Checkers

GP: 27 | W: 0 | L: 27 | OTL: 0 | P: 0
GF: 14 | GA: 168 | PP%: 1.23% | PK%: 74.07%
DG: Sebastien Chando | Morale : 33 | Moyenne d'Équipe : 61
Prochain matchs #402 vs Wolf Pack
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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
1Alex BelzileX100.005640796170949560686156585475685753620
2Jordan Kyrou (R)X100.005236926369776662726461596562627653610
3Anders BjorkX100.005435925872776256536057595665635557580
4Anthony LouisX100.005336905758949556615753525567646147580
5Kevin RoyX100.005836915763736056635854595371666357570
6Tyler Vesel (R)X100.005235955558928854585551535269656053570
7Nic HagueX100.007837885795949556305654624761636452650
8Anton LindholmX100.007835905971766958306052714669655457640
9Henri Jokiharju (R)X100.006938866573837864307356625361638253640
10Adam ClendeningX100.005539816274786661306254664773676557620
11Julius BergmanX100.006536915678857955305452575167646857610
12Stefan Elliott (R)X100.005635946075797059306154575375686253610
13David WarsofskyX100.005239816063908459306352534777695147600
14Lucas JohansenX100.006037885677868055305651544563627357600
15Dylan BlujusX100.006539815582857954305350564869657257600
16Kale Clague (R)X100.005438865970908458306053564861637753600
17Logan PyettX100.006339745771747056306058535466675243590
Rayé
1Blake SpeersX100.005837875569857954625352555463626333570
2Tyler Steenbergen (R)X100.005136925659928955585553525461636429570
3Skyler McKenzie (R)X100.005237875659878155565453525561636429560
4James De HaasX100.005634805576767255305652564564655333580
MOYENNE D'ÉQUIPE100.00593787587184785743595457526765644960
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
1Calvin Pickard100.00767775797574767574767573776352730
2Jake Paterson100.00626462736160626160626169737157620
Rayé
MOYENNE D'ÉQUIPE100.0069716976686769686769687175675568
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Ian Laperriere73676461686380CAN4551,000,000$


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'ÉquipePOS GP 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
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


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 StatusType Salaire Actuel Cap Salariale Cap Salariale Restant Exclus du Cap Salarial Link
Adam ClendeningCheckers (Car)D261992-10-26No196 Lbs6 ft0NoNoNo1Avec RestrictionPro & Farm300,000$0$0$NoLien
Alex BelzileCheckers (Car)C271991-08-31No188 Lbs5 ft11NoNoNo4Avec RestrictionPro & Farm300,000$0$0$NoLien
Anders BjorkCheckers (Car)LW221996-08-05No190 Lbs6 ft0NoNoNo3Contrat d'EntréePro & Farm300,000$0$0$NoLien
Anthony LouisCheckers (Car)LW241995-02-10No151 Lbs5 ft7NoNoNo2Avec RestrictionPro & Farm300,000$0$0$NoLien
Anton LindholmCheckers (Car)D241994-11-29No191 Lbs5 ft11NoNoNo2Avec RestrictionPro & Farm300,000$0$0$NoLien
Blake SpeersCheckers (Car)C221997-01-02No185 Lbs5 ft11NoNoNo3Contrat d'EntréePro & Farm500,000$0$0$NoLien
Calvin PickardCheckers (Car)G271992-04-15No207 Lbs6 ft1NoNoNo4Avec RestrictionPro & Farm750,000$0$0$NoLien
David WarsofskyCheckers (Car)D291990-05-30No170 Lbs5 ft9NoNoNo3Sans RestrictionPro & Farm500,000$0$0$NoLien
Dylan BlujusCheckers (Car)D251994-01-22No191 Lbs6 ft3NoNoNo1Avec RestrictionPro & Farm300,000$0$0$NoLien
Henri JokiharjuCheckers (Car)D201999-06-17Yes193 Lbs6 ft0NoNoNo4Contrat d'EntréePro & Farm900,000$0$0$NoLien
Jake PatersonCheckers (Car)G251994-05-03No176 Lbs6 ft1NoNoNo1Avec RestrictionPro & Farm300,000$0$0$NoLien
James De HaasCheckers (Car)D251994-05-03No210 Lbs6 ft4NoNoNo3Avec RestrictionPro & Farm300,000$0$0$NoLien
Jordan KyrouCheckers (Car)C211998-05-05Yes175 Lbs6 ft0NoNoNo4Contrat d'EntréePro & Farm500,000$0$0$NoLien
Julius BergmanCheckers (Car)D231995-11-02No205 Lbs6 ft1NoNoNo1Avec RestrictionPro & Farm500,000$0$0$NoLien
Kale ClagueCheckers (Car)D211998-06-05Yes177 Lbs6 ft0NoNoNo4Contrat d'EntréePro & Farm500,000$0$0$NoLien
Kevin RoyCheckers (Car)LW261993-05-20No170 Lbs5 ft9NoNoNo2Avec RestrictionPro & Farm500,000$0$0$NoLien
Logan PyettCheckers (Car)D311988-05-26No199 Lbs5 ft10NoNoNo1Sans RestrictionPro & Farm300,000$0$0$NoLien
Lucas JohansenCheckers (Car)D211997-11-16No182 Lbs6 ft2NoNoNo3Contrat d'EntréePro & Farm500,000$0$0$NoLien
Nic HagueCheckers (Car)D201998-12-05No215 Lbs6 ft6NoNoNo4Contrat d'EntréePro & Farm900,000$0$0$NoLien
Skyler McKenzieCheckers (Car)LW211998-01-20Yes154 Lbs5 ft8NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$NoLien
Stefan ElliottCheckers (Car)D281991-01-30Yes190 Lbs6 ft1NoNoNo1Sans RestrictionPro & Farm300,000$0$0$NoLien
Tyler SteenbergenCheckers (Car)C211998-01-07Yes188 Lbs5 ft1NoNoNo4Contrat d'EntréePro & Farm500,000$0$0$NoLien
Tyler VeselCheckers (Car)C251994-04-14Yes182 Lbs5 ft1NoNoNo4Avec RestrictionPro & Farm300,000$0$0$NoLien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2324.09186 Lbs5 ft112.74441,304$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
140122
230122
320122
410122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
140122
230122
320122
410122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
160122
240122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
160122
240122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
160122
240122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
160122
240122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
16012260122
24012240122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
160122
240122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
160122
240122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
, , ,
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
, , ,
Tirs de Pénalité
, , , ,
Gardien
#1 : , #2 :


