Americans

GP: 48 | W: 31 | L: 16 | OTL: 1 | P: 63
GF: 136 | GA: 78 | PP%: 17.07% | PK%: 87.58%
DG: Frederic Goldstyn | Morale : 69 | Moyenne d'Équipe : 60
Prochain matchs #757 vs Monsters
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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 SP
1Lee StempniakXX100.00945587808686867258666585558784147730
2Anton SlepyshevX100.00875560777771657250666771557870176670
3Brandon PirriX100.00655574848078786550606560557774180660
4John QuennevilleX100.00595563807669696250606060555050180610
5Justin Kloos (R)X100.00655573716269766050606260555050181600
6Zach SanfordX100.00605574747465646050606159555050182600
7Taylor BeckX100.00605569667869696050606161555556180600
8Cameron DarcyX100.00755565627767665550555555557166170580
9Eric Cornel (R)X100.00565565627770715550555555557266176580
10Conner Bleackley (R)X100.00565566627367685550555555557371176580
11Shane HarperX100.00605559726866625850575859555050180580
12Deven Sideroff (R)X100.00565555555657575550555555557573180550
13Casey NelsonX100.00755588757284617225636577557271180690
14Kevin GravelX100.00705575707075647025626067555353180640
15Calle Rosen (R)X100.00605562755872726425616062556262180620
16Justin HollX100.00605569636281686525606562555353177600
17Jyrki JokipakkaX100.00555555605555555525555555556262123540
Rayé
1Devin Setoguchi (R)X100.00555555555555555550555555557171120540
2Erik CondraX100.00565555555657575550555555557173120540
3Chase Lang (R)X100.00565555555758585550555555556568119540
4Greg CareyX100.00565555555657565550555555557150119530
5Julius Nattinen (R)X100.00565555555556555550555555555050120520
6Vaclav Karabacek (R)X100.00565555555555555550555555555050120520
7Yakov Trenin (R)X100.00565555555555555550555555555050120520
8Kyle QuinceyX100.00725561738875816725636069558578166690
9Reece ScarlettX100.00555557605757645725575757555353120550
10Robbie RussoX100.00555555605555755525555555555353120540
11Vojtech MozikX100.00555555605555675525555555555353120540
12Blake Siebenaler (R)X100.00555555605555645525555555555353120540
MOYENNE D'ÉQUIPE100.0062556365666565604258586055636115359
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
1Peter Budaj100.0080757771807577727577558787133740
2Marek Mazanec100.0071808776686873667070557169166690
Rayé
1Charlie Lindgren100.0066706772707071687071556967173680
2Alexandar Georgiev (R)100.0072666366806455718072556060119660
MOYENNE D'ÉQUIPE100.007273747175696969747355727114869
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)D48123345297157564112435310.71%46114223.81111021772260000229200.00%000000.7900001443
2Brandon PirriAmericans (Buf)C4812253725180259194357712.77%12109322.7819102222100052623055.30%95300000.6800000233
3Anton SlepyshevAmericans (Buf)LW4314193313720157109139358810.07%598422.8938113519100092024153.54%45200000.6700000532
4John QuennevilleAmericans (Buf)C48824321532068919625748.33%396020.01213152222201121541251.38%83500000.6700000124
5Zach SanfordAmericans (Buf)LW48161127134515404489195917.98%381016.896713241890000683059.74%7700010.6700102213
6Kevin GravelAmericans (Buf)D48717241540055457334369.59%32104521.793710532120000217100.00%000000.4600000220
7Kyle QuinceyAmericans (Buf)D413192211740104427625563.95%4087321.3031013591790000179000.00%000000.5000000010
8Justin KloosAmericans (Buf)C48613191431560727719527.79%662913.120005190000354052.32%49500000.6000100411
9Justin HollAmericans (Buf)D48712198515674032112421.87%2982317.150337450110130100.00%000000.4600010102
10Calle RosenAmericans (Buf)D48413175600784735142311.43%2775015.632131256000039200.00%000000.4500000220
11Shane HarperAmericans (Buf)RW481071713420803072255213.89%179916.6622423225000001039.13%4600000.4300000111
12Taylor BeckAmericans (Buf)LW4838111222033426424484.69%566113.790001290000701056.98%8600000.3300000021
13Lee StempniakAmericans (Buf)LW/RW5314-11208162272413.64%113426.971015240000242055.36%5600000.5900000001
14Eric CornelAmericans (Buf)C454043100520153926.67%12325.171013130000261050.00%16000000.3400000011
15Deven SideroffAmericans (Buf)RW4821315260408229179.09%460412.59000130000000057.89%3800000.1000000001
