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Connexion

Manchots
GP: 82 | W: 43 | L: 32 | OTL: 7 | P: 93
GF: 254 | GA: 244 | PP%: 19.29% | PK%: 82.53%
DG: Raphael Belanger | Morale : 50 | Moyenne d’équipe : 56
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Centre de jeu
Baby Hawks
50-23-9, 109pts
1
FINAL
3 Manchots
43-32-7, 93pts
Team Stats
W1StreakL1
27-9-5Home Record23-14-4
23-14-4Away Record20-18-3
7-3-0Last 10 Games6-4-0
3.61Buts par match 3.10
2.88Buts contre par match 2.98
22.11%Pourcentage en avantage numérique19.29%
86.05%Pourcentage en désavantage numérique82.53%
Manchots
43-32-7, 93pts
2
FINAL
7 Monsters
49-24-9, 107pts
Team Stats
L1StreakW1
23-14-4Home Record24-13-4
20-18-3Away Record25-11-5
6-4-0Last 10 Games4-2-4
3.10Buts par match 3.50
2.98Buts contre par match 3.15
19.29%Pourcentage en avantage numérique19.75%
82.53%Pourcentage en désavantage numérique80.38%
Meneurs d'équipe
Buts
C.J. Suess
33
Passes
Shane Pinto
40
Points
Shane Pinto
67
Plus/Moins
Shane Pinto
12
Victoires
Nico Daws
33
Pourcentage d’arrêts
Daniel Vladar
0.923

Statistiques d’équipe
Buts pour
254
3.10 GFG
Tirs pour
2788
34.00 Avg
Pourcentage en avantage numérique
19.3%
49 GF
Début de zone offensive
41.4%
Buts contre
244
2.98 GAA
Tirs contre
2743
33.45 Avg
Pourcentage en désavantage numérique
82.5%%
40 GA
Début de la zone défensive
38.5%
Informations de l'équipe

Directeur généralRaphael Belanger
DivisionEst
ConférenceEst
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance1,883
Billets de saison300


Informations de la formation

Équipe Pro23
Équipe Mineure20
Limite contact 43 / 50
Espoirs11


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 moyen
1Shane PintoX100.00694376777258466172745478244545050610202925,000$
2Mackenzie MacEachernXX100.00794490717250675925625571255858050600272560,000$
3Paul CareyX100.00747487797458595849575365524748050590332875,000$
4C.J. SuessX100.00756989666965666150566164584444050590272700,000$
5Simon Holmstrom (R)XX100.00817595637563646150615767544444050590202894,167$
6Vitaly Abramov (R)XX100.00686586676558586049585762564444050570232600,000$
7Ivan ChekhovichX100.00767495606758535854585166474444050560222776,667$
8Joel KellmanX100.00716977776946455468564761454646050550272800,000$
9Mikhail VorobyevX100.00534188697248674983535065244747050550241650,000$
10Tyler SteenbergenXXX100.00706693676663675369415861584444050550231650,000$
11Blade Jenkins (R)XX100.00787193637153545265465363504444050540213600,000$
12Pavel Gogolev (R)X100.00777289617247475050474762454444050520214834,167$
13Joel HanleyX100.007944967269586557254848752560600506303021,020,000$
14Ian MitchellX100.00614099766358805625504773254848050610222925,000$
15Dan RenoufX100.00777876627866714825374165395656050590271700,000$
16Steven SantiniX100.008076886376565850254240663854540505802621,000,000$
17Seth Barton (R)X100.00807493677441405025434164394444050550221925,000$
18Clayton Phillips (R)X100.00464477636444583525333046335454050480222575,000$
Rayé
1Tyler Weiss (R)X100.00484262685650614450433545395050050470213650,000$
MOYENNE D’ÉQUIPE100.0071618768705559534751496441484805056
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 SPÂgeContratSalaire moyen
1Nico Daws (R)100.0063474783695669636562784646050610204850,833$
2Trent Miner (R)100.0044425370454445494545454444050480203560,000$
Rayé
1Hunter Shepard (R)100.0044415173454445494545454444050480252950,000$
2Tomas Vomacka (R)100.0044716464433839413639385450050470222525,000$
MOYENNE D’ÉQUIPE100.004950547351465051484852474605051
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire