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
1Americans2020000029-7000000000002020000029-700.000246006350331611501450101241435500.00%6350.00%011254520.55%16296216.84%8140020.25%309192103519727595
2Bears20200000313-1020200000313-100000000000000.000369006350421611501450111271240300.00%6183.33%011254520.55%16296216.84%8140020.25%309192103519727595
3Bruins40400000025-2520200000013-1320200000012-1200.0000000063505216115014501916042651000.00%20575.00%011254520.55%16296216.84%8140020.25%309192103519727595
4Comets20200000016-160000000000020200000016-1600.00000000635027161150145094151423800.00%7271.43%011254520.55%16296216.84%8140020.25%309192103519727595
5Crunch20200000012-120000000000020200000012-1200.000000006350281611501450112382030400.00%10370.00%011254520.55%16296216.84%8140020.25%309192103519727595
6Devils2020000019-8000000000002020000019-800.00012300635033161150145084272927700.00%5260.00%011254520.55%16296216.84%8140020.25%309192103519727595
7Penguins20200000312-90000000000020200000312-900.00036900635041161150145079171235800.00%6266.67%011254520.55%16296216.84%8140020.25%309192103519727595
8Phantoms20200000013-130000000000020200000013-1300.00000000635028161150145083212129700.00%8275.00%011254520.55%16296216.84%8140020.25%309192103519727595
9Rocket20200000113-1220200000113-120000000000000.000123006350471611501450852522318112.50%11190.91%011254520.55%16296216.84%8140020.25%309192103519727595
10Senators20200000211-920200000211-90000000000000.00023500635036161150145095292534500.00%8275.00%011254520.55%16296216.84%8140020.25%309192103519727595
11Sound Tigers1010000008-8000000000001010000008-800.0000000063501116115014503914815200.00%4250.00%011254520.55%16296216.84%8140020.25%309192103519727595
12Thunderbirds1010000003-3000000000001010000003-300.0000000063501716115014504314814300.00%40100.00%011254520.55%16296216.84%8140020.25%309192103519727595
Total270270000014168-15490900000658-5218018000008110-10200.000142741006350456161150145012673542584298111.23%1082874.07%011254520.55%16296216.84%8140020.25%309192103519727595
14Wolf Pack30300000224-221010000008-820200000216-1400.0002460063506116115014501504331511100.00%13376.92%011254520.55%16296216.84%8140020.25%309192103519727595
_Since Last GM Reset270270000014168-15490900000658-5218018000008110-10200.000142741006350456161150145012673542584298111.23%1082874.07%011254520.55%16296216.84%8140020.25%309192103519727595
_Vs Conference70700000341-3820200000113-1250500000228-2600.000369006350124161150145032378581032414.17%28678.57%011254520.55%16296216.84%8140020.25%309192103519727595

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
270L27142741456126735425842900
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
27027000014168
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
9090000658
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
1801800008110
Derniers 10 Matchs
WLOTWOTL SOWSOL
0100000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
8111.23%1082874.07%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
16115014506350
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
11254520.55%16296216.84%8140020.25%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
309192103519727595


