As

GP: 55 | W: 27 | L: 23 | T: 5 | P: 59
GF: 169 | GA: 187 | PP%: 18.08% | PK%: 80.90%
DG: Christian Nolet | Morale : 55 | Moyenne d'Équipe : 65
Prochain matchs #386 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 SPÂgeContratSalaire
1Alan KerrX98.007660626673798073697568726758634159680291580,000$
2Brian NoonanX99.007560656871797868637170766644504644670281400,000$
3Stephan LebeauX100.006959647269716975697976687043436947670251486,000$
4Rob DiMaioX100.007051726972687275647370766447526769670253609,000$
5Kelly ChaseX100.009089256374707269617064785857596170660263532,000$
6Vladimir RuzickaX100.006246776378686874687879577448443139660301650,000$
7Ken BaumgartnerX100.008982406077686668596660755556615467640271400,000$
8Mark PedersonX100.005541787074687170667068676541416769640252365,000$
9Neil BradyX100.007161546276676775656859765659576749640252400,000$
10Dave BrownX100.008570556377727254525950804977742369630311100,000$
11Jim McKenzieX100.007874376480727266606658765534347469620241400,000$
12Troy MalletteX100.008987266680697060586660715834518165620233402,000$
13Marty McSorleyX100.008882365980717261606855845263633174680302945,000$
14Darryl ShannonX100.006952716577787763586565796250576769670251695,000$
15Robert DirkX100.007768576579737460556052785051555569660272425,000$
16Bobby DollasX100.007154715978666761607259795652424769640283425,000$
17Enrico Ciccone (R)X100.008277366181646657546142744029298157610231260,000$
Rayé
1Rob Gaudreau (R)X100.004333857172596066617271596634288255610231425,000$
2Brad MayX100.008578426676626458545860765834348920600223275,000$
3Bryan MarchmentXS49079486775747466586858845241397653670243706,000$
MOYENNE D'ÉQUIPE99.85766555657670716661686274594849605965
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 Roussel100.00737271747272798077737244478233690
2Trevor Kidd (R)100.00677475767169778076696828289664660
Rayé
1Mike Fountain (R)100.00696672737052657062676434389620610
MOYENNE D'ÉQUIPE100.0070717374716474777270683538913965
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
1Stephan LebeauAs (MIN)C552526510140461091654010915.15%8116521.20812203020112362577146.67%117000100.8700000641
2Kelly ChaseAs (MIN)RW55142842083513975132348110.61%583815.25381122114000063045.16%6200001.0000001054
3Alan KerrAs (MIN)RW4316254173758497135398511.85%8106124.6857124416111272331154.76%72500000.7700001235
4Mark PedersonAs (MIN)LW551922411120759102279118.63%282615.02391225203000004051.61%6200000.9900000323
5Rob DiMaioAs (MIN)C55122941514043140171471157.02%8110320.06412163319611251972150.09%116800010.7400000321
6Darryl ShannonAs (MIN)D55728351416031637931618.86%65130823.794610492040222282200.00%000000.5300000231
7Bryan MarchmentAs (MIN)D5592231-7116101367473234912.33%65124822.716814471991011247200.00%000010.5000101024
8Marty McSorleyAs (MIN)D5592130-1127151995976164511.84%80128023.28347382050003227110.00%000100.4700102312
9Robert DirkAs (MIN)D55621277680904559203710.17%50119521.745510341960111237000.00%000000.4500000110
10Brian NoonanAs (MIN)RW4113922-22607468100185713.00%686621.146172314010151691147.49%25900000.5100000220
11Ken BaumgartnerAs (MIN)LW5531619-810210164368531633.53%591716.6801111242000000311054.93%7100000.4100011002
12Vladimir RuzickaAs (MIN)C41991830056470135312.86%061515.010000201111080050.85%52700000.5800000200
13Bobby DollasAs (MIN)D5541115-3100165917132123.53%4380214.58011120000145110.00%000000.3700000020
14Neil BradyAs (MIN)C458715-5808584483218.18%13838.53011040001471051.43%42000000.7800000001
15Dave BrownAs (MIN)LW555914-360075535220349.62%1373913.44000120000580138.75%8000000.3800000000
