Monsters

GP: 25 | W: 19 | L: 5 | OTL: 1 | P: 39
GF: 99 | GA: 59 | PP%: 16.26% | PK%: 85.71%
DG: Patrick Auger | Morale : 68 | Moyenne d'Équipe : 62
Prochain matchs #395 vs Americans
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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
1Buddy RobinsonX100.008338846099928959666055645775685775640
2Nick CousinsXXX100.008144816469749463736563616471686379640
3Casey Mittelstadt (R)X100.005636916977749068746765526961628775640
4Oscar LindbergX100.008140846378736862726165646375685875630
5Brendan LeipsicXX100.006439856667757665537261596369666172630
6Ryan HaggertyXX100.006138866074939159625659585971665976620
7Emil PetterssonX100.005537896073928859676154565769656076610
8Jake Evans (R)X100.005736906072939059686154565765636275610
9Daniel AudetteX100.005238845864949256635854535665636275590
10Nikita SoshnikovX100.005435936069666358555756595471665175580
11Brayden BurkeX100.005236905954939058615754535663627272580
12Jonah Gadjovich (R)X100.006838845582857954555352565361636475580
13Ryan SproulX100.007136925887928956305753614671666775650
14Josiah DidierX100.006641765581847854305451564571666075610
15Kyle BurroughsX100.005942735572939152305451534866747173600
16Jeremy RoyX100.006036915673918755305652544663627475600
17Brennan MenellX100.005236906057939159306551544963626375600
18Will O'NeillX100.006244695675797355305751554579715479600
Rayé
1David Kase (R)X100.005336925855837657645954535663626325570
2Max VeronneauX100.005235955772735356525558535667644325560
MOYENNE D'ÉQUIPE100.00623886597385825853595657556865637061
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
1Marcus Hogberg100.00796967917877797877797869736470750
2Eamon McAdam100.00737068747271737271737269735175700
Rayé
1Evan Cormier (R)100.00736967837271737271737263675325700
2Filip Gustavsson100.00717472777069717069717061657525680
MOYENNE D'ÉQUIPE100.0074716981737274737274736670614971
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Todd McLellan81757775777173CAN5155,000,000$


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'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
1Oscar LindbergMonsters (Clb)LW25172037184407341118307314.41%343117.2754925900001105063.33%3000011.7100000530
2Brendan LeipsicMonsters (Clb)C/LW2512203214235204785267314.12%250520.23471120910005861355.51%48100001.2701001224
3Ryan HaggertyMonsters (Clb)C/RW2591625189582270184912.86%842216.902461593000004140.74%2700001.1800001211
4Nick CousinsMonsters (Clb)C/LW/RW259142312461041419220619.78%652020.823252310201151054076.81%6900100.8801101013
5Casey MittelstadtMonsters (Clb)C25121123114047493385912.90%359923.99134179910141192060.59%74600000.7701000221
6Buddy RobinsonMonsters (Clb)RW257916918051347114379.86%646818.73123211060008630065.31%9800000.6811000112
7Ryan SproulMonsters (Clb)D2511516173605120378282.70%2061724.71145231060000100000.00%000000.5200000100
8Jeremy RoyMonsters (Clb)D2569151760161321101128.57%1962625.0602281060110116010.00%000000.4800000112
9Emil PetterssonMonsters (Clb)C25861412115164065173812.31%334613.8600003000001359.94%31700000.8100001042
10Kyle BurroughsMonsters (Clb)D25211131442103361921110.53%1850520.241341285000090000.00%000000.5100002000
11Nikita SoshnikovMonsters (Clb)RW25581311208216217398.06%534313.7300000000000136.36%2200000.7600000012
12Jonah GadjovichMonsters (Clb)LW25211131120042133014336.67%134713.8900000000040050.00%1800000.7500000100
13Josiah DidierMonsters (Clb)D253811133605112336179.09%2854021.622241690000294100.00%000000.4100000100
14Will O'NeillMonsters (Clb)D25459124410296184722.22%1933713.500000700008100.00%000000.5300101010
15Brennan MenellMonsters (Clb)D25077712010218440.00%935414.1600011000046000.00%000000.4000000000
16Daniel AudetteMonsters (Clb)C251454003240225.00%0491.98011011000160045.45%3300002.0200000010
17Jake EvansMonsters (Clb)C25112-24061612448.33%21485.95000000003580064.57%12700000.2700000000
18Brayden BurkeMonsters (Clb)RW25000-2175349180.00%0773.1100000000000042.86%700000.0000001000
Stats d'équipe Total ou en Moyenne450991752741963745046543384723355411.69%152724316.102034541819971232991219959.39%197500110.7614208161817
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
1Marcus HogbergMonsters (Clb)2518510.8932.36147802585430100.5004250010
2Eamon McAdamMonsters (Clb)11001.0000.003000090000.0000025000
Stats d'équipe Total ou en Moyenne2619510.8952.31150802585520100.50042525010