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
1Shane PintoManchots (Pit)C6727406712220852042567917810.55%24152622.78013134116401131543355.82%170900000.88210000641
2C.J. SuessManchots (Pit)LW82333164-42401451032988021811.07%25159919.5166124619112361062244.19%17200000.8024000633
3Mackenzie MacEachernManchots (Pit)LW/RW8225345981801011002246115911.16%16153018.674593620400031966340.15%13700000.77210000313
4Jamie DrysdalePittsburghD71133952314067145128377210.16%98176424.859716712000113175400.00%000010.5900000323
5Simon HolmstromManchots (Pit)LW/RW81183250105620118831723611010.47%14139917.2848123021020251145041.77%15800000.7105112274
6Vitaly AbramovManchots (Pit)LW/RW82252449-522087110259621639.65%16148918.17781543211000003139.29%8400000.6611000323
7Paul CareyManchots (Pit)LW82143448-1335134149270701865.19%18132116.1214511510001154037.40%12300000.7312010141
8Ian MitchellManchots (Pit)D82123648-81204897146471138.22%114170120.7461016671990002175200.00%000000.5600000302
9Joel HanleyManchots (Pit)D8272734-64751768210734806.54%121174721.31448392140113176100.00%000100.3900000013
10Joel KellmanManchots (Pit)C8214203404401231901353310910.37%10137216.742578108000072151.97%160100000.5000000153
11Mikhail VorobyevManchots (Pit)C82102434-512019144156561276.41%5131816.0806610840112410058.05%149700000.5200000012
12Tyler SteenbergenManchots (Pit)C/LW/RW82141529-51606063173531218.09%8124715.22000111000001063.41%8200000.4611000113
13Steven SantiniManchots (Pit)D8232225106010136395516565.45%87129115.76101729011050200.00%000000.3900011011
14Ivan ChekhovichManchots (Pit)LW8251217-3201047388330646.02%126307.680443100003790047.66%10700000.5400200001
15Dan RenoufManchots (Pit)D827916-479151602956173612.50%79146117.8311211111000072110.00%000000.2200012001
16Seth BartonManchots (Pit)D8228101137583242911176.90%6287910.7300025000056000.00%000000.2300000000
17Blade JenkinsManchots (Pit)C/LW78459-18044614212419.52%45186.65000010000480052.68%54100000.3500000002
18Pavel GogolevManchots (Pit)LW401450205111379.09%01012.53011320000000045.83%4800000.9900000000
19Clayton PhillipsManchots (Pit)D5000200200000.00%38917.980000000002000.00%000000.00%00000000
Statistiques d’équipe totales ou en moyenne1408234416650145267016401662260073718579.00%7162299216.33458212742920323710311472361153.38%625900110.57933345293236
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
1Nico DawsManchots (Pit)58331760.9212.6433686214818800310.70337580792
2Trent MinerManchots (Pit)29101410.8943.40144921827770100.00%02458311
3Daniel VladarPittsburgh42200.9233.0123900121550000.00%0413001
4Hunter ShepardManchots (Pit)50100.9063.08156008850000.00%0024000
Statistiques d’équipe totales ou en moyenne96453470.9142.88521483250289704137869510104