16Enrico CicconeAs (MIN)D5531013-412410170361461021.43%4881214.780000130000101000.00%000000.3200002031
17Rob GaudreauAs (MIN)RW434610-4000284810358.33%24139.6100017000000154.17%2400000.4800000000
18Troy MalletteAs (MIN)LW52246-21003111115518.18%21643.17011015000001049.12%5700000.7300000000
19Jim McKenzieAs (MIN)LW55134-31603815265143.85%01953.5600018000040048.48%3300000.4100000000
20Brad MayAs (MIN)LW10000000121000.00%090.98000140000100100.00%100000.0000000000
Stats d'équipe Total ou en Moyenne99016930647558335513571151146040699711.58%4111594916.1147861333742102581333225927849.86%465900220.6000218243025
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)54262250.8823.3230522116914280130.0000532121
2Trevor KiddAs (MIN)81100.9053.3027300151580000.0000253000
Stats d'équipe Total ou en Moyenne62272350.8843.3233252118415860130.00005555121


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$20,471$No
Bobby DollasAs (MIN)D281992-02-09 9:08:37 PMNo220 Lbs6 ft2NoNoNo3Pro & Farm425,000$42,500$15,000$No425,000$425,000$
Brad MayAs (MIN)LW221998-02-09 9:08:37 PMNo209 Lbs6 ft0NoNoNo3Pro & Farm275,000$27,500$9,706$No275,000$275,000$
Brian NoonanAs (MIN)RW281992-02-09 9:08:37 PMNo180 Lbs6 ft1NoNoNo1Pro & Farm400,000$40,000$14,118$No
Bryan MarchmentAs (MIN)D241996-02-09 9:08:37 PMNo208 Lbs6 ft1NoNoNo3Pro & Farm706,000$70,600$24,918$No706,000$706,000$
Darryl ShannonAs (MIN)D251995-02-09 9:08:37 PMNo208 Lbs6 ft2NoNoNo1Pro & Farm695,000$69,500$24,529$No
Dave BrownAs (MIN)LW311989-02-09 9:08:37 PMNo205 Lbs6 ft5NoNoNo1Pro & Farm100,000$10,000$3,529$No
Dominic RousselAs (MIN)G231997-02-09 9:08:37 PMNo180 Lbs6 ft1NoNoNo1Pro & Farm250,000$25,000$8,824$No
Enrico CicconeAs (MIN)D231997-02-09 9:08:37 PMYes220 Lbs6 ft5NoNoNo1Pro & Farm260,000$26,000$9,176$No
Jim McKenzieAs (MIN)LW241996-02-09 9:08:37 PMNo221 Lbs6 ft4NoNoNo1Pro & Farm400,000$40,000$14,118$No
Kelly ChaseAs (MIN)RW261994-02-09 9:08:37 PMNo200 Lbs6 ft0NoNoNo3Pro & Farm532,000$53,200$18,776$No532,000$532,000$
Ken BaumgartnerAs (MIN)LW271993-02-09 9:08:37 PMNo215 Lbs6 ft1NoNoNo1Pro & Farm400,000$40,000$14,118$No
Mark PedersonAs (MIN)LW251995-02-09 9:08:37 PMNo196 Lbs6 ft2NoNoNo2Pro & Farm365,000$36,500$12,882$No365,000$
Marty McSorleyAs (MIN)D301990-02-09 9:08:37 PMNo225 Lbs6 ft1NoNoNo2Pro & Farm945,000$94,500$33,353$No945,000$
Mike FountainAs (MIN)G211999-02-09 9:08:37 PMYes176 Lbs6 ft1NoNoNo3Pro & Farm450,000$45,000$15,882$No450,000$450,000$
Neil BradyAs (MIN)C251995-02-09 9:08:37 PMNo205 Lbs6 ft3NoNoNo2Pro & Farm400,000$40,000$14,118$No400,000$
Rob DiMaioAs (MIN)C251995-02-09 9:08:37 PMNo190 Lbs5 ft10NoNoNo3Pro & Farm609,000$60,900$21,494$No609,000$609,000$
Rob GaudreauAs (MIN)RW231997-02-09 9:08:37 PMYes185 Lbs5 ft11NoNoNo1Pro & Farm425,000$42,500$15,000$No
Robert DirkAs (MIN)D271993-02-09 9:08:37 PMNo207 Lbs6 ft4NoNoNo2Pro & Farm425,000$42,500$15,000$No425,000$
Stephan LebeauAs (MIN)C251995-02-09 9:08:37 PMNo172 Lbs5 ft10NoNoNo1Pro & Farm486,000$48,600$17,153$No
Trevor KiddAs (MIN)G211999-02-09 9:08:37 PMYes190 Lbs6 ft2NoNoNo1Pro & Farm350,000$35,000$12,353$No
Troy MalletteAs (MIN)LW231997-02-09 9:08:37 PMNo219 Lbs6 ft3NoNoNo3Pro & Farm402,000$40,200$14,188$No402,000$402,000$
Vladimir RuzickaAs (MIN)C301990-02-09 9:08:37 PMNo212 Lbs6 ft3NoNoNo1Pro & Farm650,000$65,000$22,941$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 BaumgartnerStephan LebeauAlan Kerr35122
2Mark PedersonRob DiMaioBrian Noonan30122
3Dave BrownVladimir RuzickaKelly Chase20122
4Jim McKenzieNeil BradyAlan Kerr15122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Marty McSorley35122
