Americans

GP: 76 | W: 50 | L: 19 | OTL: 7 | P: 107
GF: 201 | GA: 128 | PP%: 15.82% | PK%: 88.44%
DG: Frederic Goldstyn | Morale : 83 | Moyenne d'Équipe : 61
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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 CareyX100.005838866371949562656161586277695685640
2Drew StaffordXX100.007438886483727063586162596384744883630
3John QuennevilleXX100.006238856376766462716063626065647885620
4Sheldon DriesX100.006640796366726762686159655669655181610
5Erik CondraX100.005637876369847261535960565782764185610
6Sam Lafferty (R)XX100.006142756074939159706254575367646184610
7Eric CornelX100.006437895579959654575452565365636285600
8Cameron DarcyX100.005838855672939155565453575069656085590
9Justin KloosXX100.005236915964766958635957565571665185590
10Kailer Yamamoto (R)XX100.005636906359767162565761585761638285590
11Conner BleackleyX100.005938865573918654575452545365636285580
12Mikey EyssimontXX100.005538845570928954565353555465636285580
13Will BittenX100.005236915855928957605655535661636422580
14Steven WhitneyX100.005337895561918754565253545175685722570
15Deven SideroffX100.005237895667777154635751525463626322560
16Casey NelsonX100.006443896274795361306658674973673784630
17Robbie RussoX100.005937885973939058306252564771666085620
18Calle RosenX100.005637886475876863306258575069655187620
19Blake SiebenalerX100.006636915579777153305251544565636287590
20Justin HollX100.005635935886735356305751524873676185580
Rayé
MOYENNE D'ÉQUIPE100.00593887597184775853585657547066587560
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 Lindgren100.00766664747574767574767571754784720
2Marek Mazanec100.00727472847170727170727175814522710
Rayé
MOYENNE D'ÉQUIPE100.0074706879737274737274737378465372
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/LW7625386320380811832496315210.04%17149219.641115267732700051216058.02%146500000.8404000449
2Greg CareyAmericans (Buf)LW7623305327255711202114812410.90%21180523.75812206533310173364154.50%42200100.5909001682
3Casey NelsonAmericans (Buf)D761240521490309910514241868.45%105189124.8941721853231123247510.00%000000.5500132415
4Calle RosenAmericans (Buf)D76143650215158455114337312.28%81177623.3761420703240222235620.00%000000.5600100415
5Drew StaffordAmericans (Buf)LW/RW72242044247810134921763712713.64%18138619.26371040313101101884451.69%17800000.6305002473
6Erik CondraAmericans (Buf)RW76192544172604684195531099.74%11142518.7641014433290001604144.33%9700000.6213000252
7Robbie RussoAmericans (Buf)D7673138286401107068296710.29%69185024.3571118523160111251300.00%000000.4100000142
8Sam LaffertyAmericans (Buf)C/LW7611263718651511861139391047.91%12135617.856111733329000054157.33%7500000.5500012152
9Brooks MacekBuffalo SabresC/RW4414213513180231071363511510.29%9113225.731893118311272090155.39%135400000.6226000616
10Sheldon DriesAmericans (Buf)C7615173210775125152188521267.98%15121516.006282714510131064253.50%127300000.5325010313
11Cameron DarcyAmericans (Buf)C7631417627531706322414.76%56198.1500015000070053.76%54500000.5500001121
12Justin HollAmericans (Buf)D7611516113405122245174.17%36113915.00022434011193000.00%000000.2800000000
13Blake SiebenalerAmericans (Buf)D7649131669510520439229.30%53137618.12123101480000124200.00%000000.1900100101
14Kailer YamamotoAmericans (Buf)C/RW766612-1120325212040985.00%47439.7800019000000049.23%19500000.3200000002
15Justin KloosAmericans (Buf)C/RW7665115808326814438.82%64996.58000280110502057.14%5600000.4400000022
16Mikey EyssimontAmericans (Buf)C/LW764610-320046459036464.44%598012.9000011000001046.34%4100000.2000000012
17Eric CornelAmericans (Buf)RW76426412025182771514.81%23744.9200000000000064.71%1700000.3200000000
18Conner BleackleyAmericans (Buf)C7601100013411690.00%21331.750000170003180060.00%4000000.1500000000
Stats d'équipe Total ou en Moyenne13321923425342307148012021292206456913749.30%4712120115.925711116854231525712432055451354.95%575800100.50532358374247
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)3925940.9281.62230148628590200.55693844532
Stats d'équipe Total ou en Moyenne3925940.9281.62230148628590200.55693844532