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 moyen restantPlafond salarial Plafond salarial restant Exclus du plafond salarial Salaire annuel 2Salaire annuel 3Salaire annuel 4Salaire annuel 5Salaire annuel 6Salaire annuel 7Salaire annuel 8Salaire annuel 9Salaire annuel 10Link
Blade JenkinsManchots (Pit)C/LW212000-08-11Yes194 Lbs6 ft1YesNoNo3Pro & Farm600,000$0$0$No600,000$600,000$Lien
C.J. Suess (contrat à 1 volet)Manchots (Pit)LW271994-03-16No190 Lbs5 ft11NoNoYes2Pro & Farm700,000$0$0$No700,000$Lien
Clayton PhillipsManchots (Pit)D221999-09-09Yes182 Lbs5 ft10NoNoNo2Pro & Farm575,000$0$0$No575,000$Lien
Dan Renouf (contrat à 1 volet)Manchots (Pit)D271994-06-01No198 Lbs6 ft3NoNoYes1Pro & Farm700,000$0$0$NoLien
Hunter ShepardManchots (Pit)G251995-11-07Yes201 Lbs6 ft0NoNoYes2Pro & Farm950,000$0$0$No950,000$Lien
Ian MitchellManchots (Pit)D221999-01-18No173 Lbs5 ft11NoNoNo2Pro & Farm925,000$0$0$No925,000$Lien
Ivan ChekhovichManchots (Pit)LW221999-01-04No187 Lbs5 ft11NoNoNo2Pro & Farm776,667$0$0$No776,667$Lien
Joel Hanley (contrat à 1 volet)Manchots (Pit)D301991-06-08No190 Lbs5 ft11NoNoYes2Pro & Farm1,020,000$120,000$0$No1,020,000$Lien
Joel Kellman (contrat à 1 volet)Manchots (Pit)C271994-05-25No192 Lbs5 ft11NoNoYes2Pro & Farm800,000$0$0$No800,000$Lien
Mackenzie MacEachern (contrat à 1 volet)Manchots (Pit)LW/RW271994-03-08No190 Lbs6 ft2NoNoYes2Pro & Farm560,000$0$0$No560,000$Lien
Mikhail VorobyevManchots (Pit)C241997-01-04No194 Lbs6 ft2NoNoYes1Pro & Farm650,000$0$0$NoLien
Nico DawsManchots (Pit)G202000-12-22Yes203 Lbs6 ft4NoNoNo4Pro & Farm850,833$0$0$No850,833$850,833$850,833$Lien
Paul Carey (contrat à 1 volet)Manchots (Pit)LW331988-09-24No200 Lbs6 ft1NoNoYes2Pro & Farm875,000$0$0$No875,000$Lien
Pavel GogolevManchots (Pit)LW212000-02-19Yes198 Lbs6 ft1NoNoNo4Pro & Farm834,167$0$0$No834,167$834,167$834,167$Lien
Seth BartonManchots (Pit)D221999-08-18Yes196 Lbs6 ft3YesNoNo1Pro & Farm925,000$0$0$NoLien
Shane PintoManchots (Pit)C202000-11-12No192 Lbs6 ft2NoNoNo2Pro & Farm925,000$0$0$No925,000$Lien
Simon HolmstromManchots (Pit)LW/RW202001-05-24Yes202 Lbs6 ft2NoNoNo2Pro & Farm894,167$0$0$No894,167$Lien
Steven Santini (contrat à 1 volet)Manchots (Pit)D261995-03-07No205 Lbs6 ft2NoNoYes2Pro & Farm1,000,000$100,000$0$No1,000,000$Lien
Tomas VomackaManchots (Pit)G221999-05-02Yes165 Lbs6 ft3NoNoNo2Pro & Farm525,000$0$0$No525,000$Lien
Trent MinerManchots (Pit)G202001-02-05Yes185 Lbs6 ft1NoNoNo3Pro & Farm560,000$0$0$No560,000$560,000$Lien
Tyler SteenbergenManchots (Pit)C/LW/RW231998-01-07No188 Lbs5 ft10NoNoNo1Pro & Farm650,000$0$0$NoLien
Tyler WeissManchots (Pit)LW212000-01-03Yes151 Lbs5 ft11NoNoNo3Pro & Farm650,000$0$0$No650,000$650,000$Lien
Vitaly AbramovManchots (Pit)LW/RW231998-05-08Yes181 Lbs5 ft10YesNoNo2Pro & Farm600,000$0$0$No600,000$Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2323.70189 Lbs6 ft12.13762,862$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Mackenzie MacEachernShane PintoSimon Holmstrom40122
2Paul CareyJoel KellmanVitaly Abramov30122
3C.J. SuessTyler SteenbergenIvan Chekhovich20122
4Ivan ChekhovichMikhail VorobyevShane Pinto10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Joel HanleyIan Mitchell40122
2Dan RenoufSteven Santini30122
3Seth BartonClayton Phillips20122
4Joel HanleyIan Mitchell10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Mackenzie MacEachernShane PintoSimon Holmstrom60122
2Paul CareyJoel KellmanVitaly Abramov40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Joel HanleyIan Mitchell60122
2Dan RenoufSteven Santini40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Shane PintoMackenzie MacEachern60122
2Simon HolmstromPaul Carey40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Joel HanleyIan Mitchell60122
2Dan RenoufSteven Santini40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Shane Pinto60122Joel HanleyIan Mitchell60122
2Mackenzie MacEachern40122Dan RenoufSteven Santini40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Shane PintoMackenzie MacEachern60122
2Simon HolmstromPaul Carey40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Joel HanleyIan Mitchell60122
2Dan RenoufSteven Santini40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Mackenzie MacEachernShane PintoSimon HolmstromJoel HanleyIan Mitchell
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Mackenzie MacEachernShane PintoSimon HolmstromJoel HanleyIan Mitchell
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Blade Jenkins, Pavel Gogolev, C.J. SuessBlade Jenkins, Pavel GogolevC.J. Suess
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Seth Barton, Clayton Phillips, Dan RenoufSeth BartonClayton Phillips, Dan Renouf
Tirs de pénalité
Shane Pinto, Mackenzie MacEachern, Simon Holmstrom, Paul Carey, C.J. Suess
Gardien
#1 : Nico Daws, #2 : Trent Miner


