Monsters

GP: 76 | W: 50 | L: 21 | OTL: 5 | P: 105
GF: 242 | GA: 150 | PP%: 17.96% | PK%: 87.47%
DG: Patrick Auger | Morale : 82 | Moyenne d'Équipe : 58
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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
1Oscar LindbergX100.00845576788078827181637076557168183700
2Dylan Strome (R)X100.00635570827570707973707065557372182690
3Nick CousinsX100.00775573756966677668657378556564183680
4Oskar Lindblom (R)X100.00765571847072737650636565557070182670
5Chris KellyX100.00685578757768676450626061557575183630
6Nikita SoshnikovX100.00845578816762646550606162555252182620
7Daniel CatenacciX100.00595572626662695550555560557574182580
8Daniel AudetteX100.00585572676259695550555559557175182580
9Nick TarnaskyX100.00745558638179645550555555556465182580
10Mike BrownX100.00605566697569545550555555556970182580
11Zack StortiniX100.00645557618179745550555555556565182580
12Ryan HaggertyX100.00715569687569665550555555555050182570
13Colin White (R)X100.00565555555657576660555555557371180560
14Tim BozonX100.00745567627468645550555555555050128560
15Madison BoweyX100.00795579866974647825716075557878182710
16Ryan SproulX100.00685566766779647425646268557070168660
17Brian LashoffX100.00555555605555785525555555556061182560
18Ville PokkaX100.00555557605757765725575757555353182560
19Mike WeberX100.00555555605555625525555555556970131550
Rayé
1Quinton HowdenX100.00565563656866695550555555555656120560
2Matt Buckles (R)X100.00825582557954545550555555555050120550
3Akim Aliu (R)X100.00565555555859605550555555557575120550
4Brandon AldersonX100.00565555555758595550555555557472120540
5Buddy RobinsonX100.00565555555758585550555555557472120540
6Cody Kunyk (R)X100.00565555555758585550555555557371120540
7Zach O'Brien (R)X100.00705568555461685550555555555050120540
8Emil Pettersson (R)X100.00555555555555555550555555557571120540
9Stephen MacAulay (R)X100.00565559626866545550555555555050120540
10Lauri KorpikoskiX100.00555555555555555550555555557473120540
11Joshua WinquistX100.00565555555556555550555555555050120520
12Olivier Archambault (R)X100.00555562555454545550555555555050120520
13Mike SisloX100.00565555555555555550555555555050120520
14Kyle BurroughsX100.00565556605656635625565656555353120540
15Robin Norell (R)X100.00555555605555675525555555555353120540
16Jeremy Roy (R)X100.00565555605555565525555555556262120540
17Will O'NeillX100.00575555605555675525555555555353120540
18Josiah DidierX100.00555555605555595525555555555353120530
19John NegrinX100.00555555605555585525555555555353120530
20Brennan Menell (R)X100.00555555605555565525555555555555120530
MOYENNE D'ÉQUIPE100.0062556263636263594457575855626214757
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
1Jack Campbell100.0073778373707075706771556967178700
2Eamon McAdam100.0062707079656565656864556062182650
Rayé
1Jeff Malcolm100.0054645971585858585958555456119580
2Marcus Hogberg100.0055555555555555555555556565120550
3Filip Gustavsson (R)100.0055555555555555555555555060120540
MOYENNE D'ÉQUIPE100.006064646761616261616155606214460
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Randy Ladouceur42626738807060CAN564100,000$


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)C76295180179151572112717215910.70%33175423.09162844100401213113457066.54%162900020.9117001664
2Oskar LindblomMonsters (Clb)LW763034647440791102424912612.40%8127916.84102333814081016825051.46%10300111.0002000244
3Madison BoweyMonsters (Clb)D661549641011010146102118318012.71%70165325.06112435843070002233310.00%000000.7700101425
4Dylan StromeMonsters (Clb)C7227245119180431902295216911.79%15124217.2579165022120261855264.29%123500000.8205000387