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
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
2225.14187 Lbs5 ft112.36397,727$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Greg CareySheldon DriesDrew Stafford40122
2Sam LaffertyJohn QuennevilleErik Condra30122
3Mikey EyssimontCameron DarcyJustin Kloos20122
4Greg CareyKailer YamamotoEric Cornel10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Casey NelsonCalle Rosen40122
2Robbie RussoBlake Siebenaler30122
3Justin HollCasey Nelson20122
4Calle RosenRobbie Russo10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Greg CareySheldon DriesDrew Stafford60122
2Sam LaffertyJohn QuennevilleErik Condra40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Casey NelsonCalle Rosen60122
2Robbie RussoBlake Siebenaler40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Greg CareyDrew Stafford60122
2Sheldon DriesErik Condra40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Casey NelsonCalle Rosen60122
2Robbie RussoBlake Siebenaler40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Greg Carey60122Casey NelsonCalle Rosen60122
2Drew Stafford40122Robbie RussoBlake Siebenaler40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Greg CareyDrew Stafford60122
2Sheldon DriesErik Condra40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Casey NelsonCalle Rosen60122
2Robbie RussoBlake Siebenaler40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Greg CareySheldon DriesDrew StaffordCasey NelsonCalle Rosen
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Greg CareySheldon DriesDrew StaffordCasey NelsonCalle Rosen
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Conner Bleackley, Cameron Darcy, Justin KloosConner Bleackley, Cameron DarcyJustin Kloos
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Justin Holl, Blake Siebenaler, Casey NelsonJustin HollBlake Siebenaler, Casey Nelson
Tirs de Pénalité
Greg Carey, Drew Stafford, Sheldon Dries, Erik Condra, John Quenneville
Gardien
#1 : Charlie Lindgren, #2 :


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
1Bears2110000013-2110000001011010000003-320.500123017748716667376667125235810351200.00%40100.00%01403248856.39%1196221054.12%565101855.50%202514561656536927481
2Bruins21100000330110000001011010000023-120.5003690177487164573766671252611627388225.00%10190.00%01403248856.39%1196221054.12%565101855.50%202514561656536927481
3Checkers440000002121922000000927220000001201281.000213657037748716202737666712527623536014321.43%110100.00%01403248856.39%1196221054.12%565101855.50%202514561656536927481
4Comets10810001037152253100010181085500000019514180.9003768105027748716287737666712521635594175621219.35%38489.47%11403248856.39%1196221054.12%565101855.50%202514561656536927481
5Crunch1254001112627-16310011016151623000011012-2140.58326426801774871631173766671252281949118568913.24%39879.49%01403248856.39%1196221054.12%565101855.50%202514561656536927481
6Devils1033010031618-25210100185351200002813-5110.550162945037748716241737666712522217410818054712.96%47785.11%01403248856.39%1196221054.12%565101855.50%202514561656536927481
7Marlies660000003082233000000164123300000014410121.00030538300774871627973766671252137354412321419.05%21290.48%21403248856.39%1196221054.12%565101855.50%202514561656536927481
8Monsters8430001020182422000001013-3421000101055100.62520375712774871620773766671252205708113643716.28%36488.89%21403248856.39%1196221054.12%565101855.50%202514561656536927481
9Penguins22000000624110000002021100000042241.00061117017748716597376667125240719371417.14%60100.00%01403248856.39%1196221054.12%565101855.50%202514561656536927481
10Phantoms21100000440110000003121010000013-220.500481200774871636737666712523714413210330.00%11281.82%01403248856.39%1196221054.12%565101855.50%202514561656536927481
11Rocket43100000963220000006242110000034-160.75091524007748716106737666712529930646622418.18%29293.10%01403248856.39%1196221054.12%565101855.50%202514561656536927481
12Senators42200000862211000005412110000032140.5008162401774871664737666712527116436019210.53%19384.21%01403248856.39%1196221054.12%565101855.50%202514561656536927481
13Sound Tigers4120010037-42010010026-42110000011030.3753580177487169173766671252872449711915.26%22386.36%01403248856.39%1196221054.12%565101855.50%202514561656536927481
14Thunderbirds22000000514110000003121100000020241.000591401774871646737666712524816163410330.00%80100.00%01403248856.39%1196221054.12%565101855.50%202514561656536927481
Total764519012452011287338247012311076641382112000149462321070.7042013595601177748716213473766671252167350978713033926215.82%3203788.44%51403248856.39%1196221054.12%565101855.50%202514561656536927481
16Wolf Pack420000111284210000107342100000155070.875122234007748716947376667125211227477116425.00%19194.74%01403248856.39%1196221054.12%565101855.50%202514561656536927481
_Since Last GM Reset764519012452011287338247012311076641382112000149462321070.7042013595601177748716213473766671252167350978713033926215.82%3203788.44%51403248856.39%1196221054.12%565101855.50%202514561656536927481
_Vs Conference2623200010102327013111000105219331312100000501337480.923102181283067748716920737666712525231592714581292620.16%107892.52%31403248856.39%1196221054.12%565101855.50%202514561656536927481