2Darryl ShannonRobert Dirk30122
3Bobby DollasEnrico Ciccone20122
4Marty McSorley15122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Ken BaumgartnerStephan LebeauAlan Kerr60122
2Mark PedersonRob DiMaioBrian Noonan40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Marty McSorley60122
2Darryl ShannonRobert Dirk40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Alan KerrBrian Noonan60122
2Stephan LebeauRob DiMaio40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Marty McSorley60122
2Darryl ShannonRobert Dirk40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Alan Kerr60122Marty McSorley60122
2Brian Noonan40122Darryl ShannonRobert Dirk40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Alan KerrBrian Noonan60122
2Stephan LebeauRob DiMaio40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Marty McSorley60122
2Darryl ShannonRobert Dirk40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Ken BaumgartnerStephan LebeauAlan KerrMarty McSorley
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Ken BaumgartnerStephan LebeauAlan KerrMarty McSorley
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, Stephan Lebeau, 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 Rouges631110002017352111000151411100000053290.750203555005559523169457487496201714510614633927.27%35585.71%0882181148.70%992195750.69%44989150.39%12888471323438719350
2Banshees532000001418-42110000079-23210000079-260.60014274101555952311145748749620130308112918211.11%31874.19%1882181148.70%992195750.69%44989150.39%12888471323438719350
3Canadiens412100001316-31010000013-2311100001213-130.3751322350055595231404574874962011026638322731.82%27581.48%0882181148.70%992195750.69%44989150.39%12888471323438719350
4Chiefs31200000712-52110000067-11010000015-420.3337142100555952366457487496207520426518211.11%18666.67%0882181148.70%992195750.69%44989150.39%12888471323438719350
5Citadelles522100001717031110000111012110000067-150.50017304710555952312145748749620162428811319421.05%44490.91%0882181148.70%992195750.69%44989150.39%12888471323438719350
6Croque-Morts725000002327-432100000159640400000818-1040.28623436610555952318845748749620214608220138821.05%39879.49%1882181148.70%992195750.69%44989150.39%12888471323438719350
7Harvard43100000101002110000025-32200000085360.7501019290055595231054574874962010125639120420.00%26580.77%0882181148.70%992195750.69%44989150.39%12888471323438719350
8Isotopes2200000011380000000000022000000113841.0001122330055595236945748749620581334499222.22%17194.12%2882181148.70%992195750.69%44989150.39%12888471323438719350
9Pacifiques de la route430100001477220000009362101000054170.8751425390055595231014574874962012126528813215.38%23386.96%0882181148.70%992195750.69%44989150.39%12888471323438719350
10Riverman30210000612-61010000026-42011000046-210.16761117005559523854574874962010314496914214.29%21576.19%0882181148.70%992195750.69%44989150.39%12888471323438719350
11Snipers402020001317-4302010001015-51000100032140.5001323360055595239845748749620118266211614214.29%29775.86%0882181148.70%992195750.69%44989150.39%12888471323438719350
12Spoonman's20200000211-90000000000020200000211-900.0002460055595235545748749620693336509111.11%12466.67%0882181148.70%992195750.69%44989150.39%12888471323438719350
Total55242353000169187-18271211220008991-2281212310008096-16590.536169306475315559523146045748749620158941183513572604718.08%3566880.90%5882181148.70%992195750.69%44989150.39%12888471323438719350