16Conner BleackleyAmericans (Buf)C430330201174560.00%11533.58011113000050064.29%1400000.3900000000
17Jyrki JokipakkaAmericans (Buf)D5011220721110.00%17815.6100006000011000.00%000000.2600000000
18Cameron DarcyAmericans (Buf)C350001135775120.00%01022.92000010000210055.71%7000000.0000001000
19Devin SetoguchiAmericans (Buf)RW7000000102130.00%0355.02000100000000100.00%100000.0000000000
20Greg CareyAmericans (Buf)C3000-100230020.00%0175.80000000000000100.00%100000.0000000000
21Chase LangAmericans (Buf)RW5000-100220030.00%0183.6700001000000033.33%300000.0000000000
22Robbie RussoAmericans (Buf)D7000000100000.00%330.460000000003000.00%000000.0000000000
23Reece ScarlettAmericans (Buf)D11000000000000.00%030.340000000001000.00%000000.0000000000
Stats d'équipe Total ou en Moyenne77811120731819162335926782103033670910.78%2201195815.373571106351190902216168426353.36%328700010.5300214242323
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)44281310.9181.602517014678150300.0000435553
2Alexandar GeorgievAmericans (Buf)1511400.9152.2187022323760300.0000150101
3Peter BudajAmericans (Buf)53200.8922.212720010930100.000050001
4Charlie LindgrenAmericans (Buf)30100.9720.6592001360000.0000043000
Stats d'équipe Total ou en Moyenne67422010.9171.76375321611013200700.00006348655


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 Link
Alexandar GeorgievAmericans (Buf)G201996-02-10Yes176 Lbs6 ft1NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No
Anton SlepyshevAmericans (Buf)LW221994-05-13No194 Lbs6 ft2NoNoNo2Contrat d'EntréePro & Farm300,000$0$0$No
Blake SiebenalerAmericans (Buf)D201996-02-27Yes208 Lbs6 ft1NoNoNo3Contrat d'EntréePro & Farm300,000$0$0$No
Brandon PirriAmericans (Buf)C251991-04-09No183 Lbs6 ft0NoNoNo2Avec RestrictionPro & Farm500,000$0$0$No
Calle RosenAmericans (Buf)D221994-02-02Yes176 Lbs6 ft1NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No
Cameron DarcyAmericans (Buf)C221994-03-02No192 Lbs6 ft0NoNoNo2Contrat d'EntréePro & Farm300,000$0$0$No
Casey NelsonAmericans (Buf)D241992-07-18No183 Lbs6 ft2NoNoNo3Avec RestrictionPro & Farm300,000$0$0$No
Charlie LindgrenAmericans (Buf)G231993-12-17No181 Lbs6 ft1NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No
Chase LangAmericans (Buf)RW201996-09-13Yes187 Lbs6 ft1NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No
Conner BleackleyAmericans (Buf)C201996-02-07Yes192 Lbs6 ft0NoNoNo3Contrat d'EntréePro & Farm500,000$0$0$No
Deven SideroffAmericans (Buf)RW191997-04-14Yes179 Lbs6 ft0NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No
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$0$No
Erik CondraAmericans (Buf)RW301986-08-06No190 Lbs6 ft0NoNoNo3Sans RestrictionPro & Farm350,000$0$0$No
Greg CareyAmericans (Buf)C261990-05-09No195 Lbs6 ft0NoNoNo3Avec RestrictionPro & Farm300,000$0$0$No
John QuennevilleAmericans (Buf)C201996-04-16No195 Lbs6 ft1NoNoNo3Contrat d'EntréePro & Farm500,000$0$0$No
Julius NattinenAmericans (Buf)C191997-01-14Yes205 Lbs6 ft2NoNoNo4Contrat d'EntréePro & Farm500,000$0$0$No
Justin HollAmericans (Buf)D241992-01-30No170 Lbs6 ft2NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No
Justin KloosAmericans (Buf)C231993-11-30Yes179 Lbs5 ft9NoNoNo4Avec RestrictionPro & Farm300,000$0$0$No
Jyrki JokipakkaAmericans (Buf)D251991-08-20No210 Lbs6 ft3NoNoNo4Avec RestrictionPro & Farm300,000$0$0$No
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$0$No
Lee StempniakAmericans (Buf)LW/RW331983-02-04No196 Lbs5 ft11NoNoNo3Sans RestrictionPro & Farm3,150,000$0$0$No
Marek MazanecAmericans (Buf)G251991-07-18No187 Lbs6 ft4NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No
Peter BudajAmericans (Buf)G341982-09-17No192 Lbs6 ft1NoNoNo2Sans RestrictionPro & Farm1,920,000$0$0$No
Reece ScarlettAmericans (Buf)D231993-03-30No180 Lbs5 ft11NoNoNo3Avec RestrictionPro & Farm300,000$0$0$No
Robbie RussoAmericans (Buf)D231993-02-15No190 Lbs6 ft0NoNoNo4Avec RestrictionPro & Farm300,000$0$0$No
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$0$No
Vaclav KarabacekAmericans (Buf)RW201996-05-02Yes199 Lbs6 ft0NoNoNo3Contrat d'EntréePro & Farm500,000$0$0$No