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
3 - 2019-09-043Checkers0Americans6LSommaire du Match
4 - 2019-09-0515Checkers2Americans3LSommaire du Match
10 - 2019-09-1133Checkers0Comets8LSommaire du Match
11 - 2019-09-1246Checkers0Crunch3LSommaire du Match
17 - 2019-09-1870Bears7Checkers0LSommaire du Match
18 - 2019-09-1984Bears6Checkers3LSommaire du Match
22 - 2019-09-23104Checkers0Comets8LSommaire du Match
24 - 2019-09-25110Checkers1Devils5LSommaire du Match
25 - 2019-09-26119Checkers0Crunch9LSommaire du Match
31 - 2019-10-02139Bruins9Checkers0LSommaire du Match
32 - 2019-10-03154Bruins4Checkers0LSommaire du Match
38 - 2019-10-09186Checkers0Devils4LSommaire du Match
39 - 2019-10-10198Checkers0Phantoms7LSommaire du Match
40 - 2019-10-11205Checkers0Sound Tigers8LSommaire du Match
43 - 2019-10-14219Checkers0Phantoms6LSommaire du Match
45 - 2019-10-16228Checkers2Penguins5LSommaire du Match
46 - 2019-10-17243Checkers1Penguins7LSommaire du Match
49 - 2019-10-20253Senators5Checkers1LSommaire du Match
50 - 2019-10-21258Senators6Checkers1LSommaire du Match
53 - 2019-10-24278Rocket5Checkers0LSommaire du Match
54 - 2019-10-25290Rocket8Checkers1LSommaire du Match
59 - 2019-10-30311Checkers0Bruins8LSommaire du Match
60 - 2019-10-31321Checkers2Wolf Pack7LSommaire du Match
61 - 2019-11-01332Checkers0Bruins4LSommaire du Match
66 - 2019-11-06355Checkers0Wolf Pack9LSommaire du Match
67 - 2019-11-07368Checkers0Thunderbirds3LSommaire du Match
72 - 2019-11-12390Wolf Pack8Checkers0LSommaire du Match
74 - 2019-11-14402Wolf Pack-Checkers-
75 - 2019-11-15415Comets-Checkers-
77 - 2019-11-17423Comets-Checkers-
80 - 2019-11-20435Sound Tigers-Checkers-
81 - 2019-11-21454Sound Tigers-Checkers-
87 - 2019-11-27482Checkers-Rocket-
88 - 2019-11-28486Checkers-Rocket-
90 - 2019-11-30504Checkers-Marlies-
94 - 2019-12-04519Checkers-Senators-
95 - 2019-12-05534Checkers-Senators-
96 - 2019-12-06548Checkers-Marlies-
101 - 2019-12-11561Penguins-Checkers-
102 - 2019-12-12575Penguins-Checkers-
105 - 2019-12-15594Sound Tigers-Checkers-
106 - 2019-12-16595Sound Tigers-Checkers-
109 - 2019-12-19618Marlies-Checkers-
110 - 2019-12-20631Marlies-Checkers-
115 - 2019-12-25658Checkers-Bruins-
116 - 2019-12-26670Checkers-Wolf Pack-
122 - 2020-01-01684Bruins-Checkers-
123 - 2020-01-02699Bruins-Checkers-
126 - 2020-01-05713Monsters-Checkers-
127 - 2020-01-06716Monsters-Checkers-
130 - 2020-01-09737Checkers-Bears-
131 - 2020-01-10755Checkers-Bears-
136 - 2020-01-15772Checkers-Thunderbirds-
137 - 2020-01-16786Checkers-Bruins-
138 - 2020-01-17794Checkers-Sound Tigers-
143 - 2020-01-22816Phantoms-Checkers-
144 - 2020-01-23829Phantoms-Checkers-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
150 - 2020-01-29858Devils-Checkers-
151 - 2020-01-30869Devils-Checkers-
157 - 2020-02-05902Checkers-Phantoms-
158 - 2020-02-06913Checkers-Phantoms-
164 - 2020-02-12946Americans-Checkers-
165 - 2020-02-13955Americans-Checkers-
168 - 2020-02-16973Crunch-Checkers-
169 - 2020-02-17978Crunch-Checkers-
172 - 2020-02-20995Wolf Pack-Checkers-
173 - 2020-02-211008Wolf Pack-Checkers-
176 - 2020-02-241018Checkers-Sound Tigers-
178 - 2020-02-261033Checkers-Wolf Pack-
179 - 2020-02-271039Checkers-Sound Tigers-
182 - 2020-03-011059Phantoms-Checkers-
183 - 2020-03-021063Phantoms-Checkers-
186 - 2020-03-051086Thunderbirds-Checkers-
187 - 2020-03-061097Thunderbirds-Checkers-
191 - 2020-03-101114Checkers-Monsters-
192 - 2020-03-111115Checkers-Monsters-



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité de l'Aréna20001000
Prix des Billets3515
Assistance00
Assistance PCT0.00%0.00%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
29 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
411,032$ 101,500$ 22,970$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 39,927$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 122 5,678$ 692,716$




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
14270270000014168-15490900000658-5218018000008110-1020142741006350456161150145012673542584298111.23%1082874.07%011254520.55%16296216.84%8140020.25%309192103519727595
Total Saison Régulière270270000014168-15490900000658-5218018000008110-1020142741006350456161150145012673542584298111.23%1082874.07%011254520.55%16296216.84%8140020.25%309192103519727595