Americans

GP: 25 | W: 13 | L: 11 | OTL: 1 | P: 27
GF: 66 | GA: 45 | PP%: 15.09% | PK%: 87.04%
DG: Frederic Goldstyn | Morale : 52 | Moyenne d'Équipe : 59
Prochain matchs #395 vs Monsters
La résolution de votre navigateur est trop petite pour cette page. Plusieurs informations sont cachées pour garder la page lisible.

Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du Joueur C L R D CON CK FG DI SK ST EN DU PH FO PA SC DF PS EX LD PO MO OV TA SP
1Anton SlepyshevX100.00875560777771657250666771557870158670
2Brandon PirriX100.00655574848078786550606560557774158650
3John QuennevilleX100.00595563807669696250606060555050158610
4Peter CehlarikX100.00605564747971696250616160555050158610
5Justin Kloos (R)X100.00655573716269766050606260555050161600
6Zach SanfordX100.00605574747465646050606159555050162600
7Taylor BeckX100.00605569667869696050606161555556158600
8Cameron DarcyX100.00755565627767665550555555557166149580
9Eric Cornel (R)X100.00565565627770715550555555557266153580
10Shane HarperX100.00605559726866625850575859555050158580
11Conner Bleackley (R)X100.00565566627367685550555555557371154570
12Cam DarcyX100.00655566557359685550555555557373149560
13Deven Sideroff (R)X100.00565555555657575550555555557573158550
14Julius HonkaX100.00715583917073787625636175557977158710
15Kyle QuinceyX100.00725561738875816725636069558578158690
16Casey NelsonX100.00755588757284617225636577557271159690
17Kevin GravelX100.00705575707075647025626067555353158630
18Calle Rosen (R)X100.00605562755872726425616062556262158620
19Justin HollX100.00605569636281686525606562555353158600
20Reece ScarlettX100.00555557605757645725575757555353135550
Rayé
1Devin Setoguchi (R)X100.00555555555555555550555555557171132540
2Erik CondraX100.00565555555657575550555555557173125540
3Chase Lang (R)X100.00565555555758585550555555556568129540
4Greg CareyX100.00565555555657565550555555557150127530
5Julius Nattinen (R)X100.00565555555556555550555555555050125520
6Vaclav Karabacek (R)X100.00565555555555555550555555555050125520
7Yakov Trenin (R)X100.00565555555555555550555555555050125520
8Oliver KylingtonX100.00555557605757635725575757555353127550
9Robbie RussoX100.00555555605555755525555555555353139550
10Jyrki JokipakkaX100.00555555605555555525555555556262125540
11Vojtech MozikX100.00555555605555675525555555555353125540
12Blake Siebenaler (R)X100.00555555605555645525555555555353125540
MOYENNE D'ÉQUIPE100.0061556365656565604158585955626014558
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
1Marek Mazanec100.0071808776686873667070557169143690
2Charlie Lindgren100.0066706772707071687071556967158680
Rayé
MOYENNE D'ÉQUIPE100.006975777469697267707155706815169
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Scott Stevens51536157657059CAN521100,000$


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'ÉquipePOS GP 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
1Casey NelsonAmericans (Buf)D257182515315313561253311.48%1859323.766511461260000126100.00%000000.8400001222
2Julius HonkaAmericans (Buf)D247172415300333855183612.73%2055623.185611461190001116100.00%000010.8600000210
3Anton SlepyshevAmericans (Buf)LW25512179400104657727596.49%257222.900441811600071251152.80%32200000.5900000301
4Zach SanfordAmericans (Buf)LW25107174281030175393318.87%143217.30549171120000272053.66%4100000.7900101110
5John QuennevilleAmericans (Buf)C2511415520031534711452.13%250420.19088141210001790053.86%44000000.5900000002
