Americans

GP: 76 | W: 45 | L: 28 | OTL: 3 | P: 93
GF: 206 | GA: 137 | PP%: 16.56% | PK%: 87.52%
DG: Frederic Goldstyn | Morale : 70 | Moyenne d'Équipe : 59
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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
1Anton SlepyshevX99.00875560777771657250666771557870180670
2Brandon PirriX99.00655574848078786550606560557774181660
3John QuennevilleX100.00595563807669696250606060555050181610
4Justin Kloos (R)X100.00655573716269766050606260555050181600
5Taylor BeckX100.00605569667869696050606161555556181600
6Cameron DarcyX100.00755565627767665550555555557166178580
7Eric Cornel (R)X100.00565565627770715550555555557266180580
8Conner Bleackley (R)X100.00565566627367685550555555557371180580
9Shane HarperX100.00605559726866625850575859555050179580
10Deven Sideroff (R)X100.00565555555657575550555555557573180550
11Devin Setoguchi (R)X100.00555555555555555550555555557171131540
12Chase Lang (R)X100.00565555555758585550555555556568131540
13Kyle QuinceyX100.00725561738875816725636069558578175690
14Casey NelsonX100.00755588757284617225636577557271171690
15Kevin GravelX100.00705575707075647025626067555353181640
16Calle Rosen (R)X100.00605562755872726425616062556262180620
17Justin HollX100.00605569636281686525606562555353180600
18Reece ScarlettX100.00555557605757645725575757555353132550
Rayé
1Erik CondraX100.00565555555657575550555555557173120540
2Greg CareyX100.00565555555657565550555555557150119530
3Julius Nattinen (R)X100.00565555555556555550555555555050120520
4Vaclav Karabacek (R)X100.00565555555555555550555555555050120520
5Yakov Trenin (R)X100.00565555555555555550555555555050120520
6Robbie RussoX100.00555555605555755525555555555353119540
7Jyrki JokipakkaX100.00555555605555555525555555556262120540
8Vojtech MozikX100.00555555605555675525555555555353120540
9Blake Siebenaler (R)X100.00555555605555645525555555555353120540
MOYENNE D'ÉQUIPE99.9361556264646465594158585955626015458
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
1Eddie Lack100.0075717076808066657279557977171720
2Marek Mazanec100.0071808776686873667070557169174700
Rayé
1Charlie Lindgren100.0066706772707071687071556967145670
2Alexandar Georgiev (R)100.0072666366806455718072556060119660
MOYENNE D'ÉQUIPE100.007172727375716668737355706815269
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
1Anton SlepyshevAmericans (Buf)LW712630561812002751912405614410.83%14161822.797111853311000143566252.25%80000010.6903000753
2Brandon PirriAmericans (Buf)C7620365632220351451864811810.75%15169922.376152148344000104396154.57%148800000.6613000355
3Casey NelsonAmericans (Buf)D6212415325795937814354758.39%63148523.97111324972850000311200.00%000000.7100001443
4Kevin GravelAmericans (Buf)D76123648226751087212255659.84%64169022.2571320863390000367210.00%000000.5700001540
5John QuennevilleAmericans (Buf)C7615324714540105147181521328.29%7148619.56218204834701152481249.74%136900000.6301000126
6Calle RosenAmericans (Buf)D7611304111134201208184285213.10%50134017.647916451700001166400.00%000000.6100012351
7Justin HollAmericans (Buf)D76102131169351197167214814.93%50132717.47167261110110214200.00%000000.4700010224
8Kyle QuinceyAmericans (Buf)D6652530812801747711733944.27%53145922.1141216902910001307100.00%000000.4100000010
9Shane HarperAmericans (Buf)RW76161127196210924797387916.49%2120415.8454930346000002040.00%7500000.4500010122
10Justin KloosAmericans (Buf)C76917261654108112212032857.50%996412.700005190001694051.10%77100000.5411101512
11Taylor BeckAmericans (Buf)LW76714218400687210540776.67%9110214.5112368300011512058.55%15200000.3801000033
12Deven SideroffAmericans (Buf)RW763691661590175318315.66%6101713.3912310149000000064.86%7400000.1800000001
13Eric CornelAmericans (Buf)C73617324016243351718.18%24335.941125280000371049.73%18700000.3200000021
14Reece ScarlettAmericans (Buf)D3624673754812133315.38%1336810.2410135000042010.00%000000.3300100001
15Conner BleackleyAmericans (Buf)C7105512015111510130.00%23164.450224250001190066.67%4200000.3200000000
16Cameron DarcyAmericans (Buf)C6322442753432245188.33%12814.47000010000210057.14%20300000.2800001100
17Vojtech MozikAmericans (Buf)D11134116010340225.00%816114.6900000000128000.00%000000.4900000100
18Devin SetoguchiAmericans (Buf)RW321121120259207145.00%23079.6200023000000057.14%1400000.1300000010
19Chase LangAmericans (Buf)RW3010134048431825.00%11775.9200001000000041.67%1200000.1100000001
20Jyrki JokipakkaAmericans (Buf)D5011220721110.00%17815.6100006000011000.00%000000.2600000000
21Greg CareyAmericans (Buf)C3000-100230020.00%0175.80000000000000100.00%100000.0000000000
22Robbie RussoAmericans (Buf)D7000000100000.00%330.460000000003000.00%000000.0000000000
Stats d'équipe Total ou en Moyenne121415931647522610387015221224162950910889.76%3751854415.2854108162558287302235279733752.49%518800010.5129236333733
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
1Eddie LackAmericans (Buf)51371310.9151.723041288710280100.88927516653
2Marek MazanecAmericans (Buf)54321730.9171.6131230158410100300.00025333653
3Alexandar GeorgievAmericans (Buf)1511400.9152.2187022323760300.0000150101
4Charlie LindgrenAmericans (Buf)30100.9720.6592001360000.0000043000
Stats d'équipe Total ou en Moyenne123803540.9171.72712942520424500700.828291198213107


