Monsters

GP: 43 | W: 30 | L: 11 | OTL: 2 | P: 62
GF: 159 | GA: 95 | PP%: 14.97% | PK%: 84.32%
DG: Patrick Auger | Morale : 74 | Moyenne d'Équipe : 63
Prochain matchs #688 vs Penguins
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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 RobinsonX100.008338846099928959666055645775685781650
2Nick CousinsXXX100.008144816469749463736563616471686384640
3Oscar LindbergX100.008140846378736862726165646375685882640
4Casey Mittelstadt (R)X100.005636916977749068746765526961628778640
5Brendan LeipsicXX100.006439856667757665537261596369666181630
6Ryan HaggertyXX100.006138866074939159625659585971665983620
7Emil PetterssonX100.005537896073928859676154565769656083610
8Daniel AudetteX100.005238845864949256635854535665636282590
9Brayden BurkeX100.005236905954939058615754535663627281590
10Nikita SoshnikovX100.005435936069666358555756595471665182580
11Jonah Gadjovich (R)X100.006838845582857954555352565361636482580
12David Kase (R)X100.005336925855837657645954535663626331570
13Ryan SproulX100.007136925887928956305753614671666782650
14Josiah DidierX100.006641765581847854305451564571666082610
15Kyle BurroughsX100.005942735572939152305451534866747182600
16Jeremy RoyX100.006036915673918755305652544663627482600
17Brennan MenellX100.005236906057939159306551544963626382600
18Will O'NeillX100.006244695675797355305751554579715487600
Rayé
1Max VeronneauX100.005235955772735356525558535667644320560
MOYENNE D'ÉQUIPE100.00623886597384825852595657556865637661
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 Hogberg100.00796967917877797877797869736480750
2Eamon McAdam100.00737068747271737271737269735182700
Rayé
1Evan Cormier (R)100.00736967837271737271737263675320690
2Filip Gustavsson100.00717472777069717069717061657520680
MOYENNE D'ÉQUIPE100.0074716981737274737274736670615171
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'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
1Oscar LindbergMonsters (Clb)LW4325315630620116721734911814.45%777518.037714411460002487161.22%4900011.4411000671
2Brendan LeipsicMonsters (Clb)C/LW43163046282552777122409813.11%683819.5048122714600061331453.79%59300001.1013001334
3Ryan HaggertyMonsters (Clb)C/RW43132841301352656121348510.74%1172416.84291130149000004251.06%32900001.1301001314
4Nick CousinsMonsters (Clb)C/LW/RW431522372463158383160351029.38%1393521.753363515801181874059.63%48800100.7914201134
5Ryan SproulMonsters (Clb)D436222826540883658153510.34%45105424.52369351600001178000.00%000000.5300000201
6Emil PetterssonMonsters (Clb)C43121527221352467110246110.91%661414.2900003000001456.06%55300000.8800001243
7Buddy RobinsonMonsters (Clb)RW4312132517475795112430609.68%1083019.3232534161000111472068.70%13100000.6014000223
8Casey MittelstadtMonsters (Clb)C281312251240482102416812.75%366823.891341910910141292060.65%83100000.7502000221
9Kyle BurroughsMonsters (Clb)D434182224721058133522011.43%3490421.03246231430000157100.00%000000.4900002000
10Nikita SoshnikovMonsters (Clb)RW4311112220801633109316910.09%1263514.79112545000001145.95%3700010.6900000212
11Jeremy RoyMonsters (Clb)D436142028280332635142117.14%32102623.88022141650110186010.00%000000.3900000112
12Jonah GadjovichMonsters (Clb)LW436142021400692547194812.77%461314.2600000000041046.43%2800000.6500000100
13Will O'NeillMonsters (Clb)D436111725792563192651423.08%3860414.0600007000038100.00%000000.5600401012
14Josiah DidierMonsters (Clb)D4331114226757923388247.89%4295722.28235161430002161100.00%000000.2900001100
15Brennan MenellMonsters (Clb)D43013132022014369550.00%1860714.1300011000055000.00%000000.4300000000