6Brandon PirriAmericans (Buf)C2586141220104040222920.00%757823.160221011800021432054.20%47600000.4800000121
7Kevin GravelAmericans (Buf)D254711024026174622218.70%1653621.45336341150000107000.00%000000.4100000110
8Justin KloosAmericans (Buf)C252810327526393514235.71%032312.95000113000061051.84%24500000.6200100101
9Kyle QuinceyAmericans (Buf)D252810144064305918353.39%2654021.632810441160000105000.00%000000.3700000000
10Shane HarperAmericans (Buf)RW2573105160371843132916.28%041716.7020215122000001041.67%2400000.4800000101
11Peter CehlarikAmericans (Buf)RW2545982018253772910.81%546818.74145161210000741056.44%10100000.3800000022
12Justin HollAmericans (Buf)D25538318034241951126.32%1640216.0900036000060100.00%000000.4000000100
13Taylor BeckAmericans (Buf)LW25257520020213014276.67%335314.150001140000441062.50%5600000.4000000010
14Calle RosenAmericans (Buf)D2507723803824147140.00%1435714.2900041500006000.00%000000.3900000010
15Deven SideroffAmericans (Buf)RW25112316020514297.14%330212.0800004000000059.09%2200000.1300000001
16Eric CornelAmericans (Buf)C2210112011171414.29%0924.1900000000001051.72%8700000.2200000010
17Conner BleackleyAmericans (Buf)C20011000221330.00%0683.4200002000000075.00%400000.2900000000
18Cameron DarcyAmericans (Buf)C15000000011000.00%0211.44000000000160050.00%1000000.0000000000
19Devin SetoguchiAmericans (Buf)RW7000000102130.00%0355.02000100000000100.00%100000.0000000000
20Cam DarcyAmericans (Buf)C15000000000000.00%000.020000000000000.00%000000.0000000000
21Greg CareyAmericans (Buf)C3000-100230020.00%0175.80000000000000100.00%100000.0000000000
22Chase LangAmericans (Buf)RW5000-100220030.00%0183.6700001000000033.33%300000.0000000000
23Oliver KylingtonAmericans (Buf)D2000000100000.00%094.970000000002000.00%000000.0000000000
24Robbie RussoAmericans (Buf)D7000000100000.00%330.460000000003000.00%000000.0000000000
25Reece ScarlettAmericans (Buf)D7000000000000.00%020.360000000001000.00%000000.0000000000
Stats d'équipe Total ou en Moyenne47766122188893582053247064121944810.30%136720915.12244468270125200011104713153.74%183300010.5200202131211
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
1Marek MazanecAmericans (Buf)25131010.9071.87141006444740200.0000250222
2Charlie LindgrenAmericans (Buf)30100.9720.6592001360000.0000025000
Stats d'équipe Total ou en Moyenne28131110.9121.80150306455100200.00002525222


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 StatusType Salaire Actuel Cap Salariale Cap Salariale Restant Exclus du Cap Salarial Salaire Année 2 Salaire Année 3 Salaire Année 4 Salaire Année 5 Salaire Année 6 Salaire Année 7 Salaire Année 8 Salaire Année 9 Salaire Année 10 Link
Anton SlepyshevAmericans (Buf)LW221994-05-13No194 Lbs6 ft2NoNoNo2Contrat d'EntréePro & Farm300,000$0$0$No300,000$
Blake SiebenalerAmericans (Buf)D201996-02-27Yes208 Lbs6 ft1NoNoNo3Contrat d'EntréePro & Farm300,000$0$0$No300,000$300,000$
Brandon PirriAmericans (Buf)C251991-04-09No183 Lbs6 ft0NoNoNo2Avec RestrictionPro & Farm500,000$0$0$No500,000$
Calle RosenAmericans (Buf)D221994-02-02Yes176 Lbs6 ft1NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No300,000$300,000$300,000$
Cam DarcyAmericans (Buf)C221994-03-02No185 Lbs6 ft0NoNoNo4Contrat d'EntréePro & Farm500,000$0$0$No500,000$500,000$500,000$
Cameron DarcyAmericans (Buf)C221994-03-02No192 Lbs6 ft0NoNoNo2Contrat d'EntréePro & Farm300,000$0$0$No300,000$
