As
GP: 82 | W: 37 | L: 36 | T: 8 | P: 83
GF: 251 | GA: 269 | PP%: 17.98% | PK%: 80.68%
DG: Christian Nolet | Morale : 51 | Moyenne d'Équipe : 65
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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 KerrX99.007660626673798073697568726758634159680301580,000$
2Brian NoonanX100.007560656871797868637170766644504646670291400,000$
3Stephan LebeauX100.006959647269716975697976687043436950670261486,000$
4Kelly ChaseX100.009089256374707269617064785857596176660273532,000$
5Vladimir RuzickaX100.006246776378686874687879577448443142660311650,000$
6Ken BaumgartnerX100.008982406077686668596660755556615460640281400,000$
7Mark PedersonX100.005541787074687170667068676541416772640262365,000$
8Neil BradyX100.007161546276676775656859765659576742640262400,000$
9Dave BrownX100.008570556377727254525950804977742372630321100,000$
10Jim McKenzieX100.007874376480727266606658765534347472620251400,000$
11Troy MalletteX100.008987266680697060586660715834518168620243402,000$
12Rob Gaudreau (R)X100.004333857172596066617271596634288237610241425,000$
13Marty McSorleyX100.008882365980717261606855845263633177680312945,000$
14Bryan MarchmentX100.009079486775747466586858845241397635670253706,000$
15Randy LadouceurX100.00797250597774735554635179508287853670341100,000$
16Robert DirkX100.007768576579737460556052785051555572660282425,000$
17Bobby DollasX100.007154715978666761607259795652424746640293425,000$
18Brad BerryX100.006346746277727255526146764457594746630291375,000$
Rayé
1Rob DiMaioX98.477051726972687275647370766447526762670263609,000$
2Brad MayX100.008578426676626458545860765834348920600233275,000$
3Darryl ShannonX100.006952716577787763586565796250576760670261695,000$
4Enrico Ciccone (R)X100.008277366181646657546142744029298151610241260,000$
MOYENNE D'ÉQUIPE99.89756556657670716560686175585051575565
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 Roussel100.00737271747272798077737244478225690
2Trevor Kidd (R)100.00677475767169778076696828289662660
Rayé
1Mike Fountain (R)100.00696672737052657062676434389620610
MOYENNE D'ÉQUIPE100.0070717374716474777270683538913665
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)C822946750260671752557117411.37%13170620.8110203053312123113617147.58%173800100.8800000742
2Mark PedersonAs (MIN)LW82283563134017861614314617.39%3123715.095162144328000005047.19%8900001.0200000444
3Rob DiMaioAs (MIN)C762042621122061179225591508.89%14151219.90620264628811282704151.72%168800010.8200000721
4Alan KerrAs (MIN)RW66253560127351561602125913511.79%13163524.799101965268213113581255.27%104400000.7300001456
5Kelly ChaseAs (MIN)RW82203353014810215109203521339.85%8120914.753912241360000114046.34%8200000.8800101064
6Darryl ShannonAs (MIN)D7812385018180389212344919.76%103186023.859716783070223402300.00%000000.5400000242
7Marty McSorleyAs (MIN)D821236487183153018612430749.68%113192423.465813693270114344110.00%000100.5000102423
8Robert DirkAs (MIN)D828303861000131649431548.51%84174621.306814532850112332000.00%000000.4400000112
9Brian NoonanAs (MIN)RW6823143703601081111732811813.29%11145221.3593124025310193043145.40%32600000.5100000321
10Bryan MarchmentAs (MIN)D65102737-7130101578987255711.49%70147022.6261016552401011289200.00%000010.5000101034
11Ken BaumgartnerAs (MIN)LW82111728-61502024770139511017.91%5135716.5631114373100001491156.60%10600000.4100031012
12Vladimir RuzickaAs (MIN)C68121325400711212426809.68%0105315.4902243001131750051.87%98900000.4700000200
13Dave BrownAs (MIN)LW82101424-3720947896317710.42%19110313.46101240000731138.94%11300000.4300000011
14Neil BradyAs (MIN)C72121123-280159171134916.90%35747.98011160001562051.18%63300000.8000000002
15Bobby DollasAs (MIN)D67416203180296718152622.22%4998414.70011124000166110.00%000000.4100000020
16Enrico CicconeAs (MIN)D7231417-415010222501991515.79%66106614.820000180000139000.00%000000.3200002031
17Randy LadouceurAs (MIN)D2711213-33354821323223.12%3561222.69123201160001122100.00%000000.4200100110
18Rob GaudreauAs (MIN)RW534610-4000305212447.69%24929.3000017000000153.57%2800000.4100000000
19Jim McKenzieAs (MIN)LW8244813606625486258.33%13233.9400018000040043.90%4100000.4900000010
20Troy MalletteAs (MIN)LW79268-420046141761111.76%22252.85022231000001052.27%8800000.7100000000
21Brad BerryAs (MIN)D19167200477111014.29%1426013.710111500009000.00%000000.5400000001
22Brad MayAs (MIN)LW10000000121000.00%090.98000140000100100.00%100000.0000000000
Stats d'équipe Total ou en Moyenne147625145570644122775203017182281625159211.00%6282382116.147313120459833176915563374371050.62%696600220.5900438354236
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)78353470.8843.2344432223920530330.0000766222
2Trevor KiddAs (MIN)142310.8953.1152120272560000.0000676000
Stats d'équipe Total ou en Moyenne92373780.8853.2249644226623090330.00008282222