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
TotalDomicileVisiteur
# 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
1Admirals21100000330110000003121010000002-220.50036900968565126093093088972571314325120.00%7185.71%01528279054.77%1344258951.91%737135354.47%2096145217945901093566
2Baby Hawks21100000770110000003121010000046-220.500712190096856512659309308897273171858500.00%6350.00%01528279054.77%1344258951.91%737135354.47%2096145217945901093566
3Bears30200001811-31010000012-12010000179-210.167816240096856512117930930889728917144816318.75%70100.00%01528279054.77%1344258951.91%737135354.47%2096145217945901093566
4Bruins31200000913-4211000008801010000015-420.33391625009685651289930930889721032031627342.86%13376.92%01528279054.77%1344258951.91%737135354.47%2096145217945901093566
5Cabaret Lady Mary Ann330000001569110000006422200000092761.0001527420096856512167930930889721142023914125.00%9188.89%11528279054.77%1344258951.91%737135354.47%2096145217945901093566
6Caroline422000001192211000005502110000064240.5001119300096856512132930930889721413926649222.22%13192.31%01528279054.77%1344258951.91%737135354.47%2096145217945901093566
7Chiefs211000001091110000005321010000056-120.5001016260096856512709309308897259166418225.00%3233.33%01528279054.77%1344258951.91%737135354.47%2096145217945901093566
8Chill200010101082100000104311000100065141.0001016260096856512729309308897284271466700.00%6266.67%11528279054.77%1344258951.91%737135354.47%2096145217945901093566
9Comets2010010046-21010000034-11000010012-110.250471100968565125793093088972691910348112.50%40100.00%01528279054.77%1344258951.91%737135354.47%2096145217945901093566
10Cougars3200000112931000000156-12200000073450.8331221330096856512115930930889729317165312216.67%8187.50%01528279054.77%1344258951.91%737135354.47%2096145217945901093566
11Crunch3200000111831000000123-12200000095450.833112132009685651211293093088972802622619444.44%11281.82%11528279054.77%1344258951.91%737135354.47%2096145217945901093566
12Heat211000005501010000012-11100000043120.5005101500968565126593093088972731914504250.00%7185.71%01528279054.77%1344258951.91%737135354.47%2096145217945901093566
13Jayhawks2110000046-21010000025-31100000021120.50048120096856512709309308897260248458337.50%4175.00%01528279054.77%1344258951.91%737135354.47%2096145217945901093566
14Las Vegas2010010069-31010000046-21000010023-110.2506121800968565126493093088972631616496116.67%7357.14%01528279054.77%1344258951.91%737135354.47%2096145217945901093566
15Marlies31200000613-720200000312-91100000031220.333611170096856512120930930889728018387710220.00%6183.33%01528279054.77%1344258951.91%737135354.47%2096145217945901093566
16Minnesota20100010660100000102111010000045-120.50069150096856512679309308897270221039300.00%5180.00%01528279054.77%1344258951.91%737135354.47%2096145217945901093566
17Monarchs220000001266110000008351100000043141.00012223400968565121239309308897267222635240.00%10100.00%01528279054.77%1344258951.91%737135354.47%2096145217945901093566