Casey NelsonAmericans (Buf)D241992-07-18No183 Lbs6 ft2NoNoNo3Avec RestrictionPro & Farm300,000$0$0$No300,000$300,000$
Charlie LindgrenAmericans (Buf)G231993-12-17No181 Lbs6 ft1NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No300,000$
Chase LangAmericans (Buf)RW201996-09-13Yes187 Lbs6 ft1NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No300,000$300,000$300,000$
Conner BleackleyAmericans (Buf)C201996-02-07Yes192 Lbs6 ft0NoNoNo3Contrat d'EntréePro & Farm500,000$0$0$No500,000$500,000$
Deven SideroffAmericans (Buf)RW191997-04-14Yes179 Lbs6 ft0NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No300,000$300,000$300,000$
Devin SetoguchiAmericans (Buf)RW301987-01-01Yes205 Lbs6 ft0NoNoNo1Sans RestrictionPro & Farm500,000$0$0$No
Eric CornelAmericans (Buf)C201996-04-11Yes191 Lbs6 ft2NoNoNo3Contrat d'EntréePro & Farm500,000$0$0$No500,000$500,000$
Erik CondraAmericans (Buf)RW301986-08-06No190 Lbs6 ft0NoNoNo3Sans RestrictionPro & Farm350,000$0$0$No350,000$350,000$
Greg CareyAmericans (Buf)C261990-05-09No195 Lbs6 ft0NoNoNo3Avec RestrictionPro & Farm300,000$0$0$No300,000$300,000$
John QuennevilleAmericans (Buf)C201996-04-16No195 Lbs6 ft1NoNoNo3Contrat d'EntréePro & Farm500,000$0$0$No500,000$500,000$
Julius HonkaAmericans (Buf)D211995-12-03No185 Lbs5 ft11NoNoNo2Contrat d'EntréePro & Farm900,000$0$0$No900,000$
Julius NattinenAmericans (Buf)C191997-01-14Yes205 Lbs6 ft2NoNoNo4Contrat d'EntréePro & Farm500,000$0$0$No500,000$500,000$500,000$
Justin HollAmericans (Buf)D241992-01-30No170 Lbs6 ft2NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No300,000$
Justin KloosAmericans (Buf)C231993-11-30Yes179 Lbs5 ft9NoNoNo4Avec RestrictionPro & Farm300,000$0$0$No300,000$300,000$300,000$
Jyrki JokipakkaAmericans (Buf)D251991-08-20No210 Lbs6 ft3NoNoNo4Avec RestrictionPro & Farm300,000$0$0$No300,000$300,000$300,000$
Kevin GravelAmericans (Buf)D241992-03-06No185 Lbs6 ft4NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Kyle QuinceyAmericans (Buf)D311985-08-12No216 Lbs6 ft2NoNoNo2Sans RestrictionPro & Farm1,000,000$0$0$No1,000,000$
Marek MazanecAmericans (Buf)G251991-07-18No187 Lbs6 ft4NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No300,000$
Oliver KylingtonAmericans (Buf)D191997-05-19No181 Lbs6 ft0NoNoNo3Contrat d'EntréePro & Farm500,000$0$0$No500,000$500,000$
Peter CehlarikAmericans (Buf)RW211995-08-02No202 Lbs6 ft2NoNoNo3Contrat d'EntréePro & Farm300,000$0$0$No300,000$300,000$
Reece ScarlettAmericans (Buf)D231993-03-30No180 Lbs5 ft11NoNoNo3Avec RestrictionPro & Farm300,000$0$0$No300,000$300,000$
Robbie RussoAmericans (Buf)D231993-02-15No190 Lbs6 ft0NoNoNo4Avec RestrictionPro & Farm300,000$0$0$No300,000$300,000$300,000$
Shane HarperAmericans (Buf)RW271989-01-31No193 Lbs5 ft11NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Taylor BeckAmericans (Buf)LW251991-05-12No203 Lbs6 ft2NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No300,000$
Vaclav KarabacekAmericans (Buf)RW201996-05-02Yes199 Lbs6 ft0NoNoNo3Contrat d'EntréePro & Farm500,000$0$0$No500,000$500,000$
Vojtech MozikAmericans (Buf)D241992-12-26No196 Lbs6 ft2NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No300,000$
Yakov TreninAmericans (Buf)C201997-01-13Yes205 Lbs6 ft2NoNoNo4Contrat d'EntréePro & Farm500,000$0$0$No500,000$500,000$500,000$