Vojtech MozikAmericans (Buf)D241992-12-26No196 Lbs6 ft2NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No
Yakov TreninAmericans (Buf)C201997-01-13Yes205 Lbs6 ft2NoNoNo4Contrat d'EntréePro & Farm500,000$0$0$No
Zach SanfordAmericans (Buf)LW221994-11-09No192 Lbs6 ft4NoNoNo3Contrat d'EntréePro & Farm500,000$0$0$No
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
3323.79192 Lbs6 ft12.79512,727$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Lee StempniakBrandon PirriShane Harper40122
2Anton SlepyshevJohn QuennevilleDeven Sideroff30122
3Zach SanfordJustin KloosLee Stempniak20122
4Taylor BeckCameron DarcyAnton Slepyshev10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Casey NelsonKevin Gravel40122
2Calle RosenJustin Holl30122
3Jyrki JokipakkaCasey Nelson20122
4Kevin GravelCalle Rosen10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Lee StempniakBrandon PirriShane Harper60122
2Anton SlepyshevJohn QuennevilleDeven Sideroff40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Casey NelsonKevin Gravel60122
2Calle RosenJustin Holl40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Lee StempniakAnton Slepyshev60122
2Brandon PirriJohn Quenneville40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Casey NelsonKevin Gravel60122
2Calle RosenJustin Holl40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Lee Stempniak60122Casey NelsonKevin Gravel60122
2Anton Slepyshev40122Calle RosenJustin Holl40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Lee StempniakAnton Slepyshev60122
2Brandon PirriJohn Quenneville40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Casey NelsonKevin Gravel60122
2Calle RosenJustin Holl40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Lee StempniakBrandon PirriShane HarperCasey NelsonKevin Gravel
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Lee StempniakBrandon PirriShane HarperCasey NelsonKevin Gravel
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Eric Cornel, Conner Bleackley, Zach SanfordEric Cornel, Conner BleackleyZach Sanford
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Jyrki Jokipakka, Justin Holl, Casey NelsonJyrki JokipakkaJustin Holl, Casey Nelson
Tirs de Pénalité
Lee Stempniak, Anton Slepyshev, Brandon Pirri, John Quenneville, Zach Sanford
Gardien
#1 : Peter Budaj, #2 : Marek Mazanec


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
1Bears211000004311010000013-21100000030320.50047110147503814838138740264111285119421.05%13192.31%0762145252.48%743135454.87%35365653.81%1320939995333571307
2Bruins2020000004-41010000003-31010000001-100.000000004750381383813874026371430311300.00%14285.71%0762145252.48%743135454.87%35365653.81%1320939995333571307
3Checkers2200000012392200000012390000000000041.00012223400475038173381387402639926607228.57%80100.00%0762145252.48%743135454.87%35365653.81%1320939995333571307
4Comets76100000258174400000014212321000001165120.85725436803475038117838138740261373210713445920.00%51688.24%0762145252.48%743135454.87%35365653.81%1320939995333571307
5Crunch50500000716-93030000037-42020000049-500.0007142100475038110438138740261103570963326.06%35780.00%0762145252.48%743135454.87%35365653.81%1320939995333571307
6Devils541000001358220000006243210000073480.800132437024750381100381387402611625669728517.86%30293.33%0762145252.48%743135454.87%35365653.81%1320939995333571307
7Marlies4300100014593200100010281100000043181.0001427410247503811353813874026762542999111.11%20290.00%0762145252.48%743135454.87%35365653.81%1320939995333571307
8Monsters42200000972211000004222110000055040.500914230147503816538138740269222809527622.22%39489.74%0762145252.48%743135454.87%35365653.81%1320939995333571307
9Penguins2020000027-51010000014-31010000013-200.000246004750381313813874026401542346116.67%14471.43%0762145252.48%743135454.87%35365653.81%1320939995333571307
10Phantoms11000000422000000000001100000042221.00048120047503812038138740261981422600.00%6266.67%1762145252.48%743135454.87%35365653.81%1320939995333571307