16Brayden BurkeMonsters (Clb)RW43448619582536102611.11%13047.0900000000001037.50%1600000.5200001011
17Daniel AudetteMonsters (Clb)C431452004580312.50%0781.83011015000180045.83%4800001.2711000010
18David KaseMonsters (Clb)RW151342000331533.33%2573.8200000000000025.00%400001.4000000100
Stats d'équipe Total ou en Moyenne73115427643035961680791732131636386211.70%2841223216.732849772801558123351437271357.00%310700120.70516609272728
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)43291120.9072.15257106929920110.68716430023
2Eamon McAdamMonsters (Clb)11001.0000.003000090000.0000043000
Stats d'équipe Total ou en Moyenne44301120.9082.122601069210010110.687164343023


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
Brayden BurkeMonsters (Clb)RW221997-01-01No165 Lbs5 ft1NoNoNo4Pro & Farm300,000$0$0$No300,000$300,000$300,000$Lien
Brendan LeipsicMonsters (Clb)C/LW251994-05-19No182 Lbs5 ft10NoNoNo4Pro & Farm500,000$0$0$No500,000$500,000$500,000$Lien
Brennan MenellMonsters (Clb)D221997-05-24No177 Lbs5 ft1NoNoNo3Pro & Farm300,000$0$0$No300,000$300,000$Lien
Buddy RobinsonMonsters (Clb)RW271991-09-30No232 Lbs6 ft6NoNoNo1Pro & Farm300,000$0$0$NoLien
Casey MittelstadtMonsters (Clb)C201998-11-22Yes202 Lbs6 ft1NoNoNo4Pro & Farm900,000$0$0$No900,000$900,000$900,000$Lien
Daniel AudetteMonsters (Clb)C231996-05-06No176 Lbs5 ft8NoNoNo2Pro & Farm500,000$0$0$No500,000$Lien
David KaseMonsters (Clb)RW221997-01-28Yes169 Lbs5 ft1NoNoNo4Pro & Farm300,000$0$0$No300,000$300,000$300,000$Lien
Eamon McAdamMonsters (Clb)G241994-09-24No200 Lbs6 ft0NoNoNo2Pro & Farm300,000$0$0$No300,000$Lien
Emil PetterssonMonsters (Clb)C251994-01-14No164 Lbs6 ft2NoNoNo3Pro & Farm300,000$0$0$No300,000$300,000$Lien
Evan CormierMonsters (Clb)G211997-11-06Yes200 Lbs6 ft3NoNoNo4Pro & Farm300,000$0$0$No300,000$300,000$300,000$Lien
Filip GustavssonMonsters (Clb)G211998-06-07No184 Lbs6 ft2NoNoNo3Pro & Farm500,000$0$0$No500,000$500,000$Lien
Jeremy RoyMonsters (Clb)D221997-05-14No195 Lbs6 ft0NoNoNo3Pro & Farm500,000$0$0$No500,000$500,000$Lien
Jonah GadjovichMonsters (Clb)LW201998-12-10Yes209 Lbs6 ft2NoNoNo4Pro & Farm500,000$0$0$No500,000$500,000$500,000$Lien
Josiah DidierMonsters (Clb)D261993-04-08No202 Lbs6 ft2NoNoNo2Pro & Farm300,000$0$0$No300,000$Lien
Kyle BurroughsMonsters (Clb)D231995-07-12No198 Lbs5 ft11NoNoNo1Pro & Farm300,000$0$0$NoLien
Marcus HogbergMonsters (Clb)G241994-11-25No209 Lbs6 ft5NoNoNo3Pro & Farm300,000$0$0$No300,000$300,000$Lien
Max VeronneauMonsters (Clb)RW231995-12-12No190 Lbs6 ft0NoNoNo4Pro & Farm300,000$0$0$No300,000$300,000$300,000$Lien
Nick CousinsMonsters (Clb)C/LW/RW251993-07-20No185 Lbs5 ft11NoNoNo2Pro & Farm300,000$0$0$No300,000$Lien
Nikita SoshnikovMonsters (Clb)RW251993-10-14No185 Lbs5 ft11NoNoNo1Pro & Farm300,000$0$0$NoLien
Oscar LindbergMonsters (Clb)LW271991-10-29No202 Lbs6 ft1NoNoNo2Pro & Farm500,000$0$0$No500,000$Lien
Ryan HaggertyMonsters (Clb)C/RW261993-03-04No200 Lbs6 ft0NoNoNo4Pro & Farm300,000$0$0$No300,000$300,000$300,000$Lien
Ryan SproulMonsters (Clb)D261993-01-13No205 Lbs6 ft4NoNoNo2Pro & Farm300,000$0$0$No300,000$Lien
Will O'NeillMonsters (Clb)D311988-04-28No190 Lbs6 ft1NoNoNo3Pro & Farm300,000$0$0$No300,000$300,000$Lien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2323.91192 Lbs5 ft112.83378,261$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Brendan LeipsicNick CousinsBuddy Robinson40122
2Oscar LindbergRyan HaggertyNikita Soshnikov30122
3Jonah GadjovichEmil PetterssonBrayden Burke20122