Zach SanfordAmericans (Buf)LW221994-11-09No192 Lbs6 ft4NoNoNo3Contrat d'EntréePro & Farm500,000$0$0$No500,000$500,000$
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
3422.97192 Lbs6 ft12.79404,412$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Anton SlepyshevBrandon PirriPeter Cehlarik40122
2Zach SanfordJohn QuennevilleShane Harper30122
3Taylor BeckJustin KloosDeven Sideroff20122
4Conner BleackleyEric CornelAnton Slepyshev10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Julius HonkaCasey Nelson40122
2Kyle QuinceyKevin Gravel30122
3Calle RosenJustin Holl20122
4Julius HonkaCasey Nelson10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Anton SlepyshevBrandon PirriPeter Cehlarik60122
2Zach SanfordJohn QuennevilleShane Harper40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Julius HonkaCasey Nelson60122
2Kyle QuinceyKevin Gravel40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Anton SlepyshevBrandon Pirri60122
2Peter CehlarikJohn Quenneville40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Julius HonkaCasey Nelson60122
2Kyle QuinceyKevin Gravel40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Anton Slepyshev60122Julius HonkaCasey Nelson60122
2Brandon Pirri40122Kyle QuinceyKevin Gravel40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Anton SlepyshevBrandon Pirri60122
2Peter CehlarikJohn Quenneville40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Julius HonkaCasey Nelson60122
2Kyle QuinceyKevin Gravel40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Anton SlepyshevBrandon PirriPeter CehlarikJulius HonkaCasey Nelson
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Anton SlepyshevBrandon PirriPeter CehlarikJulius HonkaCasey Nelson
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Conner Bleackley, Justin Kloos, Taylor BeckConner Bleackley, Justin KloosTaylor Beck
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Calle Rosen, Justin Holl, Kyle QuinceyCalle RosenJustin Holl, Kyle Quincey
Tirs de Pénalité
Anton Slepyshev, Brandon Pirri, Peter Cehlarik, John Quenneville, Justin Kloos
Gardien
#1 : Marek Mazanec, #2 : Charlie Lindgren


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
1Bears211000004311010000013-21100000030320.50047110124212014821019822764111285119421.05%13192.31%040076552.29%40471956.19%18134252.92%688488518177300160
2Bruins2020000004-41010000003-31010000001-100.000000002421201382101982276371430311300.00%14285.71%040076552.29%40471956.19%18134252.92%688488518177300160
3Checkers2200000012392200000012390000000000041.00012223400242120173210198227639926607228.57%80100.00%040076552.29%40471956.19%18134252.92%688488518177300160
4Comets440000001621433000000122101100000040481.00016284402242120111621019822766514488830516.67%24291.67%040076552.29%40471956.19%18134252.92%688488518177300160
5Crunch30300000711-42020000036-31010000045-100.000714210024212015821019822767723485815213.33%24579.17%040076552.29%40471956.19%18134252.92%688488518177300160
6Devils32100000725110000003032110000042240.667714210224212015521019822768317445217317.65%20195.00%040076552.29%40471956.19%18134252.92%688488518177300160
7Marlies10001000321100010003210000000000021.0003690024212014921019822762191016400.00%5180.00%040076552.29%40471956.19%18134252.92%688488518177300160
8Monsters1010000012-11010000012-10000000000000.00012300242120111210198227629324278112.50%12191.67%040076552.29%40471956.19%18134252.92%688488518177300160
