Chiken Wings

GP: 8 | W: 3 | L: 4 | OTL: 1 | P: 7
GF: 31 | GA: 35 | PP%: 26.67% | PK%: 85.37%
DG: Christian Roy | Morale : 48 | Moyenne d'Équipe : 64
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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
1Mark JankowskiXX99.00614291758063836468707373256565054690301700,000$
2Michael AmadioXX100.00694392737565876955647166256768049680283750,000$
3Samuel BlaisX100.009959838277548262316055637565670526602831,500,000$
4Jesper FastX100.007644927671639463386458727576800416603222,400,000$
5Zemgus GirgensonsXX100.008756897478618963546064702577770556603032,500,000$
6Ty DellandreaX100.00805784766763796461635778256061055660244900,000$
7Joel KivirantaXX100.00794392796255856233605779256365050650283775,000$
8Steven FogartyXX100.00797978657978836075546266594646050630313762,500$
9Brendan LemieuxXX100.008799477380505962345659587566670536302811,550,000$
10Justin KirklandX100.00767383637360606250625765544646051620282775,000$
11Carson MeyerX100.009145956466537465255758672546460486102721,420,000$
12Brad MaloneXX100.00717951657963665569564566436566053580353762,500$
13Juuso ValimakiX100.007544937578779069255648752563630546902511,550,000$
14Kevin BahlX100.008359727284728163255047852560610496802421,050,000$
15Justin BarronX100.00784489777576886925505874255656053680223925,000$
16Mason Lohrei (R)X100.00714386767470676525565073254747050660233925,000$
17Logan StanleyX100.008399617387634863254348802559600506502641,000,000$
18Yan Kuznetsov (R)X100.00807886677872794625354163394444057570223870,000$
Rayé
1Stefan NoesenX100.00805587747661977443737061256667051700312762,500$
2Connor CarrickX100.00716974656976825625484666446565051610301775,000$
MOYENNE D'ÉQUIPE99.9579618172756579634157567038606105165
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
1Eric Comrie100.0059505065655269606559785050042590
Rayé
1Karel Vejmelka100.0063747281656069646563755959053660
2Collin Delia100.0046496180434550524647304444049490
MOYENNE D'ÉQUIPE100.005658617558526359595661515104858
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Brent Thompson60606060606060CAN442500,000$


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
1Joel KivirantaChiken Wings (DET)LW/RW8178-1003202210154.55%313016.34033319000120010.00%1000001.2200000010
2Justin BarronChiken Wings (DET)D8538-340204201825.00%717221.52224815000021110.00%000000.9300000100
3Michael AmadioChiken Wings (DET)LW/RW8347-28022133052510.00%114217.8611210200000141053.33%3000000.9811000100
4Kevin BahlChiken Wings (DET)D852701203214122641.67%1615118.94101215000017000.00%000000.9200000011
5Zemgus GirgensonsChiken Wings (DET)C/LW8426-18014191561526.67%114718.392244180000130045.09%17300000.8200000011
6Jesper FastChiken Wings (DET)RW6415020161211033.33%48013.3501103000080020.00%500001.2500000100
7Juuso ValimakiChiken Wings (DET)D6145-440711341033.33%714524.29123215000020000.00%000000.6900000000
8Mark JankowskiChiken Wings (DET)C/LW6055-500316215210.00%712320.650332130000190054.78%11500000.8101000000
9Steven FogartyChiken Wings (DET)C/RW6055-100187370.00%07913.1900000000010057.61%9200001.2600000000
10Mason LohreiChiken Wings (DET)D6134-22061072214.29%713121.88000315000017000.00%000000.6100000000
11Ty DellandreaChiken Wings (DET)RW61340408814187.14%08614.43011212000000050.00%600000.9200000000
12Logan StanleyChiken Wings (DET)D8033-28024414430.00%712015.120000100016000.00%000000.5000000010
13Stefan NoesenChiken Wings (DET)RW4123-220147143107.14%19423.56000170000100038.64%4400000.6411000001
14Samuel BlaisChiken Wings (DET)RW6202-26069163012.50%0528.7200000000010014.29%700000.7600000000
15Connor CarrickChiken Wings (DET)D4022200412020.00%35012.550000000001000.00%000000.8000000001
16Brad MaloneChiken Wings (DET)C/LW8011-1007411070.00%1577.2200000000000059.46%3700000.3500000000
17Brendan LemieuxChiken Wings (DET)LW/RW8011022029610480.00%110813.5600034000000016.67%1200000.1800000000
18Justin KirklandChiken Wings (DET)RW8000-100515120.00%0192.4900013000000090.00%1000000.0000000000
19Yan KuznetsovChiken Wings (DET)D5000-320410040.00%36613.320000100006000.00%000000.0000000000
20Carson MeyerChiken Wings (DET)RW8000000011000.00%050.7300002000000033.33%300000.0000000000
Stats d'équipe Total ou en Moyenne135284876-288402101632365516311.86%69196714.57715224117000021652149.08%54400000.7723000344
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
1Karel VejmelkaChiken Wings (DET)32100.9044.2418400131360001.000231010
2Eric ComrieChiken Wings (DET)30110.8714.391640012930000.000034000
Stats d'équipe Total ou en Moyenne62210.8914.3034900252290001.000265010


Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
Nom du Joueur Nom de l'ÉquipePOS Âge Date de Naissance Nouveau Joueur Poids Taille Non-Échange Disponible pour Échange Ballotage Forcé Contrat Type Salaire Actuel Salaire RestantCap Salariale Cap Salariale Restant Exclus du Cap Salarial Salaire Année 2Salaire Année 3Salaire Année 4Salaire Année 5Salaire Année 6Salaire Année 7Salaire Année 8Salaire Année 9Salaire Année 10Link
Brad MaloneChiken Wings (DET)C/LW351989-05-19No217 Lbs6 ft2NoNoNo3Pro & Farm762,500$762,500$0$0$No762,500$762,500$Lien / Lien NHL
Brendan LemieuxChiken Wings (DET)LW/RW281996-03-15No213 Lbs6 ft1NoNoNo1Pro & Farm1,550,000$1,550,000$0$0$NoLien / Lien NHL
Carson MeyerChiken Wings (DET)RW271997-08-18No180 Lbs5 ft11NoNoNo2Pro & Farm1,420,000$1,420,000$0$0$No1,420,000$Lien
Collin DeliaChiken Wings (DET)G301994-06-19No208 Lbs6 ft2NoNoNo2Pro & Farm750,000$750,000$0$0$No750,000$Lien / Lien NHL
Connor CarrickChiken Wings (DET)D301994-04-13No192 Lbs5 ft11NoNoNo1Pro & Farm775,000$775,000$0$0$NoLien
Eric ComrieChiken Wings (DET)G291995-07-05No174 Lbs6 ft1NoNoNo3Pro & Farm1,800,000$1,800,000$0$0$No1,800,000$1,800,000$Lien / Lien NHL
Jesper FastChiken Wings (DET)RW321991-12-02No191 Lbs6 ft1NoNoNo2Pro & Farm2,400,000$2,400,000$0$0$No2,400,000$Lien / Lien NHL
Joel KivirantaChiken Wings (DET)LW/RW281996-03-23No174 Lbs5 ft10NoNoNo3Pro & Farm775,000$775,000$0$0$No775,000$775,000$Lien / Lien NHL
Justin BarronChiken Wings (DET)D222001-11-15No202 Lbs6 ft2NoNoNo3Pro & Farm925,000$925,000$0$0$No925,000$925,000$Lien
Justin KirklandChiken Wings (DET)RW281996-08-02No194 Lbs6 ft3NoNoNo2Pro & Farm775,000$775,000$0$0$No775,000$Lien
Juuso ValimakiChiken Wings (DET)D251998-10-06No211 Lbs6 ft2NoNoNo1Pro & Farm1,550,000$1,550,000$0$0$NoLien
Karel VejmelkaChiken Wings (DET)G281996-05-25No202 Lbs6 ft3NoNoNo1Pro & Farm842,500$842,500$0$0$NoLien
Kevin BahlChiken Wings (DET)D242000-06-27No216 Lbs6 ft6NoNoNo2Pro & Farm1,050,000$1,050,000$0$0$No1,050,000$Lien
Logan StanleyChiken Wings (DET)D261998-05-25No216 Lbs6 ft6NoNoNo4Pro & Farm1,000,000$1,000,000$0$0$No1,000,000$1,000,000$1,000,000$Lien / Lien NHL
Mark JankowskiChiken Wings (DET)C/LW301994-09-13No211 Lbs6 ft4NoNoNo1Pro & Farm700,000$700,000$0$0$NoLien / Lien NHL
Mason LohreiChiken Wings (DET)D232001-01-17Yes194 Lbs6 ft4NoNoNo3Pro & Farm925,000$925,000$0$0$No925,000$925,000$Lien
Michael AmadioChiken Wings (DET)LW/RW281996-05-13No205 Lbs6 ft1NoNoNo3Pro & Farm750,000$750,000$0$0$No750,000$750,000$Lien / Lien NHL
Samuel BlaisChiken Wings (DET)RW281996-06-17No205 Lbs6 ft2NoNoNo3Pro & Farm1,500,000$1,500,000$0$0$No1,500,000$1,500,000$Lien
Stefan NoesenChiken Wings (DET)RW311993-02-12No205 Lbs6 ft1NoNoNo2Pro & Farm762,500$762,500$0$0$No762,500$Lien / Lien NHL
Steven FogartyChiken Wings (DET)C/RW311993-04-19No210 Lbs6 ft3NoNoNo3Pro & Farm762,500$762,500$0$0$No762,500$762,500$Lien / Lien NHL
Ty DellandreaChiken Wings (DET)RW242000-07-20No183 Lbs6 ft0NoNoNo4Pro & Farm900,000$900,000$0$0$No900,000$900,000$900,000$Lien
Yan KuznetsovChiken Wings (DET)D222002-03-09Yes209 Lbs6 ft4NoNoNo3Pro & Farm870,000$870,000$0$0$No870,000$870,000$Lien
Zemgus GirgensonsChiken Wings (DET)C/LW301994-01-05No211 Lbs6 ft2NoNoNo3Pro & Farm2,500,000$2,500,000$0$0$No2,500,000$2,500,000$Lien / Lien NHL
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2327.78201 Lbs6 ft22.391,132,391$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Michael AmadioMark Jankowski35122
2Joel KivirantaZemgus GirgensonsTy Dellandrea35122
3Brendan LemieuxSteven FogartyJesper Fast25122
4Brad MaloneSamuel Blais5122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Juuso ValimakiJustin Barron35122
2Kevin BahlMason Lohrei35122
3Logan StanleyYan Kuznetsov25122
4Juuso ValimakiJustin Barron5122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Michael AmadioMark Jankowski60122
2Joel KivirantaZemgus GirgensonsTy Dellandrea40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Juuso ValimakiJustin Barron60122
2Kevin BahlMason Lohrei40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Mark Jankowski60122
2Michael AmadioZemgus Girgensons40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Juuso ValimakiJustin Barron60122
2Kevin BahlMason Lohrei40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
160122Juuso ValimakiJustin Barron60122
2Mark Jankowski40122Kevin BahlMason Lohrei40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Mark Jankowski60122
2Michael AmadioZemgus Girgensons40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Juuso ValimakiJustin Barron60122
2Kevin BahlMason Lohrei40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Michael AmadioMark JankowskiJuuso ValimakiJustin Barron
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Michael AmadioMark JankowskiJuuso ValimakiJustin Barron
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Justin Kirkland, Carson Meyer, Jesper FastJustin Kirkland, Carson MeyerJesper Fast
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Logan Stanley, Yan Kuznetsov, Kevin BahlLogan StanleyYan Kuznetsov, Kevin Bahl
Tirs de Pénalité
, Mark Jankowski, Michael Amadio, Zemgus Girgensons, Ty Dellandrea
Gardien
#1 : , #2 : Eric Comrie


