Americans

GP: 43 | W: 28 | L: 12 | OTL: 3 | P: 59
GF: 109 | GA: 72 | PP%: 16.75% | PK%: 90.53%
DG: Frederic Goldstyn | Morale : 71 | Moyenne d'Équipe : 61
Prochain matchs #689 vs Devils
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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
1Greg CareyX100.005838866371949562656161586277695681640
2Drew StaffordXX100.007438886483727063586162596384744871630
3Brooks MacekXX100.005135936557928964706362576373675878630
4John QuennevilleXX100.006238856376766462716063626065647881610
5Sheldon DriesX100.006640796366726762686159655669655181610
6Erik CondraX100.005637876369847261535960565782764181610
7Sam Lafferty (R)XX100.006142756074939159706254575367646181610
8Cameron DarcyX100.005838855672939155565453575069656081590
9Justin KloosXX100.005236915964766958635957565571665181590
10Eric CornelX100.006437895579959654575452565365636281590
11Kailer Yamamoto (R)XX100.005636906359767162565761585761638281590
12Conner BleackleyX100.005938865573918654575452545365636281580
13Mikey EyssimontXX100.005538845570928954565353555465636281580
14Steven WhitneyX100.005337895561918754565253545175685723570
15Deven SideroffX100.005237895667777154635751525463626323560
16Casey NelsonX100.006443896274795361306658674973673776630
17Robbie RussoX100.005937885973939058306252564771666081620
18Calle RosenX100.005637886475876863306258575069655181620
19Blake SiebenalerX100.006636915579777153305251544565636281590
20Justin HollX100.005635935886735356305751524873676181580
Rayé
1Will BittenX100.005236915855928957605655535661636421580
MOYENNE D'ÉQUIPE100.00593887607185785854585657547066587260
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
1Charlie Lindgren100.00766664747574767574767571754781720
Rayé
1Marek Mazanec100.00727472847170727170727175814520710
MOYENNE D'ÉQUIPE100.0074706879737274737274737378465172
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Lindy Ruff75707166898357CAN5955,000,000$


Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du Joueur Nom de l'ÉquipePOSGP G A P +/- PIM PIM5 HIT HTT SHT OSB OSM SHT% SB MP AMG PPG PPA PPP PPS PPM PKG PKA PKP PKS PKM GW GT FO% FOT GA TA EG HT P/20 PSG PSS FW FL FT S1 S2 S3
1John QuennevilleAmericans (Buf)C/LW4312243612300539814031788.57%1286420.094913371720005974058.49%80700000.8304000325
2Brooks MacekAmericans (Buf)C/RW431221331118023105127321119.45%9110725.751893018011262010155.44%132400000.6026000516
3Greg CareyAmericans (Buf)LW4318927101354553115276215.65%1195122.1375123818110132084153.54%9900100.5706001551
4Calle RosenAmericans (Buf)D439182711220412874204312.16%4394221.913912451700112146220.00%000000.5700000212
5Erik CondraAmericans (Buf)RW4312132581402652102295611.76%475717.6234723172000042041.38%5800000.6612000151
6Casey NelsonAmericans (Buf)D43222248552543557320422.74%49102023.7311011401780111157000.00%000000.4700131003
7Robbie RussoAmericans (Buf)D435182310400613839173712.82%4296222.385510321720111152200.00%000000.4800000021
8Sam LaffertyAmericans (Buf)C/LW43614201037563307021628.57%775217.49371015172000034057.50%4000000.5300001121
9Drew StaffordAmericans (Buf)LW/RW39118198455944688176312.50%972318.55336191631015872058.20%12200000.5302001221
10Sheldon DriesAmericans (Buf)C435611-4380778010526754.76%862514.54000000002542051.53%55700000.3512000012
11Kailer YamamotoAmericans (Buf)C/RW43549-380213710628784.72%156613.1700019000000043.48%2300000.3200000002