5Ryan SproulMonsters (Clb)D5310415131780866683346512.05%47127123.9971219512440220191220.00%000000.8000000274
6Nick CousinsMonsters (Clb)C75282149156601151522125214713.21%32125316.71106165919001171917261.26%69700000.7815000652
7Nikita SoshnikovMonsters (Clb)RW761428421366011998149451249.40%11126416.645111644381000001145.00%8000000.6600000234
8Jake VirtanenColumbus Blue JacketsRW36112637755576100139381137.91%1385923.884101440183011101493055.11%37200110.8625010352
9Daniel AudetteMonsters (Clb)LW76821295215344776307310.53%9107914.20471115231000054050.91%5500000.5400010023
10Nick TarnaskyMonsters (Clb)LW76911202810315973557223715.79%3102213.4633612135000052047.06%5100000.3900012201
11Daniel CatenacciMonsters (Clb)RW76117186140404495324911.58%995012.51325181080000192137.50%5600010.3800000212
12Chris KellyMonsters (Clb)C767916527528607735599.09%116027.931129350001710053.87%37500000.5311001011
13Mike BrownMonsters (Clb)RW76510151018026335516399.09%16518.57101240000001043.59%3900000.4600000000
14Brian LashoffMonsters (Clb)D76311141283593203110209.68%59146719.31235152330000219000.00%000000.1900010021
15Ville PokkaMonsters (Clb)D713111413561075302691911.54%45151721.37235162740110234000.00%000000.1800011100
16Colin WhiteMonsters (Clb)C50189101001720133107.69%94368.7401124700031451058.95%9500000.4100000001
17Mike WeberMonsters (Clb)D1514579514454220.00%926017.39112229000036000.00%000000.3800100000
18Zack StortiniMonsters (Clb)C76325-727535181931815.79%54365.750113590000570051.07%23300000.2300001000
19Tim BozonMonsters (Clb)LW2013454012511479.09%11286.4200000000000020.00%500000.6200000000
20Ryan HaggertyMonsters (Clb)RW76213614019121861911.11%22973.910001220000100040.35%5700000.2000000100
21Brendan LeipsicColumbus Blue JacketsC/LW1011000032000.00%02020.0801117000030073.33%1500001.0000000000
Stats d'équipe Total ou en Moyenne129521837359121991470131113601928547133511.31%3921945215.02871462336053563561146218843960.84%509700250.61525257344641
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
1Jack CampbellMonsters (Clb)72481950.9011.92425741213613760510.74127720812
2Eamon McAdamMonsters (Clb)72200.9041.63332009940100.0000476000
Stats d'équipe Total ou en Moyenne79502150.9011.90459041214514700610.741277676812


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
Akim AliuMonsters (Clb)RW271989-04-23Yes225 Lbs6 ft4NoNoNo3Avec RestrictionPro & Farm500,000$0$0$No
Brandon AldersonMonsters (Clb)RW241992-01-21No202 Lbs6 ft4NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Brennan MenellMonsters (Clb)D191997-05-24Yes183 Lbs5 ft11NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No
Brian LashoffMonsters (Clb)D261990-07-15No212 Lbs6 ft3NoNoNo4Avec RestrictionPro & Farm300,000$0$0$No
Buddy RobinsonMonsters (Clb)RW251991-09-30No235 Lbs6 ft5NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No
Chris KellyMonsters (Clb)C361980-11-11No198 Lbs6 ft0NoNoNo2Sans RestrictionPro & Farm300,000$0$0$No
Cody KunykMonsters (Clb)RW261990-05-20Yes195 Lbs5 ft11NoNoNo3Avec RestrictionPro & Farm500,000$0$0$No
Colin WhiteMonsters (Clb)C191997-01-30Yes190 Lbs6 ft1NoNoNo4Contrat d'EntréePro & Farm900,000$0$0$No
Daniel AudetteMonsters (Clb)LW201996-05-06No176 Lbs5 ft8NoNoNo3Contrat d'EntréePro & Farm500,000$0$0$No
Daniel CatenacciMonsters (Clb)RW231993-03-09No186 Lbs5 ft9NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No
Dylan StromeMonsters (Clb)C191997-03-07Yes185 Lbs6 ft3NoNoNo4Contrat d'EntréePro & Farm900,000$0$0$No
Eamon McAdamMonsters (Clb)G221994-09-23No199 Lbs6 ft3NoNoNo3Contrat d'EntréePro & Farm300,000$0$0$No
Emil PetterssonMonsters (Clb)C221994-01-14Yes176 Lbs6 ft2NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No
