251576285464749125798120172827803994994782490882714167731217054.49%34713561.10%2934181251.55%902173152.11%704127355.30%1850106916617411478747
1482353102167231223841171601124116122-641181501043115101147023137660711429190142710783958936772512812753174931611737.03%34212862.57%41130190159.44%988180754.68%665115657.53%1822102716827481485759
15823730033452482212741161502242122108144121150110312611313742484116590233991091528438459641005652416848858159128912342.56%37013463.78%4885175250.51%876169551.68%667120955.17%1869111316817281427722
1682363002473260234264118150133113711819411815011421231167722604206802442107102182633716992903562558861738170528511440.00%33912363.72%5871167951.88%902173152.11%672122055.08%178399417437111456764
1782293804137250278-2841171601115138146-841122203022112132-2058250409659104385115102616732910949532541885663143032814845.12%30013654.67%8848169050.18%724151247.88%640124751.32%174099517907491455727
1882323303428220241-2141161701115109125-1641161602313111116-56422038160103348893828207609571055872478804614146829712642.42%29513155.59%6951182952.00%843166550.63%643121253.05%1847112217237401413691
19823626022124254201534117150024312911712411911020811258441722543926461536103101232589717890951842360827553158431813642.77%27510063.64%1941169255.61%943173054.51%655115256.86%175298217607511494755
Total Saison Régulière73428830502223494721692252-8336714714901015212511051154-493671411560128282210641098-345762169356457331023364833901127238116758835184256142211875266632139362660112442.26%3010126857.87%4180361545452.00%76801511750.80%58621101253.23%162039437154056688130186483
Séries
122316700000534761210200000292181165000002426-232538814120820151070920224023829751313179528962829.17%852570.59%026453049.81%24453745.44%13329644.93%495267493222433219
131257000004247-5532000002122-1725000002125-41042691111081320148412218316712418147100206472042.55%503040.00%016032649.08%11424446.72%8619843.43%27116725111220999
14514000001117-62020000047-331200000710-321119300025401815366611120475410910440.00%271255.56%06713051.54%449247.83%416860.29%1136693479346
15514000001221-92020000048-431200000813-521220320016412115169731815139425718527.78%211338.10%15414437.50%358342.17%347644.74%1329299458236
16514000001221-92020000048-431200000813-521220320016412115169731815139425718527.78%211338.10%15414437.50%358342.17%347644.74%1329299458236
1940400000815-72020000026-42020000069-3081321002240133254560315944347616425.00%17570.59%04110041.00%5710554.29%376854.41%864794397838
1940400000815-72020000026-42020000069-3081321002240133254560315944347616425.00%17570.59%04110041.00%5710554.29%376854.41%864794397838
Total Séries58243400000146183-37271314000006678-123111200000080105-25481462423883024545513206252971773284190967348511092217031.67%23810356.72%2681147446.20%586124946.92%40285047.29%132078212265541059513