12Justin HollAmericans (Buf)D430661140311415370.00%1961914.4100013000046000.00%000000.1900000000
13Cameron DarcyAmericans (Buf)C43044295122016560.00%41954.5400000000030058.29%18700000.4100001000
14Eric CornelAmericans (Buf)RW4322408017131761111.76%12074.8300000000000060.00%1000000.3900000000
15Blake SiebenalerAmericans (Buf)D4313403205310224134.55%2661814.3900017000036100.00%000000.1300000000
16Mikey EyssimontAmericans (Buf)C/LW43033-514021244919220.00%255813.0000000000000047.62%2100000.1100000000
17Justin KloosAmericans (Buf)C/RW43000100000010.00%0130.3200002000000050.00%400000.0000000000
18Conner BleackleyAmericans (Buf)C43000-200434270.00%1461.0800008000080050.00%2000000.0000000000
Stats d'équipe Total ou en Moyenne770100175275783974568570611623077748.61%2481153114.98306090282159734725120823455.35%327200100.48422135192125
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
1Charlie LindgrenAmericans (Buf)63200.9131.9134620111260000.0000543000
Stats d'équipe Total ou en Moyenne63200.9131.9134620111260000.0000543000


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 Cap Salariale Cap Salariale Restant Exclus du Cap Salarial Salaire Année 2Salaire Année 3Salaire Année 4Salaire Année 5Salaire Année 6Salaire Année 7Salaire Année 8Salaire Année 9Salaire Année 10Link
Blake SiebenalerAmericans (Buf)D231996-02-27No208 Lbs6 ft1NoNoNo2Pro & Farm300,000$0$0$No300,000$Lien
Brooks MacekAmericans (Buf)C/RW271992-05-15No180 Lbs5 ft1NoNoNo1Pro & Farm300,000$0$0$NoLien
Calle RosenAmericans (Buf)D251994-02-02No186 Lbs6 ft1NoNoNo3Pro & Farm300,000$0$0$No300,000$300,000$Lien
Cameron DarcyAmericans (Buf)C251994-03-02No190 Lbs6 ft0NoNoNo1Pro & Farm300,000$0$0$NoLien
Casey NelsonAmericans (Buf)D261992-07-18No185 Lbs6 ft1NoNoNo2Pro & Farm300,000$0$0$No300,000$Lien
Charlie LindgrenAmericans (Buf)G251993-12-18No182 Lbs6 ft1NoNoNo1Pro & Farm300,000$0$0$NoLien
Conner BleackleyAmericans (Buf)C231996-02-07No192 Lbs6 ft0NoNoNo2Pro & Farm500,000$0$0$No500,000$Lien
Deven SideroffAmericans (Buf)RW221997-04-14No171 Lbs5 ft11NoNoNo3Pro & Farm300,000$0$0$No300,000$300,000$Lien
Drew StaffordAmericans (Buf)LW/RW331985-10-30No215 Lbs6 ft2NoNoNo1Pro & Farm1,000,000$0$0$NoLien
Eric CornelAmericans (Buf)RW231996-04-11No195 Lbs6 ft2NoNoNo2Pro & Farm500,000$0$0$No500,000$Lien
Erik CondraAmericans (Buf)RW321986-08-06No185 Lbs5 ft11NoNoNo2Pro & Farm350,000$0$0$No350,000$Lien
Greg CareyAmericans (Buf)LW291990-04-05No204 Lbs5 ft10NoNoNo2Pro & Farm300,000$0$0$No300,000$Lien
John QuennevilleAmericans (Buf)C/LW231996-04-16No195 Lbs6 ft1NoNoNo2Pro & Farm500,000$0$0$No500,000$Lien
Justin HollAmericans (Buf)D271992-01-30No205 Lbs6 ft4NoNoNo1Pro & Farm300,000$0$0$NoLien
Justin KloosAmericans (Buf)C/RW251993-11-30No175 Lbs5 ft9NoNoNo3Pro & Farm300,000$0$0$No300,000$300,000$Lien
Kailer YamamotoAmericans (Buf)C/RW201998-09-29Yes153 Lbs5 ft8NoNoNo4Pro & Farm900,000$0$0$No900,000$900,000$900,000$Lien
Marek MazanecAmericans (Buf)G271991-07-18No187 Lbs6 ft4NoNoNo1Pro & Farm300,000$0$0$NoLien
Mikey EyssimontAmericans (Buf)C/LW221996-09-09No180 Lbs6 ft0NoNoNo4Pro & Farm300,000$0$0$No300,000$300,000$300,000$Lien
Robbie RussoAmericans (Buf)D261993-02-15No191 Lbs6 ft0NoNoNo3Pro & Farm300,000$0$0$No300,000$300,000$Lien
Sam LaffertyAmericans (Buf)C/LW241995-03-06Yes184 Lbs6 ft1NoNoNo4Pro & Farm300,000$0$0$No300,000$300,000$300,000$Lien
Sheldon DriesAmericans (Buf)C251994-04-23No185 Lbs5 ft9NoNoNo4Pro & Farm300,000$0$0$No300,000$300,000$300,000$Lien