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
Eddie LackAmericans (Buf)G291988-01-05No187 Lbs6 ft4NoNoNo1Sans RestrictionPro & Farm1,000,000$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
Marek MazanecAmericans (Buf)G251991-07-18No187 Lbs6 ft4NoNoNo2Avec RestrictionPro & Farm300,000$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
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
3123.39191 Lbs6 ft12.74398,387$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Anton SlepyshevBrandon PirriShane Harper40122
2Taylor BeckJohn QuennevilleDeven Sideroff30122
3Eric CornelJustin KloosDevin Setoguchi20122
4Conner BleackleyCameron DarcyChase Lang10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Kyle QuinceyCasey Nelson40122
2Kevin GravelCalle Rosen30122
3Justin HollReece Scarlett20122
4Kyle QuinceyCasey Nelson10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Anton SlepyshevBrandon PirriShane Harper60122
2Taylor BeckJohn QuennevilleDeven Sideroff40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Kyle QuinceyCasey Nelson60122
2Kevin GravelCalle Rosen40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Anton SlepyshevBrandon Pirri60122
2John QuennevilleTaylor Beck40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Kyle QuinceyCasey Nelson60122
2Kevin GravelCalle Rosen40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Anton Slepyshev60122Kyle QuinceyCasey Nelson60122
2Brandon Pirri40122Kevin GravelCalle Rosen40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Anton SlepyshevBrandon Pirri60122
2John QuennevilleTaylor Beck40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Kyle QuinceyCasey Nelson60122
2Kevin GravelCalle Rosen40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Anton SlepyshevBrandon PirriShane HarperKyle QuinceyCasey Nelson
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Anton SlepyshevBrandon PirriShane HarperKyle QuinceyCasey Nelson
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Eric Cornel, Conner Bleackley, Justin KloosEric Cornel, Conner BleackleyJustin Kloos
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Justin Holl, Reece Scarlett, Kevin GravelJustin HollReece Scarlett, Kevin Gravel
Tirs de Pénalité
Anton Slepyshev, Brandon Pirri, John Quenneville, Taylor Beck, Justin Kloos
Gardien
#1 : Eddie Lack, #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
1Bears211000004311010000013-21100000030320.500471101767155448622625633284111285119421.05%13192.31%01224233952.33%1157215453.71%546103952.55%207614761604531906481
2Bruins2020000004-41010000003-31010000001-100.0000000076715543862262563328371430311300.00%14285.71%01224233952.33%1157215453.71%546103952.55%207614761604531906481
3Checkers440000002471722000000123922000000124881.0002442660076715541656226256332870134611210220.00%160100.00%01224233952.33%1157215453.71%546103952.55%207614761604531906481
4Comets10730000030131755000000172155230000013112140.7003053830476715542446226256332820245161204681319.12%771185.71%01224233952.33%1157215453.71%546103952.55%207614761604531906481
5Crunch1238001002132-1161400100613-7624000001519-470.2922138590076715542616226256332825978174242821012.20%791284.81%01224233952.33%1157215453.71%546103952.55%207614761604531906481
6Devils10530100123167532000001183521010011284130.650234366027671554221622625633282116116919751815.69%77988.31%01224233952.33%1157215453.71%546103952.55%207614761604531906481
7Marlies6500100025817320010001028330000001569121.00025497402767155422362262563328117407516019315.79%33390.91%01224233952.33%1157215453.71%546103952.55%207614761604531906481
8Monsters825000101618-24120001086241300000812-460.375162541017671554141622625633281875118621745817.78%80988.75%01224233952.33%1157215453.71%546103952.55%207614761604531906481
9Penguins2020000027-51010000014-31010000013-200.0002460076715543162262563328401542346116.67%14471.43%01224233952.33%1157215453.71%546103952.55%207614761604531906481
10Phantoms211000004311010000001-11100000042220.50048120076715544262262563328501428471200.00%13284.62%11224233952.33%1157215453.71%546103952.55%207614761604531906481
11Rocket430000101248210000105322200000071681.0001218300276715541016226256332885226510024520.83%29293.10%01224233952.33%1157215453.71%546103952.55%207614761604531906481
12Senators422000001073211000005232110000055040.50010192901767155499622625633286815608837718.92%24483.33%01224233952.33%1157215453.71%546103952.55%207614761604531906481
13Sound Tigers42100100963220000006152010010035-250.6259152401767155496622625633286725547330620.00%26388.46%01224233952.33%1157215453.71%546103952.55%207614761604531906481
14Thunderbirds220000001156110000004221100000073441.0001120310076715547062262563328449224311436.36%110100.00%01224233952.33%1157215453.71%546103952.55%207614761604531906481
Total764128022212061376938211301120955441382015011011118328930.61220636857401576715541899622625633281525428117516834537516.56%5216587.52%11224233952.33%1157215453.71%546103952.55%207614761604531906481
16Wolf Pack4400000015411220000009182200000063381.000152742017671554119622625633284715358426415.38%15380.00%01224233952.33%1157215453.71%546103952.55%207614761604531906481
_Since Last GM Reset764128022212061376938211301120955441382015011011118328930.61220636857401576715541899622625633281525428117516834537516.56%5216587.52%11224233952.33%1157215453.71%546103952.55%207614761604531906481
_Vs Conference2621301010102376513110010104812361310300000542529460.885102182284087671554803622625633285181293696191322720.45%1661690.36%01224233952.33%1157215453.71%546103952.55%207614761604531906481