11Rocket33000000817110000001012200000071661.000814220247503816938138740266318557617317.65%24195.83%0762145252.48%743135454.87%35365653.81%1320939995333571307
12Senators21100000633110000004041010000023-120.50061117014750381513813874026305263817423.53%13284.62%0762145252.48%743135454.87%35365653.81%1320939995333571307
13Sound Tigers31100100651110000003032010010035-230.50069150147503817538138740265320445623417.39%21385.71%0762145252.48%743135454.87%35365653.81%1320939995333571307
14Thunderbirds220000001156110000004221100000073441.000112031004750381703813874026449224311436.36%110100.00%0762145252.48%743135454.87%35365653.81%1320939995333571307
Total48301601100136785825177010007231412313900100644717630.65613624438001447503811176381387402694426368710162874917.07%3143987.58%1762145252.48%743135454.87%35365653.81%1320939995333571307
16Wolf Pack4400000015411220000009182200000063381.00015274201475038111938138740264715358426415.38%15380.00%0762145252.48%743135454.87%35365653.81%1320939995333571307
_Since Last GM Reset48301601100136785825177010007231412313900100644717630.65613624438001447503811176381387402694426368710162874917.07%3143987.58%1762145252.48%743135454.87%35365653.81%1320939995333571307
_Vs Conference181610100070224811100010004193276100000291316340.94470126196074750381525381387402635993252412891921.35%114992.11%0762145252.48%743135454.87%35365653.81%1320939995333571307

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
4863L113624438011769442636871016014
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
483016110013678
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
2517710007231
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
2313901006447
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
2874917.07%3143987.58%1
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
38138740264750381
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
762145252.48%743135454.87%35365653.81%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
1320939995333571307


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 - 2018-11-16395Monsters0Americans3WSommaire du Match
74 - 2018-11-17404Americans2Monsters3LSommaire du Match
78 - 2018-11-21430Senators0Americans4WSommaire du Match
80 - 2018-11-23437Wolf Pack0Americans4WSommaire du Match
81 - 2018-11-24453Wolf Pack1Americans5WSommaire du Match
85 - 2018-11-28465Americans3Monsters2WSommaire du Match
87 - 2018-11-30481Marlies0Americans5WSommaire du Match
88 - 2018-12-01490Americans4Comets1WSommaire du Match
92 - 2018-12-05512Sound Tigers0Americans3WSommaire du Match
94 - 2018-12-07524Americans4Rocket0WSommaire du Match
95 - 2018-12-08532Americans3Rocket1WSommaire du Match
101 - 2018-12-14568Marlies0Americans2WSommaire du Match
102 - 2018-12-15574Americans4Marlies3WSommaire du Match
108 - 2018-12-21608Americans1Penguins3LSommaire du Match
109 - 2018-12-22625Americans4Phantoms2WSommaire du Match
113 - 2018-12-26650Devils2Americans3WSommaire du Match
115 - 2018-12-28661Comets0Americans2WSommaire du Match
116 - 2018-12-29673Americans0Crunch4LSommaire du Match
122 - 2019-01-04689Americans3Devils1WSommaire du Match
123 - 2019-01-05701Americans4Wolf Pack2WSommaire du Match
127 - 2019-01-09719Crunch1Americans0LSommaire du Match
129 - 2019-01-11725Thunderbirds2Americans4WSommaire du Match
130 - 2019-01-12740Americans3Comets5LSommaire du Match
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
13 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
160,521$ 169,200$ 122,250$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 93,022$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 63 1,388$ 87,444$




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
13483016011001367858251770100072314123139001006447176313624438001447503811176381387402694426368710162874917.07%3143987.58%1762145252.48%743135454.87%35365653.81%1320939995333571307
Total Saison Régulière483016011001367858251770100072314123139001006447176313624438001447503811176381387402694426368710162874917.07%3143987.58%1762145252.48%743135454.87%35365653.81%1320939995333571307
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