9Penguins1010000014-31010000014-30000000000000.0001230024212011821019822761922110300.00%7271.43%040076552.29%40471956.19%18134252.92%688488518177300160
10Rocket11000000101110000001010000000000021.0001230124212013121019822761651632600.00%70100.00%040076552.29%40471956.19%18134252.92%688488518177300160
11Senators1010000023-1000000000001010000023-100.00024600242120124210198227614414238112.50%7271.43%040076552.29%40471956.19%18134252.92%688488518177300160
12Sound Tigers2010010035-2000000000002010010035-210.2503470024212015021019822763919304515213.33%14378.57%040076552.29%40471956.19%18134252.92%688488518177300160
13Thunderbirds11000000734000000000001100000073421.000713200024212014121019822761946238337.50%30100.00%040076552.29%40471956.19%18134252.92%688488518177300160
Total2512110110066452114760100037251211550010029209270.5406612218806242120164121019822765101363585321592415.09%1622187.04%040076552.29%40471956.19%18134252.92%688488518177300160
15Wolf Pack11000000211000000000001100000021121.00024600242120129210198227611213166116.67%4175.00%040076552.29%40471956.19%18134252.92%688488518177300160
_Since Last GM Reset2512110110066452114760100037251211550010029209270.5406612218806242120164121019822765101363585321592415.09%1622187.04%040076552.29%40471956.19%18134252.92%688488518177300160
_Vs Conference980010003910297600100028721220000001138181.0003971110032421201310210198227616041106219551018.18%47393.62%040076552.29%40471956.19%18134252.92%688488518177300160

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
2527W16612218864151013635853206
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
25121111006645
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
147610003725
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
115501002920
Derniers 10 Matchs
WLOTWOTL SOWSOL
550000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
1592415.09%1622187.04%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
21019822762421201
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
40076552.29%40471956.19%18134252.92%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
688488518177300160


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
3 - 2018-09-073Checkers2Americans5WSommaire du Match
4 - 2018-09-0815Checkers1Americans7WSommaire du Match
8 - 2018-09-1230Crunch2Americans0LSommaire du Match
11 - 2018-09-1543Americans2Sound Tigers3LSommaire du Match
12 - 2018-09-1658Americans1Sound Tigers2LXSommaire du Match
15 - 2018-09-1963Americans4Comets0WSommaire du Match
17 - 2018-09-2174Marlies2Americans3WXSommaire du Match
18 - 2018-09-2286Americans2Senators3LSommaire du Match
24 - 2018-09-28111Comets1Americans3WSommaire du Match
25 - 2018-09-29125Rocket0Americans1WSommaire du Match
31 - 2018-10-05145Bears3Americans1LSommaire du Match
32 - 2018-10-06156Americans3Bears0WSommaire du Match
36 - 2018-10-10177Monsters2Americans1LSommaire du Match
38 - 2018-10-12187Crunch4Americans3LSommaire du Match
45 - 2018-10-19229Americans7Thunderbirds3WSommaire du Match
46 - 2018-10-20245Americans0Bruins1LSommaire du Match
47 - 2018-10-21249Americans2Wolf Pack1WSommaire du Match
52 - 2018-10-26270Comets0Americans6WSommaire du Match
53 - 2018-10-27284Americans1Devils2LSommaire du Match
59 - 2018-11-02312Penguins4Americans1LSommaire du Match
60 - 2018-11-03327Americans3Devils0WSommaire du Match
64 - 2018-11-07344Comets1Americans3WSommaire du Match