Steven WhitneyAmericans (Buf)RW281991-02-18No168 Lbs5 ft7NoNoNo1Pro & Farm300,000$0$0$NoLien
Will BittenAmericans (Buf)RW201998-07-10No167 Lbs5 ft1NoNoNo4Pro & Farm500,000$0$0$No500,000$500,000$500,000$Lien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2325.22186 Lbs5 ft112.30393,478$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Greg CareyBrooks MacekDrew Stafford40122
2Sam LaffertyJohn QuennevilleErik Condra30122
3Mikey EyssimontSheldon DriesKailer Yamamoto20122
4Brooks MacekCameron DarcyEric Cornel10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Casey Nelson40122
2Robbie RussoCalle Rosen30122
3Blake SiebenalerJustin Holl20122
4Casey Nelson10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Greg CareyBrooks MacekDrew Stafford60122
2Sam LaffertyJohn QuennevilleErik Condra40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Casey Nelson60122
2Robbie RussoCalle Rosen40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Brooks MacekGreg Carey60122
2Drew StaffordJohn Quenneville40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Casey Nelson60122
2Robbie RussoCalle Rosen40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Brooks Macek60122Casey Nelson60122
2Greg Carey40122Robbie RussoCalle Rosen40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Brooks MacekGreg Carey60122
2Drew StaffordJohn Quenneville40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Casey Nelson60122
2Robbie RussoCalle Rosen40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Greg CareyBrooks MacekDrew StaffordCasey Nelson
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Greg CareyBrooks MacekDrew StaffordCasey Nelson
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Conner Bleackley, Justin Kloos, Sheldon DriesConner Bleackley, Justin KloosSheldon Dries
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Blake Siebenaler, Justin Holl, Robbie RussoBlake SiebenalerJustin Holl, Robbie Russo
Tirs de Pénalité
Brooks Macek, Greg Carey, Drew Stafford, John Quenneville, Sheldon Dries
Gardien
#1 : , #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
1Bears2110000013-2110000001011010000003-320.500123015223295664253634363135810351200.00%40100.00%0823145856.45%670122654.65%31856356.48%1161836931302520270
2Bruins21100000330110000001011010000023-120.5003690152232954542536343631611627388225.00%10190.00%0823145856.45%670122654.65%31856356.48%1161836931302520270
3Checkers22000000927220000009270000000000041.000916250152232951014253634363133812296350.00%50100.00%0823145856.45%670122654.65%31856356.48%1161836931302520270
4Comets64100010189942100010138522000000514100.8331832500152232951764253634363190385910330516.67%24387.50%0823145856.45%670122654.65%31856356.48%1161836931302520270
5Crunch421000101385210000106332110000075260.7501321340052232951214253634363110332427626623.08%17476.47%0823145856.45%670122654.65%31856356.48%1161836931302520270
6Devils4020100136-32010100012-12010000124-230.3753580152232957642536343631933736762015.00%180100.00%0823145856.45%670122654.65%31856356.48%1161836931302520270
7Marlies440000002151633000000164121100000051481.000213758005223295185425363436318523328113323.08%16193.75%2823145856.45%670122654.65%31856356.48%1161836931302520270
8Monsters412000101113-22020000049-52100001074340.5001119301052232951094253634363110339417716425.00%17288.24%1823145856.45%670122654.65%31856356.48%1161836931302520270