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
Brayden BurkeMonsters (Clb)RW221997-01-01No165 Lbs5 ft1NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$NoLien
Brendan LeipsicMonsters (Clb)C/LW251994-05-19No182 Lbs5 ft10NoNoNo4Avec RestrictionPro & Farm500,000$0$0$NoLien
Brennan MenellMonsters (Clb)D221997-05-24No177 Lbs5 ft1NoNoNo3Contrat d'EntréePro & Farm300,000$0$0$NoLien
Buddy RobinsonMonsters (Clb)RW271991-09-30No232 Lbs6 ft6NoNoNo1Avec RestrictionPro & Farm300,000$0$0$NoLien
Casey MittelstadtMonsters (Clb)C201998-11-22Yes202 Lbs6 ft1NoNoNo4Contrat d'EntréePro & Farm900,000$0$0$NoLien
Daniel AudetteMonsters (Clb)C231996-05-06No176 Lbs5 ft8NoNoNo2Avec RestrictionPro & Farm500,000$0$0$NoLien
David KaseMonsters (Clb)RW221997-01-28Yes169 Lbs5 ft1NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$NoLien
Eamon McAdamMonsters (Clb)G241994-09-24No200 Lbs6 ft0NoNoNo2Avec RestrictionPro & Farm300,000$0$0$NoLien
Emil PetterssonMonsters (Clb)C251994-01-14No164 Lbs6 ft2NoNoNo3Avec RestrictionPro & Farm300,000$0$0$NoLien
Evan CormierMonsters (Clb)G211997-11-06Yes200 Lbs6 ft3NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$NoLien
Filip GustavssonMonsters (Clb)G211998-06-07No184 Lbs6 ft2NoNoNo3Contrat d'EntréePro & Farm500,000$0$0$NoLien
Jake EvansMonsters (Clb)C231996-06-02Yes186 Lbs6 ft0NoNoNo4Avec RestrictionPro & Farm300,000$0$0$NoLien
Jeremy RoyMonsters (Clb)D221997-05-14No195 Lbs6 ft0NoNoNo3Contrat d'EntréePro & Farm500,000$0$0$NoLien
Jonah GadjovichMonsters (Clb)LW201998-12-10Yes209 Lbs6 ft2NoNoNo4Contrat d'EntréePro & Farm500,000$0$0$NoLien
Josiah DidierMonsters (Clb)D261993-04-08No202 Lbs6 ft2NoNoNo2Avec RestrictionPro & Farm300,000$0$0$NoLien
Kyle BurroughsMonsters (Clb)D231995-07-12No198 Lbs5 ft11NoNoNo1Avec RestrictionPro & Farm300,000$0$0$NoLien
Marcus HogbergMonsters (Clb)G241994-11-25No209 Lbs6 ft5NoNoNo3Avec RestrictionPro & Farm300,000$0$0$NoLien
Max VeronneauMonsters (Clb)RW231995-12-12No190 Lbs6 ft0NoNoNo4Avec RestrictionPro & Farm300,000$0$0$NoLien
Nick CousinsMonsters (Clb)C/LW/RW251993-07-20No185 Lbs5 ft11NoNoNo2Avec RestrictionPro & Farm300,000$0$0$NoLien
Nikita SoshnikovMonsters (Clb)RW251993-10-14No185 Lbs5 ft11NoNoNo1Avec RestrictionPro & Farm300,000$0$0$NoLien
Oscar LindbergMonsters (Clb)LW271991-10-29No202 Lbs6 ft1NoNoNo2Avec RestrictionPro & Farm500,000$0$0$NoLien
Ryan HaggertyMonsters (Clb)C/RW261993-03-04No200 Lbs6 ft0NoNoNo4Avec RestrictionPro & Farm300,000$0$0$NoLien
Ryan SproulMonsters (Clb)D261993-01-13No205 Lbs6 ft4NoNoNo2Avec RestrictionPro & Farm300,000$0$0$NoLien
Will O'NeillMonsters (Clb)D311988-04-28No190 Lbs6 ft1NoNoNo3Sans RestrictionPro & Farm300,000$0$0$NoLien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2423.88192 Lbs5 ft112.88375,000$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Nick CousinsCasey MittelstadtBuddy Robinson40122
2Oscar LindbergBrendan LeipsicRyan Haggerty30122
3Jonah GadjovichEmil PetterssonNikita Soshnikov20122
4Casey MittelstadtJake EvansBrayden Burke10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Ryan SproulJeremy Roy40122
2Josiah DidierKyle Burroughs30122
3Will O'NeillBrennan Menell20122
4Ryan SproulJeremy Roy10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Nick CousinsCasey MittelstadtBuddy Robinson60122
2Oscar LindbergBrendan LeipsicRyan Haggerty40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Ryan SproulJeremy Roy60122
2Josiah DidierKyle Burroughs40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Casey MittelstadtNick Cousins60122
2Buddy RobinsonBrendan Leipsic40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Ryan SproulJeremy Roy60122
2Josiah DidierKyle Burroughs40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Casey Mittelstadt60122Ryan SproulJeremy Roy60122
2Nick Cousins40122Josiah DidierKyle Burroughs40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Casey MittelstadtNick Cousins60122
2Buddy RobinsonBrendan Leipsic40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Ryan SproulJeremy Roy60122
2Josiah DidierKyle Burroughs40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Nick CousinsCasey MittelstadtBuddy RobinsonRyan SproulJeremy Roy
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Nick CousinsCasey MittelstadtBuddy RobinsonRyan SproulJeremy Roy
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Daniel Audette, Emil Pettersson, Jake EvansDaniel Audette, Emil PetterssonJake Evans
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Will O'Neill, Brennan Menell, Josiah DidierWill O'NeillBrennan Menell, Josiah Didier
Tirs de Pénalité
Casey Mittelstadt, Nick Cousins, Buddy Robinson, Brendan Leipsic, Oscar Lindberg
Gardien
#1 : Marcus Hogberg, #2 : Eamon McAdam