66 - 2018-11-09353Bruins3Americans0LSommaire du Match
67 - 2018-11-10366Americans4Crunch5LSommaire du Match
71 - 2018-11-14386Devils0Americans3WSommaire du Match
73 - 2018-11-16395Monsters-Americans-
74 - 2018-11-17404Americans-Monsters-
78 - 2018-11-21430Senators-Americans-
80 - 2018-11-23437Wolf Pack-Americans-
81 - 2018-11-24453Wolf Pack-Americans-
85 - 2018-11-28465Americans-Monsters-
87 - 2018-11-30481Marlies-Americans-
88 - 2018-12-01490Americans-Comets-
92 - 2018-12-05512Sound Tigers-Americans-
94 - 2018-12-07524Americans-Rocket-
95 - 2018-12-08532Americans-Rocket-
101 - 2018-12-14568Marlies-Americans-
102 - 2018-12-15574Americans-Marlies-
108 - 2018-12-21608Americans-Penguins-
109 - 2018-12-22625Americans-Phantoms-
113 - 2018-12-26650Devils-Americans-
115 - 2018-12-28661Comets-Americans-
116 - 2018-12-29673Americans-Crunch-
122 - 2019-01-04689Americans-Devils-
123 - 2019-01-05701Americans-Wolf Pack-
127 - 2019-01-09719Crunch-Americans-
129 - 2019-01-11725Thunderbirds-Americans-
130 - 2019-01-12740Americans-Comets-
133 - 2019-01-15757Americans-Monsters-
136 - 2019-01-18774Crunch-Americans-
137 - 2019-01-19782Americans-Crunch-
138 - 2019-01-20797Devils-Americans-
141 - 2019-01-23811Monsters-Americans-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
143 - 2019-01-25818Americans-Comets-
144 - 2019-01-26834Senators-Americans-
148 - 2019-01-30852Americans-Comets-
151 - 2019-02-02871Americans-Crunch-
152 - 2019-02-03884Crunch-Americans-
157 - 2019-02-08904Sound Tigers-Americans-
158 - 2019-02-09916Americans-Devils-
159 - 2019-02-10926Devils-Americans-
162 - 2019-02-13938Comets-Americans-
164 - 2019-02-15946Americans-Checkers-
165 - 2019-02-16955Americans-Checkers-
171 - 2019-02-22988Monsters-Americans-
172 - 2019-02-23994Americans-Marlies-
173 - 2019-02-241011Americans-Marlies-
176 - 2019-02-271021Phantoms-Americans-
178 - 2019-03-011032Rocket-Americans-
179 - 2019-03-021048Americans-Devils-
185 - 2019-03-081077Crunch-Americans-
186 - 2019-03-091089Americans-Crunch-
188 - 2019-03-111104Americans-Monsters-
192 - 2019-03-151121Devils-Americans-
193 - 2019-03-161130Americans-Crunch-
194 - 2019-03-171142Americans-Senators-



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
24 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
88,036$ 137,500$ 77,250$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 50,954$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 122 1,224$ 149,328$




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
132512110110066452114760100037251211550010029209276612218806242120164121019822765101363585321592415.09%1622187.04%040076552.29%40471956.19%18134252.92%688488518177300160
Total Saison Régulière2512110110066452114760100037251211550010029209276612218806242120164121019822765101363585321592415.09%1622187.04%040076552.29%40471956.19%18134252.92%688488518177300160
Séries
1216970000042366844000002320385300000191631842751170116111503581191191182349882113261081816.67%89989.89%022849046.53%20446344.06%9621844.04%410282362119199102
1216970000042366844000002320385300000191631842751170116111503581191191182349882113261081816.67%89989.89%022849046.53%20446344.06%9621844.04%410282362119199102
Total Séries3218140000084721216880000046406161060000038326368415023402322230071623823823646981764226522163616.67%1781889.89%045698046.53%40892644.06%19243644.04%820564724238399205