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)RW301991-02-09 9:08:37 PMNo195 Lbs5 ft11NoNoNo1Pro & Farm580,000$58,000$426$No
Bobby DollasAs (MIN)D291992-02-09 9:08:37 PMNo220 Lbs6 ft2NoNoNo3Pro & Farm425,000$42,500$312$No425,000$425,000$
Brad BerryAs (MIN)D291992-02-09 9:08:37 PMNo205 Lbs6 ft3NoNoNo1Pro & Farm375,000$37,500$276$No
Brad MayAs (MIN)LW231998-02-09 9:08:37 PMNo209 Lbs6 ft0NoNoNo3Pro & Farm275,000$27,500$202$No275,000$275,000$
Brian NoonanAs (MIN)RW291992-02-09 9:08:37 PMNo180 Lbs6 ft1NoNoNo1Pro & Farm400,000$40,000$294$No
Bryan MarchmentAs (MIN)D251996-02-09 9:08:37 PMNo208 Lbs6 ft1NoNoNo3Pro & Farm706,000$70,600$519$No706,000$706,000$
Darryl ShannonAs (MIN)D261995-02-09 9:08:37 PMNo208 Lbs6 ft2NoNoNo1Pro & Farm695,000$69,500$511$No
Dave BrownAs (MIN)LW321989-02-09 9:08:37 PMNo205 Lbs6 ft5NoNoNo1Pro & Farm100,000$10,000$74$No
Dominic RousselAs (MIN)G241997-02-09 9:08:37 PMNo180 Lbs6 ft1NoNoNo1Pro & Farm250,000$25,000$184$No
Enrico CicconeAs (MIN)D241997-02-09 9:08:37 PMYes220 Lbs6 ft5NoNoNo1Pro & Farm260,000$26,000$191$No
Jim McKenzieAs (MIN)LW251996-02-09 9:08:37 PMNo221 Lbs6 ft4NoNoNo1Pro & Farm400,000$40,000$294$No
Kelly ChaseAs (MIN)RW271994-02-09 9:08:37 PMNo200 Lbs6 ft0NoNoNo3Pro & Farm532,000$53,200$391$No532,000$532,000$
Ken BaumgartnerAs (MIN)LW281993-02-09 9:08:37 PMNo215 Lbs6 ft1NoNoNo1Pro & Farm400,000$40,000$294$No
Mark PedersonAs (MIN)LW261995-02-09 9:08:37 PMNo196 Lbs6 ft2NoNoNo2Pro & Farm365,000$36,500$268$No365,000$
Marty McSorleyAs (MIN)D311990-02-09 9:08:37 PMNo225 Lbs6 ft1NoNoNo2Pro & Farm945,000$94,500$695$No945,000$
Mike FountainAs (MIN)G221999-02-09 9:08:37 PMYes176 Lbs6 ft1NoNoNo3Pro & Farm450,000$45,000$331$No450,000$450,000$
Neil BradyAs (MIN)C261995-02-09 9:08:37 PMNo205 Lbs6 ft3NoNoNo2Pro & Farm400,000$40,000$294$No400,000$
Randy LadouceurAs (MIN)D341987-02-09 9:08:37 PMNo221 Lbs6 ft2NoNoNo1Pro & Farm100,000$10,000$74$No
Rob DiMaioAs (MIN)C261995-02-09 9:08:37 PMNo190 Lbs5 ft10NoNoNo3Pro & Farm609,000$60,900$448$No609,000$609,000$
Rob GaudreauAs (MIN)RW241997-02-09 9:08:37 PMYes185 Lbs5 ft11NoNoNo1Pro & Farm425,000$42,500$312$No
Robert DirkAs (MIN)D281993-02-09 9:08:37 PMNo207 Lbs6 ft4NoNoNo2Pro & Farm425,000$42,500$312$No425,000$
Stephan LebeauAs (MIN)C261995-02-09 9:08:37 PMNo172 Lbs5 ft10NoNoNo1Pro & Farm486,000$48,600$357$No
Trevor KiddAs (MIN)G221999-02-09 9:08:37 PMYes190 Lbs6 ft2NoNoNo1Pro & Farm350,000$35,000$257$No
Troy MalletteAs (MIN)LW241997-02-09 9:08:37 PMNo219 Lbs6 ft3NoNoNo3Pro & Farm402,000$40,200$296$No402,000$402,000$
Vladimir RuzickaAs (MIN)C311990-02-09 9:08:37 PMNo212 Lbs6 ft3NoNoNo1Pro & Farm650,000$65,000$478$No
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2526.84203 Lbs6 ft21.72440,200$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Mark PedersonStephan LebeauAlan Kerr35122
2Ken BaumgartnerVladimir RuzickaBrian Noonan30122
3Dave BrownNeil BradyKelly Chase20122
4Jim McKenzieAlan KerrRob Gaudreau15122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Marty McSorleyRandy Ladouceur35122
2Bryan MarchmentRobert Dirk30122
3Bobby DollasBrad Berry20122
4Marty McSorleyRandy Ladouceur15122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Mark PedersonStephan LebeauAlan Kerr60122
2Ken BaumgartnerVladimir RuzickaBrian Noonan40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Marty McSorleyRandy Ladouceur60122
2Bryan MarchmentRobert Dirk40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Alan KerrStephan Lebeau60122
2Brian NoonanVladimir Ruzicka40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Marty McSorleyRandy Ladouceur60122
2Bryan MarchmentRobert Dirk40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Alan Kerr60122Marty McSorleyRandy Ladouceur60122
2Stephan Lebeau40122Bryan MarchmentRobert Dirk40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Alan KerrStephan Lebeau60122
