As

GP: 18 | W: 10 | L: 6 | T: 2 | P: 22
GF: 63 | GA: 61 | PP%: 22.22% | PK%: 79.38%
DG: Christian Nolet | Morale : 54 | Moyenne d'Équipe : 65
Prochain matchs #128 vs Pacifiques de la route
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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
1Alan KerrX98.007660626673798073697568726758634155680
2Brian NoonanX99.007560656871797868637170766644504638670
3Rob DiMaioX99.007051726972687275647370766447526759670
4Kelly ChaseX100.009089256374707269617064785857596159660
5Vladimir RuzickaX100.006246776378686874687879577448443159660
6Ken BaumgartnerX100.008982406077686668596660755556615457640
7Mark PedersonX100.005541787074687170667068676541416759640
8Neil BradyX100.007161546276676775656859765659576739640
9Dave BrownX100.008570556377727254525950804977742359630
10Jim McKenzieX100.007874376480727266606658765534347459620
11Troy MalletteX100.008987266680697060586660715834518155620
12Marty McSorleyX99.008882365980717261606855845263633160680
13Bryan MarchmentX99.009079486775747466586858845241397660670
14Darryl ShannonX100.006952716577787763586565796250576759670
15Robert DirkX100.007768576579737460556052785051555559650
16Bobby DollasX100.007154715978666761607259795652424759640
17Enrico Ciccone (R)X100.008277366181646657546142744029298157610
Rayé
1Stephan LebeauX94.366959647269716975697976687043436948670
2Rob Gaudreau (R)X100.004333857172596066617271596634288257610
3Brad MayX100.008578426676626458545860765834348947600
MOYENNE D'ÉQUIPE99.42766555657670716661686274594849605565
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
1Dominic Roussel99.00737271747272798077737244478258690
2Trevor Kidd (R)100.00677475767169778076696828289659660
Rayé
1Mike Fountain (R)100.00696672737052657062676434389632610
MOYENNE D'ÉQUIPE99.6770717374716474777270683538915065
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Brian Sutter72717067798480CAN38295,000$


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
1Kelly ChaseAs (MIN)RW18515206260602844102611.36%129216.252571061000011047.62%2100001.3700000023
2Mark PedersonAs (MIN)LW1889172003284093120.00%130416.942571274000002061.90%2100001.1200000101
3Rob DiMaioAs (MIN)C186111754095257164010.53%236520.2925713730113522149.24%39400010.9300000110
4Bryan MarchmentAs (MIN)D1861016-3235462630111020.00%2042023.374372075101172100.00%000010.7600001023
5Stephan LebeauAs (MIN)C188816-340134761183613.11%141222.9236913740001683048.71%42700100.7800000301
6Darryl ShannonAs (MIN)D1841014660121723121517.39%2241423.033141374000274100.00%000000.6800000220
7Alan KerrAs (MIN)RW14581318062549162710.20%033023.5942622630003570152.00%20000000.7900000021
8Robert DirkAs (MIN)D181111252202722205135.00%1438921.610441075000065000.00%000000.6200000010
9Marty McSorleyAs (MIN)D183811-329555162291213.64%2942223.452131374000066000.00%000000.5200001101
10Vladimir RuzickaAs (MIN)C1864102002313272818.75%027615.36000020110470052.50%24000000.7200000200
11Ken BaumgartnerAs (MIN)LW182793421057102611177.69%230016.670559750000100057.69%2600000.6000011001
12Brian NoonanAs (MIN)RW8145-16025917175.88%015719.710113320001200063.16%1900000.6300000000
13Dave BrownAs (MIN)LW18224-328041171931010.53%425314.06000100000330124.24%3300000.3200000000
14Enrico CicconeAs (MIN)D18134-44810441453320.00%1826114.5300006000023000.00%000000.3100002001
15Rob GaudreauAs (MIN)RW17213-600012235208.70%220412.0100013000000046.15%1300000.2900000000
16Bobby DollasAs (MIN)D18022-1206203670.00%1226814.9001118000013000.00%000000.1500000000
17Jim McKenzieAs (MIN)LW18112-36014413297.69%0653.6400002000030062.50%800000.6100000000
18Neil BradyAs (MIN)C8202-40021182625.00%0597.39000010001150056.47%8500000.6800000000
19Brad MayAs (MIN)LW10000000121000.00%090.98000140000100100.00%100000.0000000000
20Troy MalletteAs (MIN)LW15000-220832110.00%1473.1400006000000059.26%2700000.0000000000
Stats d'équipe Total ou en Moyenne32463114177-32563043139449514731812.73%129525416.222239611427911231262710350.56%151500120.6700015101012
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
1Dominic RousselAs (MIN)1810620.8873.25108800595230020.0000180000
Stats d'équipe Total ou en Moyenne1810620.8873.25108800595230020.0000180000