13Wolves642000001920-1321000001110132100000810-280.6671931501055595231524574874962015751771573326.06%34779.41%1882181148.70%992195750.69%44989150.39%12888471323438719350
_Since Last GM Reset55292303000169187-18271211220008991-2281712-210008096-16640.582169306475315559523146045748749620158941183513572604718.08%3566880.90%5882181148.70%992195750.69%44989150.39%12888471323438719350
_Vs Conference3015120300095100-5178612000625751376-110003343-10360.60095168263205559523793457487496208842224287771452517.24%1813580.66%2882181148.70%992195750.69%44989150.39%12888471323438719350
_Vs Division19108010006264-211631100041338845-100002131-10220.57962109171205559523509457487496205421562655041041918.27%1082081.48%2882181148.70%992195750.69%44989150.39%12888471323438719350

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
5559L116930647514601589411835135731
Tous les Matchs
GPWLOTWOTL TGFGA
552423305169187
Matchs locaux
GPWLOTWOTL TGFGA
2712112028991
Matchs Éxtérieurs
GPWLOTWOTL TGFGA
2812121038096
Derniers 10 Matchs
WLOTWOTL T
44002
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
2604718.08%3566880.90%5
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
457487496205559523
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
882181148.70%992195750.69%44989150.39%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
12888471323438719350


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 - 2020-10-21128As3Pacifiques de la route2WSommaire du Match
33 - 2020-10-23133As2Banshees6LSommaire du Match
35 - 2020-10-25138As4Canadiens6LSommaire du Match
37 - 2020-10-27145Chiefs4As2LSommaire du Match
39 - 2020-10-29153Wolves4As5WSommaire du Match
41 - 2020-10-31162As1Croque-Morts2LSommaire du Match
42 - 2020-11-01166Riverman6As2LSommaire du Match
44 - 2020-11-03177Ailes Rouges1As2WSommaire du Match
46 - 2020-11-05184As1Chiefs5LSommaire du Match
47 - 2020-11-06191As1Banshees0WSommaire du Match
49 - 2020-11-08196Snipers4As5WXSommaire du Match
50 - 2020-11-09205Snipers3As2LSommaire du Match
52 - 2020-11-11212As4Wolves3WSommaire du Match
53 - 2020-11-12218Banshees2As4WSommaire du Match
55 - 2020-11-14221As6Isotopes1WSommaire du Match
57 - 2020-11-16233Harvard1As2WSommaire du Match
58 - 2020-11-17241As3Citadelles5LSommaire du Match
60 - 2020-11-19247Pacifiques de la route1As6WSommaire du Match
61 - 2020-11-20253As1Wolves6LSommaire du Match
62 - 2020-11-21255As3Citadelles2WSommaire du Match
64 - 2020-11-23264Citadelles3As3TXSommaire du Match
65 - 2020-11-24271As2Riverman4LSommaire du Match
67 - 2020-11-26277Citadelles4As3LSommaire du Match
68 - 2020-11-27288As3Snipers2WXSommaire du Match
70 - 2020-11-29293Canadiens3As1LSommaire du Match
72 - 2020-12-01303As3Harvard1WSommaire du Match
73 - 2020-12-02306Harvard4As0LSommaire du Match
74 - 2020-12-03317Ailes Rouges5As5TXSommaire du Match
75 - 2020-12-04321As1Spoonman's5LSommaire du Match
77 - 2020-12-06327As2Riverman2TXSommaire du Match
78 - 2020-12-07335Croque-Morts2As6WSommaire du Match
79 - 2020-12-08340As2Croque-Morts8LSommaire du Match
80 - 2020-12-09348Citadelles3As5WSommaire du Match
82 - 2020-12-11353As1Spoonman's6LSommaire du Match
84 - 2020-12-13363Ailes Rouges1As2WSommaire du Match
86 - 2020-12-15371As5Isotopes2WSommaire du Match
88 - 2020-12-17376Banshees7As3LSommaire du Match
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
14 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
733,581$ 982,400$ 922,400$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
982,400$ 733,581$ 23 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 48 7,922$ 380,256$




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