4Nick CousinsDavid Kase10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Ryan SproulJosiah Didier40122
2Kyle BurroughsJeremy Roy30122
3Brennan MenellWill O'Neill20122
4Ryan SproulJosiah Didier10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Brendan LeipsicNick CousinsBuddy Robinson60122
2Oscar LindbergRyan HaggertyNikita Soshnikov40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Ryan SproulJosiah Didier60122
2Kyle BurroughsJeremy Roy40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Nick CousinsBuddy Robinson60122
2Brendan LeipsicOscar Lindberg40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Ryan SproulJosiah Didier60122
2Kyle BurroughsJeremy Roy40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Nick Cousins60122Ryan SproulJosiah Didier60122
2Buddy Robinson40122Kyle BurroughsJeremy Roy40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Nick CousinsBuddy Robinson60122
2Brendan LeipsicOscar Lindberg40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Ryan SproulJosiah Didier60122
2Kyle BurroughsJeremy Roy40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Brendan LeipsicNick CousinsBuddy RobinsonRyan SproulJosiah Didier
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Brendan LeipsicNick CousinsBuddy RobinsonRyan SproulJosiah Didier
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Daniel Audette, Emil Pettersson, Daniel Audette, Emil Pettersson
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Brennan Menell, Will O'Neill, Kyle BurroughsBrennan MenellWill O'Neill, Kyle Burroughs
Tirs de Pénalité
Nick Cousins, Buddy Robinson, Brendan Leipsic, Oscar Lindberg, Ryan Haggerty
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
1Admirals11000000431000000000001100000043121.000461000614846733446458422271431613900.00%7185.71%0789135958.06%730130056.15%37864059.06%1155836939296510264
2Americans42100001131122010000147-32200000094550.6251324371061484671034464584222710929398317211.76%16475.00%0789135958.06%730130056.15%37864059.06%1155836939296510264
3Bears21000001770000000000002100000177030.750712190061484675944645842227591918461317.69%9277.78%0789135958.06%730130056.15%37864059.06%1155836939296510264
4Comets32100000770220000005321010000024-240.667711180061484678644645842227721851461516.67%22481.82%0789135958.06%730130056.15%37864059.06%1155836939296510264
5Crunch32100000880220000006331010000025-340.6678132100614846764446458422279121486712325.00%21385.71%0789135958.06%730130056.15%37864059.06%1155836939296510264
6Devils2020000016-5000000000002020000016-500.000112006148467454464584222736182229900.00%11190.91%0789135958.06%730130056.15%37864059.06%1155836939296510264
7Griffins4400000018216220000009272200000090981.0001832500361484671184464584222789266872900.00%21195.24%0789135958.06%730130056.15%37864059.06%1155836939296510264
8IceHogs320010001541122000000111101000100043161.000153045016148467124446458422275913294210110.00%12191.67%0789135958.06%730130056.15%37864059.06%1155836939296510264
9Marlies660000003892944000000247172200000014212121.00038691070161484673284464584222797318912719421.05%31390.32%1789135958.06%730130056.15%37864059.06%1155836939296510264
10Penguins32100000972211000006511100000032140.6679162500614846786446458422276320536023417.39%13284.62%0789135958.06%730130056.15%37864059.06%1155836939296510264
11Phantoms2010100046-2000000000002010100046-220.50047110061484673444645842227471425386116.67%100100.00%0789135958.06%730130056.15%37864059.06%1155836939296510264
12Rocket42200000171522200000012842020000057-240.5001729460061484671154464584222711530766317529.41%301066.67%0789135958.06%730130056.15%37864059.06%1155836939296510264