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 Cap 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
Alan KerrAs (MIN)RW291991-02-09 9:08:37 PMNo195 Lbs5 ft11NoNoNo1Pro & Farm580,000$58,000$45,632$No
Bobby DollasAs (MIN)D281992-02-09 9:08:37 PMNo220 Lbs6 ft2NoNoNo3Pro & Farm425,000$42,500$33,438$No425,000$425,000$
Brad MayAs (MIN)LW221998-02-09 9:08:37 PMNo209 Lbs6 ft0NoNoNo3Pro & Farm275,000$27,500$21,636$No275,000$275,000$
Brian NoonanAs (MIN)RW281992-02-09 9:08:37 PMNo180 Lbs6 ft1NoNoNo1Pro & Farm400,000$40,000$31,471$No
Bryan MarchmentAs (MIN)D241996-02-09 9:08:37 PMNo208 Lbs6 ft1NoNoNo3Pro & Farm706,000$70,600$55,546$No706,000$706,000$
Darryl ShannonAs (MIN)D251995-02-09 9:08:37 PMNo208 Lbs6 ft2NoNoNo1Pro & Farm695,000$69,500$54,680$No
Dave BrownAs (MIN)LW311989-02-09 9:08:37 PMNo205 Lbs6 ft5NoNoNo1Pro & Farm100,000$10,000$7,868$No
Dominic RousselAs (MIN)G231997-02-09 9:08:37 PMNo180 Lbs6 ft1NoNoNo1Pro & Farm250,000$25,000$19,669$No
Enrico CicconeAs (MIN)D231997-02-09 9:08:37 PMYes220 Lbs6 ft5NoNoNo1Pro & Farm260,000$26,000$20,456$No
Jim McKenzieAs (MIN)LW241996-02-09 9:08:37 PMNo221 Lbs6 ft4NoNoNo1Pro & Farm400,000$40,000$31,471$No
Kelly ChaseAs (MIN)RW261994-02-09 9:08:37 PMNo200 Lbs6 ft0NoNoNo3Pro & Farm532,000$53,200$41,856$No532,000$532,000$
Ken BaumgartnerAs (MIN)LW271993-02-09 9:08:37 PMNo215 Lbs6 ft1NoNoNo1Pro & Farm400,000$40,000$31,471$No
Mark PedersonAs (MIN)LW251995-02-09 9:08:37 PMNo196 Lbs6 ft2NoNoNo2Pro & Farm365,000$36,500$28,717$No365,000$
Marty McSorleyAs (MIN)D301990-02-09 9:08:37 PMNo225 Lbs6 ft1NoNoNo2Pro & Farm945,000$94,500$74,349$No945,000$
Mike FountainAs (MIN)G211999-02-09 9:08:37 PMYes176 Lbs6 ft1NoNoNo3Pro & Farm450,000$45,000$35,404$No450,000$450,000$
Neil BradyAs (MIN)C251995-02-09 9:08:37 PMNo205 Lbs6 ft3NoNoNo2Pro & Farm400,000$40,000$31,471$No400,000$
Rob DiMaioAs (MIN)C251995-02-09 9:08:37 PMNo190 Lbs5 ft10NoNoNo3Pro & Farm609,000$60,900$47,914$No609,000$609,000$
Rob GaudreauAs (MIN)RW231997-02-09 9:08:37 PMYes185 Lbs5 ft11NoNoNo1Pro & Farm425,000$42,500$33,438$No
Robert DirkAs (MIN)D271993-02-09 9:08:37 PMNo207 Lbs6 ft4NoNoNo2Pro & Farm425,000$42,500$33,438$No425,000$
Stephan Lebeau (Sur la Masse Salariale)As (MIN)C251995-02-09 9:08:37 PMNo172 Lbs5 ft10NoNoNo1Pro & Farm486,000$48,600$38,237$No
Trevor KiddAs (MIN)G211999-02-09 9:08:37 PMYes190 Lbs6 ft2NoNoNo1Pro & Farm350,000$35,000$27,537$No
Troy MalletteAs (MIN)LW231997-02-09 9:08:37 PMNo219 Lbs6 ft3NoNoNo3Pro & Farm402,000$40,200$31,628$No402,000$402,000$
Vladimir RuzickaAs (MIN)C301990-02-09 9:08:37 PMNo212 Lbs6 ft3NoNoNo1Pro & Farm650,000$65,000$51,140$No
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2325.43202 Lbs6 ft21.78457,826$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Ken BaumgartnerRob DiMaioAlan Kerr35122
2Mark PedersonBrian Noonan30122
3Dave BrownVladimir RuzickaKelly Chase20122
4Jim McKenzieNeil BradyAlan Kerr15122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Marty McSorleyBryan Marchment35122
2Darryl ShannonRobert Dirk30122
3Bobby DollasEnrico Ciccone20122
4Marty McSorleyBryan Marchment15122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Ken BaumgartnerRob DiMaioAlan Kerr60122
2Mark PedersonBrian Noonan40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Marty McSorleyBryan Marchment60122
2Darryl ShannonRobert Dirk40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Alan KerrBrian Noonan60122
2Rob DiMaio40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Marty McSorleyBryan Marchment60122
2Darryl ShannonRobert Dirk40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Alan Kerr60122Marty McSorleyBryan Marchment60122
2Brian Noonan40122Darryl ShannonRobert Dirk40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Alan KerrBrian Noonan60122
2Rob DiMaio40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Marty McSorleyBryan Marchment60122
2Darryl ShannonRobert Dirk40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Ken BaumgartnerRob DiMaioAlan KerrMarty McSorleyBryan Marchment
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Ken BaumgartnerRob DiMaioAlan KerrMarty McSorleyBryan Marchment
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Troy Mallette, Kelly Chase, Vladimir RuzickaTroy Mallette, Kelly ChaseVladimir Ruzicka
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Bobby Dollas, Enrico Ciccone, Darryl ShannonBobby DollasEnrico Ciccone, Darryl Shannon
Tirs de Pénalité
Alan Kerr, Brian Noonan, Rob DiMaio, , Kelly Chase
Gardien
#1 : Dominic Roussel, #2 : Trevor Kidd