Filip GustavssonMonsters (Clb)G181998-06-07Yes185 Lbs6 ft2NoNoNo4Contrat d'EntréePro & Farm500,000$0$0$No
Jack CampbellMonsters (Clb)G251992-01-09No195 Lbs6 ft3NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Jeff MalcolmMonsters (Clb)G271989-04-13No179 Lbs6 ft2NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No
Jeremy RoyMonsters (Clb)D191997-05-14Yes187 Lbs6 ft0NoNoNo4Contrat d'EntréePro & Farm500,000$0$0$No
John NegrinMonsters (Clb)D271989-03-25No194 Lbs6 ft2NoNoNo3Avec RestrictionPro & Farm500,000$0$0$No
Joshua WinquistMonsters (Clb)LW231993-09-06No185 Lbs5 ft11NoNoNo3Avec RestrictionPro & Farm300,000$0$0$No
Josiah DidierMonsters (Clb)D231993-04-08No203 Lbs6 ft2NoNoNo3Avec RestrictionPro & Farm300,000$0$0$No
Kyle BurroughsMonsters (Clb)D211995-07-12No198 Lbs6 ft0NoNoNo1Contrat d'EntréePro & Farm630,000$0$0$No
Lauri KorpikoskiMonsters (Clb)LW301986-07-28No205 Lbs6 ft1NoNoNo1Sans RestrictionPro & Farm976,882$0$0$No
Madison BoweyMonsters (Clb)D211995-04-22No194 Lbs6 ft1NoNoNo1Contrat d'EntréePro & Farm894,000$0$0$No
Marcus HogbergMonsters (Clb)G221994-11-25No209 Lbs6 ft5NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No
Matt BucklesMonsters (Clb)C211995-05-05Yes218 Lbs6 ft3NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No
Mike BrownMonsters (Clb)RW311985-06-23No205 Lbs5 ft11NoNoNo1Sans RestrictionPro & Farm300,000$0$0$No
Mike SisloMonsters (Clb)RW281988-01-19No195 Lbs5 ft11NoNoNo1Sans RestrictionPro & Farm300,000$0$0$No
Mike WeberMonsters (Clb)D291987-12-15No212 Lbs6 ft2NoNoNo1Sans RestrictionPro & Farm300,000$0$0$No
Nick CousinsMonsters (Clb)C231993-07-19No169 Lbs5 ft10NoNoNo3Avec RestrictionPro & Farm300,000$0$0$No
Nick TarnaskyMonsters (Clb)LW321984-11-24No230 Lbs6 ft2NoNoNo4Sans RestrictionPro & Farm300,000$0$0$No
Nikita SoshnikovMonsters (Clb)RW231993-10-14No183 Lbs5 ft11NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No
Olivier ArchambaultMonsters (Clb)LW231993-02-15Yes176 Lbs5 ft11NoNoNo4Avec RestrictionPro & Farm500,000$0$0$No
Oscar LindbergMonsters (Clb)C251991-10-28No195 Lbs6 ft1NoNoNo3Avec RestrictionPro & Farm500,000$0$0$No
Oskar LindblomMonsters (Clb)LW201996-08-15Yes192 Lbs6 ft1NoNoNo4Contrat d'EntréePro & Farm500,000$0$0$No
Quinton HowdenMonsters (Clb)C241992-01-20No189 Lbs6 ft2NoNoNo3Avec RestrictionPro & Farm300,000$0$0$No
Robin NorellMonsters (Clb)D211995-02-17Yes195 Lbs5 ft11NoNoNo3Contrat d'EntréePro & Farm300,000$0$0$No
Ryan HaggertyMonsters (Clb)RW231993-03-03No201 Lbs6 ft0NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Ryan SproulMonsters (Clb)D241993-01-12No206 Lbs6 ft4NoNoNo3Avec RestrictionPro & Farm300,000$0$0$No
Stephen MacAulayMonsters (Clb)C241992-04-20Yes182 Lbs6 ft2NoNoNo4Avec RestrictionPro & Farm500,000$0$0$No
Tim BozonMonsters (Clb)LW221994-03-24No196 Lbs6 ft1NoNoNo3Contrat d'EntréePro & Farm300,000$0$0$No
Ville PokkaMonsters (Clb)D221994-06-02No214 Lbs6 ft0NoNoNo1Contrat d'EntréePro & Farm500,000$0$0$No
Will O'NeillMonsters (Clb)D281988-04-27No190 Lbs6 ft1NoNoNo1Sans RestrictionPro & Farm500,000$0$0$No
Zach O'BrienMonsters (Clb)RW241992-06-29Yes192 Lbs5 ft11NoNoNo4Avec RestrictionPro & Farm500,000$0$0$No
Zack StortiniMonsters (Clb)C311985-09-10No230 Lbs6 ft4NoNoNo3Sans RestrictionPro & Farm500,000$0$0$No
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
4424.14197 Lbs6 ft12.70427,293$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Oskar LindblomOscar Lindberg40122
2Daniel AudetteDylan StromeNikita Soshnikov30122
3Nick TarnaskyNick CousinsDaniel Catenacci20122
4Tim BozonChris KellyMike Brown10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Madison BoweyRyan Sproul40122
2Ville PokkaBrian Lashoff30122
3Mike WeberMadison Bowey20122