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
1Admirals11000000431000000000001100000043121.00046100033323233327929926691431613900.00%7185.71%051482762.15%42374057.16%23639260.20%713528506165290154
2Americans11000000422000000000001100000042221.000481200333232331279299266925711189111.11%30100.00%051482762.15%42374057.16%23639260.20%713528506165290154
3Bears21000001770000000000002100000177030.75071219003332323592792992669591918461317.69%9277.78%051482762.15%42374057.16%23639260.20%713528506165290154
4Comets1010000024-2000000000001010000024-200.0002460033323233127929926692242412500.00%12191.67%051482762.15%42374057.16%23639260.20%713528506165290154
5Crunch22000000633220000006330000000000041.00069150033323234027929926695612405310330.00%18288.89%051482762.15%42374057.16%23639260.20%713528506165290154
6Devils1010000004-4000000000001010000004-400.00000000333232328279299266914101218300.00%6183.33%051482762.15%42374057.16%23639260.20%713528506165290154
7Griffins11000000624110000006240000000000021.000610160033323232227929926693182522000.00%5180.00%051482762.15%42374057.16%23639260.20%713528506165290154
8IceHogs320010001541122000000111101000100043161.00015304501333232312427929926695913294210110.00%12191.67%051482762.15%42374057.16%23639260.20%713528506165290154
9Marlies550000003072333000000165112200000014212101.000305484013332323282279299266983277810119421.05%28292.86%151482762.15%42374057.16%23639260.20%713528506165290154
10Penguins32100000972211000006511100000032140.667916250033323238627929926696320536023417.39%13284.62%051482762.15%42374057.16%23639260.20%713528506165290154
11Phantoms2010100046-2000000000002010100046-220.5004711003332323342792992669471425386116.67%100100.00%051482762.15%42374057.16%23639260.20%713528506165290154
12Rocket2200000012842200000012840000000000041.0001220320033323236527929926695914392913538.46%15660.00%051482762.15%42374057.16%23639260.20%713528506165290154
Total2517502001995940121110000057243313640200142357390.7809917627502333232384927929926695521523744651232016.26%1402085.71%151482762.15%42374057.16%23639260.20%713528506165290154
14Wolves1010000002-2000000000001010000002-200.000000003332323142792992669201413300.00%2150.00%051482762.15%42374057.16%23639260.20%713528506165290154
_Since Last GM Reset2517502001995940121110000057243313640200142357390.7809917627502333232384927929926695521523744651232016.26%1402085.71%151482762.15%42374057.16%23639260.20%713528506165290154
_Vs Conference1053010012627-1431000001284622010011419-5130.65026447000333232324727929926692397514821555916.36%56787.50%051482762.15%42374057.16%23639260.20%713528506165290154
_Vs Division11020100058223680000000401822302010001841420.09158101159013332323440279299266925468193223511325.49%691184.06%151482762.15%42374057.16%23639260.20%713528506165290154

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
2539OTW19917627584955215237446502
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
2517520019959
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
1211100005724
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
136420014235
Derniers 10 Matchs
WLOTWOTL SOWSOL
711001
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
1232016.26%1402085.71%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
27929926693332323
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
51482762.15%42374057.16%23639260.20%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
713528506165290154