2Brian NoonanVladimir Ruzicka40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Marty McSorleyRandy Ladouceur60122
2Bryan MarchmentRobert Dirk40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Mark PedersonStephan LebeauAlan KerrMarty McSorleyRandy Ladouceur
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Mark PedersonStephan LebeauAlan KerrMarty McSorleyRandy Ladouceur
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Troy Mallette, Kelly Chase, Neil BradyTroy Mallette, Kelly ChaseNeil Brady
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Bobby Dollas, Brad Berry, Bryan MarchmentBobby DollasBrad Berry, Bryan Marchment
Tirs de Pénalité
Alan Kerr, Stephan Lebeau, Brian Noonan, Vladimir Ruzicka, 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 Rouges942210002724352111000151414211000012102120.6672748750088877242547307497752724369154222531120.75%59788.14%11386278249.82%1473287051.32%667131450.76%1947128519576541069524
2Banshees532000001418-42110000079-23210000079-260.60014274101888772411173074977527130308112918211.11%31874.19%11386278249.82%1473287051.32%667131450.76%1947128519576541069524
3Canadiens614100001824-62020000036-3412100001518-330.250183250008887724203730749775271623587135301033.33%38976.32%01386278249.82%1473287051.32%667131450.76%1947128519576541069524
4Chiefs513100001420-6311100001011-12020000049-530.30014264000888772412473074977527133487611430310.00%351168.57%01386278249.82%1473287051.32%667131450.76%1947128519576541069524
5Citadelles6321000021183311100001110132100000108270.583213859108887724153730749775271915410013924520.83%50492.00%01386278249.82%1473287051.32%667131450.76%1947128519576541069524
6Croque-Morts1037000003339-65230000022193514000001120-960.3003359921088877242777307497752730590116267571322.81%551180.00%11386278249.82%1473287051.32%667131450.76%1947128519576541069524
7Harvard64200000181623120000039-633000000157880.66718325000888772417973074977527152358914434617.65%37781.08%01386278249.82%1473287051.32%667131450.76%1947128519576541069524
8Isotopes530110002010103101100097222000000113890.90020385800888772416473074977527144426811824520.83%29293.10%21386278249.82%1473287051.32%667131450.76%1947128519576541069524
9Pacifiques de la route742100002118342200000121203201000096390.643213859008887724178730749775271964213017825520.00%45784.44%01386278249.82%1473287051.32%667131450.76%1947128519576541069524
10Riverman50410000918-920200000510-53021000048-410.100917260088877241387307497752715830651192328.70%29872.41%01386278249.82%1473287051.32%667131450.76%1947128519576541069524
11Snipers503020001622-6302010001015-52010100067-140.40016294500888772413173074977527156408013918211.11%381073.68%01386278249.82%1473287051.32%667131450.76%1947128519576541069524
12Spoonman's513001001019-92010010048-431200000611-530.3001018280188877241367307497752714654861102129.52%37975.68%01386278249.82%1473287051.32%667131450.76%1947128519576541069524
13Wolves862000003023743100000181264310000012111120.75030538310888772423373074977527196599921649714.29%45980.00%11386278249.82%1473287051.32%667131450.76%1947128519576541069524
Total82333684100251269-1841141943100129142-1341191741000122127-5830.5062514557063288877242281730749775272312628123120304067317.98%52810280.68%61386278249.82%1473287051.32%667131450.76%1947128519576541069524
_Since Last GM Reset82413604100251269-1841141943100129142-13412717-41000122127-5910.5552514557063288877242281730749775272312628123120304067317.98%52810280.68%61386278249.82%1473287051.32%667131450.76%1947128519576541069524
_Vs Conference44212003000136144-823911120008282021129-110005462-8480.545136244380208887724121173074977527125433064411412254017.78%2715280.81%31386278249.82%1473287051.32%667131450.76%1947128519576541069524
_Vs Division27151101000908641475110005545101386-100003541-6320.59390160250208887724764730749775277442183697051593119.50%1592783.02%31386278249.82%1473287051.32%667131450.76%1947128519576541069524