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
1Ailes Rouges31101000111012010100067-11100000053240.6671118290022202017915516716679927767515640.00%21385.71%029659250.00%32263450.79%14828951.21%433291423140233116
2Banshees11000000431000000000001100000043121.000481200222020123155167166735818194125.00%8275.00%129659250.00%32263450.79%14828951.21%433291423140233116
3Canadiens21010000871000000000002101000087130.750814220022202017215516716675412313714428.57%12283.33%029659250.00%32263450.79%14828951.21%433291423140233116
4Chiefs11000000431110000004310000000000021.000481200222020131155167166724610238112.50%3166.67%029659250.00%32263450.79%14828951.21%433291423140233116
5Croque-Morts413000001415-1211000009722020000058-320.2501426401022202011011551671667116353810323417.39%17570.59%029659250.00%32263450.79%14828951.21%433291423140233116
6Harvard11000000541000000000001100000054121.0005101500222020138155167166735516286350.00%7357.14%029659250.00%32263450.79%14828951.21%433291423140233116
7Pacifiques de la route21010000541110000003211001000022030.7505914002220201551551671667611216478112.50%8275.00%029659250.00%32263450.79%14828951.21%433291423140233116
8Snipers1010000038-51010000038-50000000000000.0003690022202012415516716674271836100.00%8187.50%029659250.00%32263450.79%14828951.21%433291423140233116
Total18962100063612944010003133-29522000032284220.611631141772022202014951551671667525129256431992222.22%972079.38%129659250.00%32263450.79%14828951.21%433291423140233116
10Wolves32100000972211000006601100000031240.667915241022202017215516716675917336320210.00%13192.31%029659250.00%32263450.79%14828951.21%433291423140233116
_Since Last GM Reset181160100063612944010003133-29720000032284240.667631141772022202014951551671667525129256431992222.22%972079.38%129659250.00%32263450.79%14828951.21%433291423140233116
_Vs Conference1366010004244-2834010002730-35320000015141140.5384274116202220201331155167166737798181324671319.40%671282.09%029659250.00%32263450.79%14828951.21%433291423140233116
_Vs Division1045010003432262301000212014220000013121100.500345993202220201252155167166727479147241581220.69%51982.35%029659250.00%32263450.79%14828951.21%433291423140233116

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
1822W16311417749552512925643120
Tous les Matchs
GPWLOTWOTL TGFGA
18961026361
Matchs locaux
GPWLOTWOTL TGFGA
9441003133
Matchs Éxtérieurs
GPWLOTWOTL TGFGA
9520023228
Derniers 10 Matchs
WLOTWOTL T
63001
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
992222.22%972079.38%1
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
15516716672220201
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
29659250.00%32263450.79%14828951.21%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
433291423140233116