4Ryan SproulVille Pokka10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Oskar LindblomOscar Lindberg60122
2Daniel AudetteDylan StromeNikita Soshnikov40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Madison BoweyRyan Sproul60122
2Ville PokkaBrian Lashoff40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Oscar Lindberg60122
2Dylan StromeNick Cousins40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Madison BoweyRyan Sproul60122
2Ville PokkaBrian Lashoff40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
160122Madison BoweyRyan Sproul60122
2Oscar Lindberg40122Ville PokkaBrian Lashoff40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Oscar Lindberg60122
2Dylan StromeNick Cousins40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Madison BoweyRyan Sproul60122
2Ville PokkaBrian Lashoff40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Oskar LindblomOscar LindbergMadison BoweyRyan Sproul
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Oskar LindblomOscar LindbergMadison BoweyRyan Sproul
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Zack Stortini, Ryan Haggerty, Chris KellyZack Stortini, Ryan HaggertyChris Kelly
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Mike Weber, Brian Lashoff, Madison BoweyMike WeberBrian Lashoff, Madison Bowey
Tirs de Pénalité
, Oscar Lindberg, Dylan Strome, Nick Cousins, Oskar Lindblom
Gardien
#1 : Jack Campbell, #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
1Admirals430000011147210000014222200000072570.875111829029278686100668676715375523456635617.14%20290.00%01490244360.99%1204208657.72%659104563.06%213515611561528899478
2Americans85200001181624310000012844210000168-2110.688183250009278686187668676715371414211213280911.25%45882.22%01490244360.99%1204208657.72%659104563.06%213515611561528899478
3Bears4210001011832010001058-32200000060660.750111930029278686936686767153710132487027414.81%24387.50%01490244360.99%1204208657.72%659104563.06%213515611561528899478
4Checkers43001000217142200000012392100100094581.000213657009278686159668676715376227308416531.25%15380.00%01490244360.99%1204208657.72%659104563.06%213515611561528899478
5Comets43000010166102200000010462100001062481.000162541019278686106668676715377727578727622.22%22290.91%01490244360.99%1204208657.72%659104563.06%213515611561528899478
6Crunch42100100121112010010057-22200000074350.625121931009278686116668676715377120467333515.15%23386.96%01490244360.99%1204208657.72%659104563.06%213515611561528899478
7Devils421000011011-12010000147-32200000064250.62510182810927868691668676715378729406531619.35%20385.00%01490244360.99%1204208657.72%659104563.06%213515611561528899478
8Griffins44000000215162200000091822000000124881.000213859019278686123668676715377120626926726.92%23291.30%21490244360.99%1204208657.72%659104563.06%213515611561528899478
9IceHogs430000101248220000006062100001064281.000121628029278686107668676715377622466920525.00%21385.71%01490244360.99%1204208657.72%659104563.06%213515611561528899478
10Marlies880000004984144000000204164400000029425161.0004986135039278686336668676715371364270167321237.50%330100.00%21490244360.99%1204208657.72%659104563.06%213515611561528899478
11Penguins41300000813-52110000045-12020000048-420.2508152300927868671668676715377224586426415.38%23482.61%01490244360.99%1204208657.72%659104563.06%213515611561528899478
12Phantoms42100001710-3210000014312110000037-450.62571118009278686846686767153710129767334514.71%32584.38%01490244360.99%1204208657.72%659104563.06%213515611561528899478
13Rocket84400000252324220000013103422000001213-180.5002548730092786862316686767153715336115147631117.46%51688.24%11490244360.99%1204208657.72%659104563.06%213515611561528899478