9Penguins22000000624110000002021100000042241.00061117015223295594253634363140719371417.14%60100.00%0823145856.45%670122654.65%31856356.48%1161836931302520270
10Phantoms1010000013-2000000000001010000013-200.000123005223295184253634363118229186116.67%5260.00%0823145856.45%670122654.65%31856356.48%1161836931302520270
11Rocket32100000651110000003122110000034-140.6676101600522329582425363436316619484816318.75%21290.48%0823145856.45%670122654.65%31856356.48%1161836931302520270
12Senators211000003301010000013-21100000020220.50036901522329536425363436312982529700.00%10190.00%0823145856.45%670122654.65%31856356.48%1161836931302520270
13Sound Tigers3110010034-11000010023-12110000011030.5003580152232956642536343631621533601616.25%14192.86%0823145856.45%670122654.65%31856356.48%1161836931302520270
14Thunderbirds11000000202000000000001100000020221.000246015223295234253634363122912176233.33%60100.00%0823145856.45%670122654.65%31856356.48%1161836931302520270
Total4323120114210972372313501130663828201070001243349590.6861091923011952232951232425363436319302854667862093516.75%1901890.53%3823145856.45%670122654.65%31856356.48%1161836931302520270
16Wolf Pack31000011963210000107341000000123-150.8339162500522329569425363436319024416213323.08%17194.12%0823145856.45%670122654.65%31856356.48%1161836931302520270
_Since Last GM Reset4323120114210972372313501130663828201070001243349590.6861091923011952232951232425363436319302854667862093516.75%1901890.53%3823145856.45%670122654.65%31856356.48%1161836931302520270
_Vs Conference1613200010562135108100010411526651000001569280.87556991550352232955674253634363129697163278711622.54%72691.67%2823145856.45%670122654.65%31856356.48%1161836931302520270

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
4359W2109192301123293028546678619
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
432312114210972
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
2313511306638
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
2010700124334
Derniers 10 Matchs
WLOTWOTL SOWSOL
630100
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
2093516.75%1901890.53%3
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
425363436315223295
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
823145856.45%670122654.65%31856356.48%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
1161836931302520270


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 - 2019-09-043Checkers0Americans6WSommaire du Match
4 - 2019-09-0515Checkers2Americans3WSommaire du Match
8 - 2019-09-0930Crunch1Americans3WSommaire du Match
11 - 2019-09-1243Americans1Sound Tigers0WSommaire du Match
12 - 2019-09-1358Americans0Sound Tigers1LSommaire du Match
15 - 2019-09-1663Americans4Comets1WSommaire du Match
17 - 2019-09-1874Marlies1Americans4WSommaire du Match
18 - 2019-09-1986Americans2Senators0WSommaire du Match
24 - 2019-09-25111Comets2Americans3WSommaire du Match
25 - 2019-09-26125Rocket1Americans3WSommaire du Match
31 - 2019-10-02145Bears0Americans1WSommaire du Match
32 - 2019-10-03156Americans0Bears3LSommaire du Match
36 - 2019-10-07177Monsters4Americans2LSommaire du Match
38 - 2019-10-09187Crunch2Americans3WXXSommaire du Match
45 - 2019-10-16229Americans2Thunderbirds0WSommaire du Match
46 - 2019-10-17245Americans2Bruins3LSommaire du Match
47 - 2019-10-18249Americans2Wolf Pack3LXXSommaire du Match
52 - 2019-10-23270Comets2Americans3WXXSommaire du Match