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
1Crunch211000001091110000005321010000056-120.50010182800911102897597805941814743133.33%70100.00%012425748.25%14930948.22%6413846.38%1901291915810552
2Phantom211000006601010000034-11100000032120.50061117009111025475978056919265113430.77%10370.00%012425748.25%14930948.22%6413846.38%1901291915810552
3Rockets201000101013-31010000048-41000001065120.50010142400911102467597805932726544125.00%11190.91%012425748.25%14930948.22%6413846.38%1901291915810552
4Sword 2010010057-21010000023-11000010034-110.25051015009111026575978057226306510220.00%13284.62%012425748.25%14930948.22%6413846.38%1901291915810552
Total824001103135-4413000001418-4411001101717070.438315384009111022547597805328909624430826.67%41685.37%012425748.25%14930948.22%6413846.38%1901291915810552
_Since Last GM Reset824001103135-4413000001418-4411001101717070.438315384009111022547597805328909624430826.67%41685.37%012425748.25%14930948.22%6413846.38%1901291915810552
_Vs Conference824001103135-4413000001418-4411001101717070.438315384009111022547597805328909624430826.67%41685.37%012425748.25%14930948.22%6413846.38%1901291915810552
_Vs Division4240011016151213000008712110011088070.875162945009111021437597805163374012516531.25%17382.35%012425748.25%14930948.22%6413846.38%1901291915810552

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
87L3315384254328909624400
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
82401103135
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
41300001418
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
41101101717
Derniers 10 Matchs
WLOTWOTL SOWSOL
340100
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
30826.67%41685.37%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
7597805911102
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
12425748.25%14930948.22%6413846.38%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
1901291915810552


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 - 2024-09-172Sword 3Chiken Wings2LSommaire du Match
3 - 2024-09-1917Crunch3Chiken Wings5WSommaire du Match
5 - 2024-09-2126Chiken Wings6Rockets5WXXSommaire du Match
6 - 2024-09-2232Chiken Wings3Sword 4LXSommaire du Match
7 - 2024-09-2338Chiken Wings3Phantom2WSommaire du Match
8 - 2024-09-2444Chiken Wings5Crunch6LSommaire du Match
11 - 2024-09-2759Rockets8Chiken Wings4LSommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
14 - 2024-09-3075Phantom4Chiken Wings3LSommaire du Match



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité de l'Aréna20001000
Prix des Billets4020
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
0 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
0$ 2,604,500$ 2,774,833$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 0$ 0 0

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




LigueDomicileVisiteur
Année GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff P G A TP SO EG GP1 GP2 GP3 GP4 SHF SH1 SP2 SP3 SP4 SHA SHB Pim Hit PPA PPG PP% PKA PK GA PK% PK GF W OF FO T OF FO OF FO% W DF FO T DF FO DF FO% W NT FO T NT FO NT FO% PZ DF PZ OF PZ NT PC DF PC OF PC NT