14Senators817000001117-64040000038-54130000089-120.12511172801927868616466867671537186481521625658.93%66887.88%11490244360.99%1204208657.72%659104563.06%213515611561528899478
Total7646210113424215092382112001131157441382590102112776511050.6912424176591129278686207066867671537147144598814065299517.96%4315487.47%61490244360.99%1204208657.72%659104563.06%213515611561528899478
16Wolves431000001073211000004402200000063360.750101929009278686102668676715378224317823521.74%13284.62%01490244360.99%1204208657.72%659104563.06%213515611561528899478
_Since Last GM Reset7646210113424215092382112001131157441382590102112776511050.6912424176591129278686207066867671537147144598814065299517.96%4315487.47%61490244360.99%1204208657.72%659104563.06%213515611561528899478
_Vs Conference281014001125970-111428001122538-1314860000034322250.4465999158139278686619668676715376181824205072072914.01%1882686.17%11490244360.99%1204208657.72%659104563.06%213515611561528899478
_Vs Division4042000021368056201100002623824203100000744232100.1251362403760592786861157668676715377582085577502904916.90%2412788.80%61490244360.99%1204208657.72%659104563.06%213515611561528899478

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
76105W4242417659207014714459881406112
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
7646211134242150
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
382112011311574
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
38259102112776
Derniers 10 Matchs
WLOTWOTL SOWSOL
540001
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
5299517.96%4315487.47%6
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
668676715379278686
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
1490244360.99%1204208657.72%659104563.06%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
213515611561528899478


Derniers Match Joués
Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
JourMatch Équipe Visiteuse Score Équipe Locale Score ST OT SO RI Lien
3 - 2018-09-072IceHogs0Monsters5WSommaire du Match
4 - 2018-09-0810IceHogs0Monsters1WSommaire du Match
6 - 2018-09-1027Monsters7Marlies2WSommaire du Match
9 - 2018-09-1332Penguins3Monsters1LSommaire du Match
11 - 2018-09-1547Penguins2Monsters3WSommaire du Match
17 - 2018-09-2172Monsters3Comets0WSommaire du Match
18 - 2018-09-2290Monsters3Devils2WSommaire du Match
22 - 2018-09-26102Monsters2Wolves1WSommaire du Match
24 - 2018-09-28112Monsters4Admirals0WSommaire du Match
25 - 2018-09-29120Monsters2IceHogs1WSommaire du Match
31 - 2018-10-05141Marlies2Monsters3WSommaire du Match
33 - 2018-10-07169Griffins0Monsters4WSommaire du Match
36 - 2018-10-10177Monsters2Americans1WSommaire du Match
38 - 2018-10-12182Rocket1Monsters4WSommaire du Match
39 - 2018-10-13192Rocket2Monsters4WSommaire du Match
45 - 2018-10-19223Monsters4Bears0WSommaire du Match
46 - 2018-10-20238Monsters2Bears0WSommaire du Match
52 - 2018-10-26266Marlies0Monsters7WSommaire du Match
54 - 2018-10-28293Monsters5Marlies1WSommaire du Match
57 - 2018-10-31301Marlies2Monsters4WSommaire du Match
59 - 2018-11-02308Crunch4Monsters3LXSommaire du Match
60 - 2018-11-03318Crunch3Monsters2LSommaire du Match
64 - 2018-11-07343Monsters3Phantoms2WSommaire du Match
66 - 2018-11-09354Monsters3Penguins4LSommaire du Match
67 - 2018-11-10369Monsters0Phantoms5LSommaire du Match
73 - 2018-11-16395Monsters0Americans3LSommaire du Match
74 - 2018-11-17404Americans2Monsters3WSommaire du Match
78 - 2018-11-21426Monsters5Griffins2WSommaire du Match
80 - 2018-11-23436Senators3Monsters1LSommaire du Match
81 - 2018-11-24449Senators2Monsters1LSommaire du Match
85 - 2018-11-28465Americans3Monsters2LSommaire du Match
87 - 2018-11-30477Griffins1Monsters5WSommaire du Match