13Senators311000101358211000008171000001054140.66713223501614846777446458422277226586118633.33%20385.00%0789135958.06%730130056.15%37864059.06%1155836939296510264
Total4326110202215995642217300011904050219802011695514620.72115927943816614846713374464584222710022886207971872814.97%2363784.32%1789135958.06%730130056.15%37864059.06%1155836939296510264
15Wolves31100010550210000105321010000002-240.66757120061484676544645842227792028501000.00%13284.62%0789135958.06%730130056.15%37864059.06%1155836939296510264
_Since Last GM Reset4326110202215995642217300011904050219802011695514620.72115927943816614846713374464584222710022886207971872814.97%2363784.32%1789135958.06%730130056.15%37864059.06%1155836939296510264
_Vs Conference156601011423936420000020911924010112230-8170.567427111301614846736544645842227368118224301811518.52%841186.90%0789135958.06%730130056.15%37864059.06%1155836939296510264
_Vs Division240301000107505714000000063283510030100044222220.04210718929615614846780544645842227573163378473922021.74%1392482.73%1789135958.06%730130056.15%37864059.06%1155836939296510264

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
4362W11592794381337100228862079716
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
432611202215995
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
2217300119040
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
219820116955
Derniers 10 Matchs
WLOTWOTL SOWSOL
440020
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
1872814.97%2363784.32%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
446458422276148467
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
789135958.06%730130056.15%37864059.06%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
1155836939296510264


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 - 2019-11-13395Monsters5Americans2WSommaire du Match
74 - 2019-11-14404Americans3Monsters2LXXSommaire du Match
78 - 2019-11-18426Monsters4Griffins0WSommaire du Match
80 - 2019-11-20436Senators1Monsters0LSommaire du Match
81 - 2019-11-21449Senators0Monsters8WSommaire du Match
85 - 2019-11-25465Americans4Monsters2LSommaire du Match
87 - 2019-11-27477Griffins0Monsters3WSommaire du Match
88 - 2019-11-28492Monsters5Griffins0WSommaire du Match
95 - 2019-12-05531Comets2Monsters3WSommaire du Match
96 - 2019-12-06545Comets1Monsters2WSommaire du Match
99 - 2019-12-09553Monsters5Senators4WXXSommaire du Match
101 - 2019-12-11563Monsters2Crunch5LSommaire du Match
102 - 2019-12-12582Monsters1Devils2LSommaire du Match
108 - 2019-12-18610Monsters2Rocket3LSommaire du Match
109 - 2019-12-19616Monsters3Rocket4LSommaire du Match
113 - 2019-12-23647Marlies2Monsters8WSommaire du Match
114 - 2019-12-24653Wolves2Monsters3WXXSommaire du Match
116 - 2019-12-26675Wolves1Monsters2WSommaire du Match
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
16 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
3,121,477$ 87,000$ 24,370$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 54,463$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 75 26,222$ 1,966,650$




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
1443261102022159956422173000119040502198020116955146215927943816614846713374464584222710022886207971872814.97%2363784.32%1789135958.06%730130056.15%37864059.06%1155836939296510264
Total Saison Régulière43261102022159956422173000119040502198020116955146215927943816614846713374464584222710022886207971872814.97%2363784.32%1789135958.06%730130056.15%37864059.06%1155836939296510264