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
7693W12063685741899152542811751683015
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
7641282221206137
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
38211311209554
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
382015110111183
Derniers 10 Matchs
WLOTWOTL SOWSOL
351010
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
4537516.56%5216587.52%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
622625633287671554
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
1224233952.33%1157215453.71%546103952.55%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
207614761604531906481


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 - 2019-01-15757Americans2Monsters3LSommaire du Match
136 - 2019-01-18774Crunch1Americans2WSommaire du Match
137 - 2019-01-19782Americans3Crunch5LSommaire du Match
138 - 2019-01-20797Devils3Americans1LSommaire du Match
141 - 2019-01-23811Monsters2Americans1LSommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
143 - 2019-01-25818Americans0Comets2LSommaire du Match
144 - 2019-01-26834Senators2Americans1LSommaire du Match
148 - 2019-01-30852Americans2Comets3LSommaire du Match
151 - 2019-02-02871Americans4Crunch2WSommaire du Match
152 - 2019-02-03884Crunch2Americans1LXSommaire du Match
157 - 2019-02-08904Sound Tigers1Americans3WSommaire du Match
158 - 2019-02-09916Americans1Devils2LXXSommaire du Match
159 - 2019-02-10926Devils2Americans4WSommaire du Match
162 - 2019-02-13938Comets0Americans3WSommaire du Match
164 - 2019-02-15946Americans6Checkers2WSommaire du Match
165 - 2019-02-16955Americans6Checkers2WSommaire du Match
171 - 2019-02-22988Monsters2Americans3WXXSommaire du Match
172 - 2019-02-23994Americans4Marlies1WSommaire du Match
173 - 2019-02-241011Americans7Marlies2WSommaire du Match
176 - 2019-02-271021Phantoms1Americans0LSommaire du Match
178 - 2019-03-011032Rocket3Americans4WXXSommaire du Match
179 - 2019-03-021048Americans4Devils3WXSommaire du Match
185 - 2019-03-081077Crunch3Americans0LSommaire du Match
186 - 2019-03-091089Americans3Crunch1WSommaire du Match
188 - 2019-03-111104Americans1Monsters4LSommaire du Match
192 - 2019-03-151121Devils1Americans0LSommaire du Match
193 - 2019-03-161130Americans1Crunch2LSommaire du Match
194 - 2019-03-171142Americans3Senators2WSommaire du Match



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
0 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
234,236$ 123,500$ 127,250$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 134,273$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 0 1,152$ 0$




LigueDomicileVisiteur
Année GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff P G A TP SO EG GP1 GP2 GP3 GP4 SHF SH1 SP2 SP3 SP4 SHA SHB Pim Hit PPA PPG PP% PKA PK GA PK% PK GF W OF FO T OF FO OF FO% W DF FO T DF FO DF FO% W NT FO T NT FO NT FO% PZ DF PZ OF PZ NT PC DF PC OF PC NT
137641280222120613769382113011209554413820150110111183289320636857401576715541899622625633281525428117516834537516.56%5216587.52%11224233952.33%1157215453.71%546103952.55%207614761604531906481
Total Saison Régulière7641280222120613769382113011209554413820150110111183289320636857401576715541899622625633281525428117516834537516.56%5216587.52%11224233952.33%1157215453.71%546103952.55%207614761604531906481
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