88 - 2018-12-01492Monsters7Griffins2WSommaire du Match
95 - 2018-12-08531Comets2Monsters5WSommaire du Match
96 - 2018-12-09545Comets2Monsters5WSommaire du Match
99 - 2018-12-12553Monsters3Senators0WSommaire du Match
101 - 2018-12-14563Monsters3Crunch2WSommaire du Match
102 - 2018-12-15582Monsters3Devils2WSommaire du Match
108 - 2018-12-21610Monsters3Rocket2WSommaire du Match
109 - 2018-12-22616Monsters5Rocket3WSommaire du Match
113 - 2018-12-26647Marlies0Monsters6WSommaire du Match
114 - 2018-12-27653Wolves1Monsters2WSommaire du Match
116 - 2018-12-29675Wolves3Monsters2LSommaire du Match
122 - 2019-01-04688Monsters1Penguins4LSommaire du Match
123 - 2019-01-05702Monsters4Crunch2WSommaire du Match
126 - 2019-01-08713Monsters4Checkers3WXSommaire du Match
127 - 2019-01-09716Monsters5Checkers1WSommaire du Match
130 - 2019-01-12739Devils4Monsters3LXXSommaire du Match
131 - 2019-01-13749Devils3Monsters1LSommaire du Match
133 - 2019-01-15757Americans2Monsters3WSommaire du Match
136 - 2019-01-18769Monsters2Senators3LSommaire du Match
137 - 2019-01-19783Monsters1Senators2LSommaire du Match
138 - 2019-01-20799Monsters3Comets2WXXSommaire du Match
141 - 2019-01-23811Monsters2Americans1WSommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
143 - 2019-01-25819Admirals2Monsters1LXXSommaire du Match
145 - 2019-01-27841Admirals0Monsters3WSommaire du Match
149 - 2019-01-31855Rocket5Monsters4LSommaire du Match
150 - 2019-02-01859Rocket2Monsters1LSommaire du Match
151 - 2019-02-02868Monsters10Marlies0WSommaire du Match
156 - 2019-02-07896Senators1Monsters0LSommaire du Match
157 - 2019-02-08898Senators2Monsters1LSommaire du Match
162 - 2019-02-13934Monsters3Admirals2WSommaire du Match
164 - 2019-02-15950Monsters4Wolves2WSommaire du Match
165 - 2019-02-16960Monsters4IceHogs3WXXSommaire du Match
171 - 2019-02-22988Monsters2Americans3LXXSommaire du Match
172 - 2019-02-23996Bears3Monsters4WXXSommaire du Match
173 - 2019-02-241009Bears5Monsters1LSommaire du Match
178 - 2019-03-011028Phantoms2Monsters1LXXSommaire du Match
179 - 2019-03-021041Phantoms1Monsters3WSommaire du Match
183 - 2019-03-061066Monsters2Rocket3LSommaire du Match
185 - 2019-03-081078Monsters2Rocket5LSommaire du Match
186 - 2019-03-091090Monsters2Senators4LSommaire du Match
188 - 2019-03-111104Americans1Monsters4WSommaire du Match
191 - 2019-03-141114Checkers2Monsters8WSommaire du Match
192 - 2019-03-151115Checkers1Monsters4WSommaire du Match
194 - 2019-03-171145Monsters7Marlies1WSommaire 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
299,597$ 188,009$ 124,568$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 199,544$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 0 1,485$ 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
137646210113424215092382112001131157441382590102112776511052424176591129278686207066867671537147144598814065299517.96%4315487.47%61490244360.99%1204208657.72%659104563.06%213515611561528899478
Total Saison Régulière7646210113424215092382112001131157441382590102112776511052424176591129278686207066867671537147144598814065299517.96%4315487.47%61490244360.99%1204208657.72%659104563.06%213515611561528899478
Séries
1220164000004919301082000002191210820000028101832498313206121817246614315614621405121392396141149.93%1661093.98%338167356.61%36566654.80%16827960.22%509338516168266131
1220164000004919301082000002191210820000028101832498313206121817246614315614621405121392396141149.93%1661093.98%338167356.61%36566654.80%16827960.22%509338516168266131
Total Séries4032800000983860201640000042182420164000005620366498166264012243634493228631229242810242784792282289.93%3322093.98%6762134656.61%730133254.80%33655860.22%10186771032337533263