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
76107L1201359560213416735097871303117
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
7645191245201128
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
38247123110766
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
38211200149462
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
3926215.82%3203788.44%5
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
737666712527748716
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
1403248856.39%1196221054.12%565101855.50%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
202514561656536927481


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 - 2020-01-01689Americans4Devils1WSommaire du Match
123 - 2020-01-02701Americans3Wolf Pack2WSommaire du Match
127 - 2020-01-06719Crunch6Americans2LSommaire du Match
129 - 2020-01-08725Thunderbirds1Americans3WSommaire du Match
130 - 2020-01-09740Americans4Comets0WSommaire du Match
133 - 2020-01-12757Americans0Monsters1LSommaire du Match
136 - 2020-01-15774Crunch1Americans3WSommaire du Match
137 - 2020-01-16782Americans2Crunch3LXXSommaire du Match
138 - 2020-01-17797Devils0Americans1WSommaire du Match
141 - 2020-01-20811Monsters0Americans1WSommaire du Match
143 - 2020-01-22818Americans6Comets2WSommaire du Match
144 - 2020-01-23834Senators1Americans4WSommaire du Match
148 - 2020-01-27852Americans4Comets2WSommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
151 - 2020-01-30871Americans0Crunch3LSommaire du Match
152 - 2020-01-31884Crunch1Americans2WSommaire du Match
157 - 2020-02-05904Sound Tigers3Americans0LSommaire du Match
158 - 2020-02-06916Americans1Devils2LXXSommaire du Match
159 - 2020-02-07926Devils3Americans2LXXSommaire du Match
162 - 2020-02-10938Comets2Americans5WSommaire du Match
164 - 2020-02-12946Americans5Checkers0WSommaire du Match
165 - 2020-02-13955Americans7Checkers0WSommaire du Match
171 - 2020-02-19988Monsters4Americans5WSommaire du Match
172 - 2020-02-20994Americans6Marlies1WSommaire du Match
173 - 2020-02-211011Americans3Marlies2WSommaire du Match
176 - 2020-02-241021Phantoms1Americans3WSommaire du Match
178 - 2020-02-261032Rocket1Americans3WSommaire du Match
179 - 2020-02-271048Americans1Devils6LSommaire du Match
185 - 2020-03-041077Crunch4Americans3LXSommaire du Match
186 - 2020-03-051089Americans0Crunch1LSommaire du Match
188 - 2020-03-071104Americans3Monsters0WSommaire du Match
192 - 2020-03-111121Devils0Americans4WSommaire du Match
193 - 2020-03-121130Americans1Crunch0WSommaire du Match
194 - 2020-03-131142Americans1Senators2LSommaire 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
5,109,848$ 87,500$ 50,750$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 109,776$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 0 26,224$ 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
14764519012452011287338247012311076641382112000149462321072013595601177748716213473766671252167350978713033926215.82%3203788.44%51403248856.39%1196221054.12%565101855.50%202514561656536927481
Total Saison Régulière764519012452011287338247012311076641382112000149462321072013595601177748716213473766671252167350978713033926215.82%3203788.44%51403248856.39%1196221054.12%565101855.50%202514561656536927481