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 - 2020-09-213As3Croque-Morts5LSommaire du Match
2 - 2020-09-2212Croque-Morts2As6WSommaire du Match
4 - 2020-09-2419As4Canadiens4TXSommaire du Match
5 - 2020-09-2523Ailes Rouges4As5WXSommaire du Match
6 - 2020-09-2630As3Wolves1WSommaire du Match
8 - 2020-09-2838Wolves4As2LSommaire du Match
9 - 2020-09-2945As2Croque-Morts3LSommaire du Match
10 - 2020-09-3052As4Banshees3WSommaire du Match
11 - 2020-10-0155Croque-Morts5As3LSommaire du Match
14 - 2020-10-0466Ailes Rouges3As1LSommaire du Match
15 - 2020-10-0571As4Canadiens3WSommaire du Match
17 - 2020-10-0777Pacifiques de la route2As3WSommaire du Match
19 - 2020-10-0983As5Harvard4WSommaire du Match
21 - 2020-10-1191As2Pacifiques de la route2TXSommaire du Match
23 - 2020-10-1398Wolves2As4WSommaire du Match
25 - 2020-10-15106As5Ailes Rouges3WSommaire du Match
27 - 2020-10-17110Snipers8As3LSommaire du Match
29 - 2020-10-19121Chiefs3As4WSommaire du Match
31 - 2020-10-21128As-Pacifiques de la route-
33 - 2020-10-23133As-Banshees-
35 - 2020-10-25138As-Canadiens-
37 - 2020-10-27145Chiefs-As-
39 - 2020-10-29153Wolves-As-
41 - 2020-10-31162As-Croque-Morts-
42 - 2020-11-01166Riverman-As-
44 - 2020-11-03177Ailes Rouges-As-
46 - 2020-11-05184As-Chiefs-
47 - 2020-11-06191As-Banshees-
49 - 2020-11-08196Snipers-As-
50 - 2020-11-09205Snipers-As-
52 - 2020-11-11212As-Wolves-
53 - 2020-11-12218Banshees-As-
55 - 2020-11-14221As-Isotopes-
57 - 2020-11-16233Harvard-As-
58 - 2020-11-17241As-Citadelles-
60 - 2020-11-19247Pacifiques de la route-As-
61 - 2020-11-20253As-Wolves-
62 - 2020-11-21255As-Citadelles-
64 - 2020-11-23264Citadelles-As-
65 - 2020-11-24271As-Riverman-
67 - 2020-11-26277Citadelles-As-
68 - 2020-11-27288As-Snipers-
70 - 2020-11-29293Canadiens-As-
72 - 2020-12-01303As-Harvard-
73 - 2020-12-02306Harvard-As-
74 - 2020-12-03317Ailes Rouges-As-
75 - 2020-12-04321As-Spoonman's-
77 - 2020-12-06327As-Riverman-
78 - 2020-12-07335Croque-Morts-As-
79 - 2020-12-08340As-Croque-Morts-
80 - 2020-12-09348Citadelles-As-
82 - 2020-12-11353As-Spoonman's-
84 - 2020-12-13363Ailes Rouges-As-
86 - 2020-12-15371As-Isotopes-
88 - 2020-12-17376Banshees-As-
90 - 2020-12-19386As-Pacifiques de la route-
92 - 2020-12-21390Croque-Morts-As-
94 - 2020-12-23400Isotopes-As-
96 - 2020-12-25404As-Harvard-
98 - 2020-12-27414As-Ailes Rouges-
100 - 2020-12-29418Wolves-As-
101 - 2020-12-30424As-Riverman-
103 - 2021-01-01432Spoonman's-As-
105 - 2021-01-03442Isotopes-As-
106 - 2021-01-04445As-Snipers-
108 - 2021-01-06450As-Spoonman's-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
110 - 2021-01-08459Pacifiques de la route-As-
112 - 2021-01-10465As-Canadiens-
113 - 2021-01-11473Croque-Morts-As-
115 - 2021-01-13479As-Croque-Morts-
116 - 2021-01-14486As-Chiefs-
117 - 2021-01-15491Chiefs-As-
118 - 2021-01-16500Isotopes-As-
120 - 2021-01-18509As-Wolves-
121 - 2021-01-19515Pacifiques de la route-As-
123 - 2021-01-21528Harvard-As-
124 - 2021-01-22531As-Ailes Rouges-
126 - 2021-01-24541Canadiens-As-
127 - 2021-01-25543As-Ailes Rouges-
130 - 2021-01-28556Riverman-As-
133 - 2021-01-31565As-Citadelles-
134 - 2021-02-01569Spoonman's-As-



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
32 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
238,966$ 1,004,400$ 944,400$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
1,004,400$ 238,966$ 22 1

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 107 8,084$ 864,988$




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
199318962100063612944010003133-2952200003228422631141772022202014951551671667525129256431992222.22%972079.38%129659250.00%32263450.79%14828951.21%433291423140233116
Total Saison Régulière18962100063612944010003133-2952200003228422631141772022202014951551671667525129256431992222.22%972079.38%129659250.00%32263450.79%14828951.21%433291423140233116