18Monsters422000001314-122000000103720200000311-840.500132336009685651212893093088972116508781715.88%4175.00%01528279054.77%1344258951.91%737135354.47%2096145217945901093566
19Monsters2020000048-41010000034-11010000014-300.00047110096856512579309308897277192244800.00%10190.00%01528279054.77%1344258951.91%737135354.47%2096145217945901093566
20Oceanics210000101055100000102111100000084441.00010162600968565127293093088972632120399333.33%3166.67%01528279054.77%1344258951.91%737135354.47%2096145217945901093566
21Oil Kings20200000610-41010000035-21010000035-200.000611170096856512729309308897276151241600.00%6266.67%01528279054.77%1344258951.91%737135354.47%2096145217945901093566
22Phantoms320010001147220000007161000100043161.0001122330196856512107930930889728529234714321.43%8187.50%01528279054.77%1344258951.91%737135354.47%2096145217945901093566
23Rocket31100001810-21000000145-12110000045-130.5008162400968565128593093088972963720679222.22%9188.89%01528279054.77%1344258951.91%737135354.47%2096145217945901093566
24Seattle2110000035-2110000001011010000025-320.5003690196856512689309308897271108496116.67%40100.00%01528279054.77%1344258951.91%737135354.47%2096145217945901093566
25Senators31200000660211000004311010000023-120.3336121800968565129093093088972923126551119.09%8275.00%01528279054.77%1344258951.91%737135354.47%2096145217945901093566
26Sharks20100010770100000104311010000034-120.500711180096856512649309308897280251438100.00%70100.00%01528279054.77%1344258951.91%737135354.47%2096145217945901093566
27Sound Tigers41200001812-42010000136-32110000056-130.3758152300968565121179309308897213956107610110.00%50100.00%01528279054.77%1344258951.91%737135354.47%2096145217945901093566
28Spiders421000101293220000006332010001066060.75012203200968565121279309308897213432328112325.00%16475.00%01528279054.77%1344258951.91%737135354.47%2096145217945901093566
29Stars2110000067-11010000035-21100000032120.500691510968565124693093088972812325453133.33%7185.71%01528279054.77%1344258951.91%737135354.47%2096145217945901093566
30Thunder330000001046220000006241100000042261.0001015250096856512779309308897210330366312325.00%13192.31%01528279054.77%1344258951.91%737135354.47%2096145217945901093566
31Wolf Pack421010001192210010007522110000044060.75011223301968565121139309308897215549249210110.00%12283.33%11528279054.77%1344258951.91%737135354.47%2096145217945901093566
Total8235320325525424410411814010441281151341171802211126129-3930.5672544547081396856512278893093088972274377956217482544919.29%2294082.53%41528279054.77%1344258951.91%737135354.47%2096145217945901093566
_Since Last GM Reset8235320325525424410411814010441281151341171802211126129-3930.5672544547081396856512278893093088972274377956217482544919.29%2294082.53%41528279054.77%1344258951.91%737135354.47%2096145217945901093566
_Vs Conference4419160304213612412241360103176562020610020116068-8540.614136243379029685651214769309308897214474403069171462718.49%1161983.62%21528279054.77%1344258951.91%737135354.47%2096145217945901093566