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
8283OTL1251455706228123126281231203032
Tous les Matchs
GPWLOTWOTL TGFGA
823336418251269
Matchs locaux
GPWLOTWOTL TGFGA
411419314129142
Matchs Éxtérieurs
GPWLOTWOTL TGFGA
411917104122127
Derniers 10 Matchs
WLOTWOTL T
35011
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
4067317.98%52810280.68%6
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
730749775278887724
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
1386278249.82%1473287051.32%667131450.76%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
1947128519576541069524


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 - 2020-12-19386As4Pacifiques de la route2WSommaire du Match
92 - 2020-12-21390Croque-Morts5As4LSommaire du Match
94 - 2020-12-23400Isotopes2As3WSommaire du Match
96 - 2020-12-25404As7Harvard2WSommaire du Match
98 - 2020-12-27414As2Ailes Rouges2TXSommaire du Match
100 - 2020-12-29418Wolves2As7WSommaire du Match
101 - 2020-12-30424As0Riverman2LSommaire du Match
103 - 2021-01-01432Spoonman's4As1LSommaire du Match
105 - 2021-01-03442Isotopes2As3WXSommaire du Match
106 - 2021-01-04445As3Snipers5LSommaire du Match
108 - 2021-01-06450As4Spoonman's0WSommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
110 - 2021-01-08459Pacifiques de la route6As2LSommaire du Match
112 - 2021-01-10465As3Canadiens5LSommaire du Match
113 - 2021-01-11473Croque-Morts5As3LSommaire du Match
115 - 2021-01-13479As3Croque-Morts2WSommaire du Match
116 - 2021-01-14486As3Chiefs4LSommaire du Match
117 - 2021-01-15491Chiefs4As4TXSommaire du Match
118 - 2021-01-16500Isotopes3As3TXSommaire du Match
120 - 2021-01-18509As4Wolves1WSommaire du Match
121 - 2021-01-19515Pacifiques de la route3As1LSommaire du Match
123 - 2021-01-21528Harvard4As1LSommaire du Match
124 - 2021-01-22531As4Ailes Rouges3WSommaire du Match
126 - 2021-01-24541Canadiens3As2LSommaire du Match
127 - 2021-01-25543As1Ailes Rouges2LSommaire du Match
130 - 2021-01-28556Riverman4As3LSommaire du Match
133 - 2021-01-31565As4Citadelles1WSommaire du Match
134 - 2021-02-01569Spoonman's4As3LXSommaire du Match



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

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

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
1,134,525$ 1,100,500$ 1,040,500$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
1,100,500$ 1,134,525$ 25 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 1 8,790$ 8,790$




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