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 - 2019-09-042IceHogs1Monsters6WSommaire du Match
4 - 2019-09-0510IceHogs0Monsters5WSommaire du Match
6 - 2019-09-0727Monsters7Marlies2WSommaire du Match
9 - 2019-09-1032Penguins3Monsters2LSommaire du Match
11 - 2019-09-1247Penguins2Monsters4WSommaire du Match
17 - 2019-09-1872Monsters2Comets4LSommaire du Match
18 - 2019-09-1990Monsters0Devils4LSommaire du Match
22 - 2019-09-23102Monsters0Wolves2LSommaire du Match
24 - 2019-09-25112Monsters4Admirals3WSommaire du Match
25 - 2019-09-26120Monsters4IceHogs3WXSommaire du Match
31 - 2019-10-02141Marlies1Monsters3WSommaire du Match
33 - 2019-10-04169Griffins2Monsters6WSommaire du Match
36 - 2019-10-07177Monsters4Americans2WSommaire du Match
38 - 2019-10-09182Rocket4Monsters5WSommaire du Match
39 - 2019-10-10192Rocket4Monsters7WSommaire du Match
45 - 2019-10-16223Monsters4Bears3WSommaire du Match
46 - 2019-10-17238Monsters3Bears4LXXSommaire du Match
52 - 2019-10-23266Marlies2Monsters7WSommaire du Match
54 - 2019-10-25293Monsters7Marlies0WSommaire du Match
57 - 2019-10-28301Marlies2Monsters6WSommaire du Match
59 - 2019-10-30308Crunch1Monsters3WSommaire du Match
60 - 2019-10-31318Crunch2Monsters3WSommaire du Match
64 - 2019-11-04343Monsters1Phantoms4LSommaire du Match
66 - 2019-11-06354Monsters3Penguins2WSommaire du Match
67 - 2019-11-07369Monsters3Phantoms2WXSommaire du Match
73 - 2019-11-13395Monsters-Americans-
74 - 2019-11-14404Americans-Monsters-
78 - 2019-11-18426Monsters-Griffins-
80 - 2019-11-20436Senators-Monsters-
81 - 2019-11-21449Senators-Monsters-
85 - 2019-11-25465Americans-Monsters-
87 - 2019-11-27477Griffins-Monsters-
88 - 2019-11-28492Monsters-Griffins-
95 - 2019-12-05531Comets-Monsters-
96 - 2019-12-06545Comets-Monsters-
99 - 2019-12-09553Monsters-Senators-
101 - 2019-12-11563Monsters-Crunch-
102 - 2019-12-12582Monsters-Devils-
108 - 2019-12-18610Monsters-Rocket-
109 - 2019-12-19616Monsters-Rocket-
113 - 2019-12-23647Marlies-Monsters-
114 - 2019-12-24653Wolves-Monsters-
116 - 2019-12-26675Wolves-Monsters-
122 - 2020-01-01688Monsters-Penguins-
123 - 2020-01-02702Monsters-Crunch-
126 - 2020-01-05713Monsters-Checkers-
127 - 2020-01-06716Monsters-Checkers-
130 - 2020-01-09739Devils-Monsters-
131 - 2020-01-10749Devils-Monsters-
133 - 2020-01-12757Americans-Monsters-
136 - 2020-01-15769Monsters-Senators-
137 - 2020-01-16783Monsters-Senators-
138 - 2020-01-17799Monsters-Comets-
141 - 2020-01-20811Monsters-Americans-
143 - 2020-01-22819Admirals-Monsters-
145 - 2020-01-24841Admirals-Monsters-
149 - 2020-01-28855Rocket-Monsters-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
150 - 2020-01-29859Rocket-Monsters-
151 - 2020-01-30868Monsters-Marlies-
156 - 2020-02-04896Senators-Monsters-
157 - 2020-02-05898Senators-Monsters-
162 - 2020-02-10934Monsters-Admirals-
164 - 2020-02-12950Monsters-Wolves-
165 - 2020-02-13960Monsters-IceHogs-
171 - 2020-02-19988Monsters-Americans-
172 - 2020-02-20996Bears-Monsters-
173 - 2020-02-211009Bears-Monsters-
178 - 2020-02-261028Phantoms-Monsters-
179 - 2020-02-271041Phantoms-Monsters-
183 - 2020-03-021066Monsters-Rocket-
185 - 2020-03-041078Monsters-Rocket-
186 - 2020-03-051090Monsters-Senators-
188 - 2020-03-071104Americans-Monsters-
191 - 2020-03-101114Checkers-Monsters-
192 - 2020-03-111115Checkers-Monsters-
194 - 2020-03-131145Monsters-Marlies-



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
26 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
1,889,112$ 90,000$ 24,370$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 33,453$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 122 26,237$ 3,200,914$




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
142517502001995940121110000057243313640200142357399917627502333232384927929926695521523744651232016.26%1402085.71%151482762.15%42374057.16%23639260.20%713528506165290154
Total Saison Régulière2517502001995940121110000057243313640200142357399917627502333232384927929926695521523744651232016.26%1402085.71%151482762.15%42374057.16%23639260.20%713528506165290154