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
8293L125445470827882743779562174813
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
8235323255254244
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4118141044128115
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
4117182211126129
Derniers 10 matchs
WLOTWOTL SOWSOL
640000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
2544919.29%2294082.53%4
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
9309308897296856512
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
1528279054.77%1344258951.91%737135354.47%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
2096145217945901093566


Derniers matchs 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
7 - 2022-10-1311Jayhawks5Manchots2BLSommaire du match
9 - 2022-10-1531Thunder1Manchots3BWSommaire du match
11 - 2022-10-1742Manchots2Rocket4ALSommaire du match
14 - 2022-10-2062Monarchs3Manchots8BWSommaire du match
16 - 2022-10-2282Manchots1Monsters4ALSommaire du match
18 - 2022-10-2494Manchots3Oil Kings5ALSommaire du match
19 - 2022-10-25104Manchots4Heat3AWSommaire du match
22 - 2022-10-28125Manchots1Comets2ALXSommaire du match
23 - 2022-10-29137Manchots2Seattle5ALSommaire du match
26 - 2022-11-01147Bruins2Manchots4BWSommaire du match
27 - 2022-11-02160Manchots3Crunch2AWSommaire du match
30 - 2022-11-05184Seattle0Manchots1BWSommaire du match
34 - 2022-11-09208Manchots3Bears4ALSommaire du match
36 - 2022-11-11221Manchots3Marlies1AWSommaire du match
37 - 2022-11-12229Manchots2Rocket1AWSommaire du match
40 - 2022-11-15251Marlies5Manchots2BLSommaire du match
42 - 2022-11-17268Manchots4Minnesota5ALSommaire du match
44 - 2022-11-19276Manchots8Oceanics4AWSommaire du match
45 - 2022-11-20290Manchots4Baby Hawks6ALSommaire du match
48 - 2022-11-23306Heat2Manchots1BLSommaire du match
50 - 2022-11-25324Manchots4Phantoms3AWXSommaire du match
51 - 2022-11-26335Marlies7Manchots1BLSommaire du match
54 - 2022-11-29352Caroline3Manchots2BLSommaire du match
56 - 2022-12-01368Las Vegas6Manchots4BLSommaire du match
58 - 2022-12-03384Chiefs3Manchots5BWSommaire du match
61 - 2022-12-06404Monsters2Manchots5BWSommaire du match
64 - 2022-12-09426Manchots6Crunch3AWSommaire du match
65 - 2022-12-10437Crunch3Manchots2BLXXSommaire du match
67 - 2022-12-12449Stars5Manchots3BLSommaire du match
70 - 2022-12-15474Manchots4Cabaret Lady Mary Ann1AWSommaire du match
73 - 2022-12-18498Manchots0Caroline2ALSommaire du match
75 - 2022-12-20511Wolf Pack2Manchots3BWSommaire du match
77 - 2022-12-22526Caroline2Manchots3BWSommaire du match
82 - 2022-12-27550Manchots4Sound Tigers3AWSommaire du match
83 - 2022-12-28560Cougars6Manchots5BLXXSommaire du match
85 - 2022-12-30576Spiders2Manchots4BWSommaire du match
88 - 2023-01-02595Manchots1Bruins5ALSommaire du match
91 - 2023-01-05620Manchots2Las Vegas3ALXSommaire du match
94 - 2023-01-08640Manchots2Jayhawks1AWSommaire du match
96 - 2023-01-10652Comets4Manchots3BLSommaire du match
99 - 2023-01-13674Oceanics1Manchots2BWXXSommaire du match
100 - 2023-01-14682Manchots6Caroline2AWSommaire du match
102 - 2023-01-16700Admirals1Manchots3BWSommaire du match
104 - 2023-01-18712Manchots2Senators3ALSommaire du match
106 - 2023-01-20730Senators1Manchots3BWSommaire du match
108 - 2023-01-22746Manchots3Spiders2AWXXSommaire du match