53 - 2019-10-24284Americans1Devils2LXXSommaire du Match
59 - 2019-10-30312Penguins0Americans2WSommaire du Match
60 - 2019-10-31327Americans1Devils2LSommaire du Match
64 - 2019-11-04344Comets3Americans2LSommaire du Match
66 - 2019-11-06353Bruins0Americans1WSommaire du Match
67 - 2019-11-07366Americans2Crunch3LSommaire du Match
71 - 2019-11-11386Devils0Americans1WXSommaire du Match
73 - 2019-11-13395Monsters5Americans2LSommaire du Match
74 - 2019-11-14404Americans3Monsters2WXXSommaire du Match
78 - 2019-11-18430Senators3Americans1LSommaire du Match
80 - 2019-11-20437Wolf Pack2Americans3WXXSommaire du Match
81 - 2019-11-21453Wolf Pack1Americans4WSommaire du Match
85 - 2019-11-25465Americans4Monsters2WSommaire du Match
87 - 2019-11-27481Marlies1Americans5WSommaire du Match
88 - 2019-11-28490Americans1Comets0WSommaire du Match
92 - 2019-12-02512Sound Tigers3Americans2LXSommaire du Match
94 - 2019-12-04524Americans1Rocket3LSommaire du Match
95 - 2019-12-05532Americans2Rocket1WSommaire du Match
101 - 2019-12-11568Marlies2Americans7WSommaire du Match
102 - 2019-12-12574Americans5Marlies1WSommaire du Match
108 - 2019-12-18608Americans4Penguins2WSommaire du Match
109 - 2019-12-19625Americans1Phantoms3LSommaire du Match
113 - 2019-12-23650Devils2Americans0LSommaire du Match
115 - 2019-12-25661Comets1Americans5WSommaire du Match
116 - 2019-12-26673Americans5Crunch2WSommaire du Match
122 - 2020-01-01689Americans-Devils-
123 - 2020-01-02701Americans-Wolf Pack-
127 - 2020-01-06719Crunch-Americans-
129 - 2020-01-08725Thunderbirds-Americans-
130 - 2020-01-09740Americans-Comets-
133 - 2020-01-12757Americans-Monsters-
136 - 2020-01-15774Crunch-Americans-
137 - 2020-01-16782Americans-Crunch-
138 - 2020-01-17797Devils-Americans-
141 - 2020-01-20811Monsters-Americans-
143 - 2020-01-22818Americans-Comets-
144 - 2020-01-23834Senators-Americans-
148 - 2020-01-27852Americans-Comets-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
151 - 2020-01-30871Americans-Crunch-
152 - 2020-01-31884Crunch-Americans-
157 - 2020-02-05904Sound Tigers-Americans-
158 - 2020-02-06916Americans-Devils-
159 - 2020-02-07926Devils-Americans-
162 - 2020-02-10938Comets-Americans-
164 - 2020-02-12946Americans-Checkers-
165 - 2020-02-13955Americans-Checkers-
171 - 2020-02-19988Monsters-Americans-
172 - 2020-02-20994Americans-Marlies-
173 - 2020-02-211011Americans-Marlies-
176 - 2020-02-241021Phantoms-Americans-
178 - 2020-02-261032Rocket-Americans-
179 - 2020-02-271048Americans-Devils-
185 - 2020-03-041077Crunch-Americans-
186 - 2020-03-051089Americans-Crunch-
188 - 2020-03-071104Americans-Monsters-
192 - 2020-03-111121Devils-Americans-
193 - 2020-03-121130Americans-Crunch-
194 - 2020-03-131142Americans-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
15 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
3,143,000$ 90,500$ 50,750$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 75,906$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 75 26,240$ 1,968,000$




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
144323120114210972372313501130663828201070001243349591091923011952232951232425363436319302854667862093516.75%1901890.53%3823145856.45%670122654.65%31856356.48%1161836931302520270
Total Saison Régulière4323120114210972372313501130663828201070001243349591091923011952232951232425363436319302854667862093516.75%1901890.53%3823145856.45%670122654.65%31856356.48%1161836931302520270