110 - 2023-01-24756Cabaret Lady Mary Ann4Manchots6BWSommaire du match
112 - 2023-01-26773Manchots4Bears5ALXXSommaire du match
114 - 2023-01-28793Sharks3Manchots4BWXXSommaire du match
124 - 2023-02-07813Monsters4Manchots3BLSommaire du match
127 - 2023-02-10831Manchots0Admirals2ALSommaire du match
128 - 2023-02-11845Manchots4Monarchs3AWSommaire du match
131 - 2023-02-14863Manchots3Sharks4ALSommaire du match
134 - 2023-02-17879Manchots1Sound Tigers3ALSommaire du match
135 - 2023-02-18886Spiders1Manchots2BWSommaire du match
137 - 2023-02-20906Sound Tigers3Manchots2BLXXSommaire du match
140 - 2023-02-23922Oil Kings5Manchots3BLSommaire du match
142 - 2023-02-25943Manchots5Chiefs6ALSommaire du match
143 - 2023-02-26951Thunder1Manchots3BWSommaire du match
145 - 2023-02-28963Manchots6Chill5AWXSommaire du match
147 - 2023-03-02977Manchots4Thunder2AWSommaire du match
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
149 - 2023-03-04993Manchots5Cabaret Lady Mary Ann1AWSommaire du match
152 - 2023-03-071013Monsters1Manchots5BWSommaire du match
154 - 2023-03-091027Sound Tigers3Manchots1BLSommaire du match
156 - 2023-03-111039Phantoms0Manchots4BWSommaire du match
157 - 2023-03-121054Wolf Pack3Manchots4BWXSommaire du match
159 - 2023-03-141064Rocket5Manchots4BLXXSommaire du match
161 - 2023-03-161082Manchots2Wolf Pack0AWSommaire du match
163 - 2023-03-181103Manchots2Wolf Pack4ALSommaire du match
165 - 2023-03-201115Senators2Manchots1BLSommaire du match
167 - 2023-03-221133Manchots1Monsters4ALSommaire du match
168 - 2023-03-231143Manchots3Stars2AWSommaire du match
170 - 2023-03-251162Bears2Manchots1BLSommaire du match
173 - 2023-03-281180Manchots3Cougars2AWSommaire du match
175 - 2023-03-301192Chill3Manchots4BWXXSommaire du match
177 - 2023-04-011205Bruins6Manchots4BLSommaire du match
178 - 2023-04-021221Phantoms1Manchots3BWSommaire du match
180 - 2023-04-041233Manchots3Spiders4ALSommaire du match
182 - 2023-04-061244Minnesota1Manchots2BWXXSommaire du match
184 - 2023-04-081266Manchots4Cougars1AWSommaire du match
187 - 2023-04-111286Baby Hawks1Manchots3BWSommaire du match
189 - 2023-04-131303Manchots2Monsters7ALSommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité17501250
Prix des billets5020
Assistance43,49933,684
Assistance PCT60.63%65.72%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
0 1883 - 62.75% 69,479$2,848,630$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
1,279,234$ 1,189,084$ 1,189,084$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
6,258$ 1,279,234$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 0 6,258$ 0$




Manchots Leaders statistiques (saison régulière)

# Nom du joueur GP G A P +/- PIM HIT HTT SHT SHT% SB MP AMG PPG PPA PPP PPS PKG PKA PKP PKS GW GT FO% HT P/20 PSG PSS

Manchots Leaders des statistiques des gardiens (saison régulière)

# Nom du gardien GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA

Manchots Statistiques de l'Équipe de Carrière

TotalDomicileVisiteur
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

Manchots Leaders statistiques (séries éliminatoires)

# Nom du joueur GP G A P +/- PIM HIT HTT SHT SHT% SB MP AMG PPG PPA PPP PPS PKG PKA PKP PKS GW GT FO% HT P/20 PSG PSS

Manchots Leaders des statistiques des gardiens (séries éliminatoires)

# Nom du gardien GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA