Monsters

GP: 25 | W: 20 | L: 4 | OTL: 1 | P: 41
GF: 81 | GA: 38 | PP%: 19.75% | PK%: 91.55%
DG: Patrick Auger | Morale : 70 | Moyenne d'Équipe : 58
Prochain matchs #395 vs Americans
La résolution de votre navigateur est trop petite pour cette page. Plusieurs informations sont cachées pour garder la page lisible.

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 LindbergX100.00845576788078827181637076557168177690
2David Kampf (R)X100.00765580807772807190656577557267136680
3Dylan Strome (R)X100.00635570827570707973707065557372171680
4Nick CousinsX100.00775573756966677668657378556564178680
5Oskar Lindblom (R)X100.00765571847072737650636565557070176670
6Chris KellyX100.00685578757768676450626061557575177630
7Nikita SoshnikovX100.00845578816762646550606162555252176620
8Daniel CatenacciX100.00595572626662695550555560557574176580
9Daniel AudetteX100.00585572676259695550555559557175176580
10Nick TarnaskyX100.00745558638179645550555555556465176580
11Mike BrownX100.00605566697569545550555555556970176580
12Zack StortiniX100.00645557618179745550555555556565176580
13Ryan HaggertyX100.00715569687569665550555555555050176570
14Colin White (R)X100.00565555555657576660555555557371162560
15Madison BoweyX100.00795579866974647825716075557878172710
16Mike ReillyX100.00755581865776588425776377557573178710
17Ryan SproulX100.00685566766779647425646268557070176660
18Brian LashoffX100.00555555605555785525555555556061173560
19Ville PokkaX100.00555557605757765725575757555353160560
Rayé
1Tim BozonX100.00745567627468645550555555555050126560
2Quinton HowdenX100.00565563656866695550555555555656125560
3Jayce Hawryluk (R)X100.00605570636762695550555555555050125550
4Matt Buckles (R)X100.00825582557954545550555555555050125550
5Akim Aliu (R)X100.00565555555859605550555555557575125550
6Brandon AldersonX100.00565555555758595550555555557472125540
7Buddy RobinsonX100.00565555555758585550555555557472125540
8Cody Kunyk (R)X100.00565555555758585550555555557371125540
9Zach O'Brien (R)X100.00705568555461685550555555555050125540
10Emil Pettersson (R)X100.00555555555555555550555555557571125540
11Stephen MacAulay (R)X100.00565559626866545550555555555050125540
12Lauri KorpikoskiX100.00555555555555555550555555557473125540
13Joshua WinquistX100.00565555555556555550555555555050125520
14Olivier Archambault (R)X100.00555562555454545550555555555050125520
15Mike SisloX100.00565555555555555550555555555050125520
16Mike WeberX100.00555555605555625525555555556970128550
17Josiah DidierX100.00555555605555595525555555555353125540
18Kyle BurroughsX100.00565556605656635625565656555353125540
19Robin Norell (R)X100.00555555605555675525555555555353125540
20Jeremy Roy (R)X100.00565555605555565525555555556262125540
21Brennan Menell (R)X100.00555555605555565525555555555555125540
22Will O'NeillX100.00575555605555675525555555555353125540
23John NegrinX100.00555555605555585525555555555353125530
MOYENNE D'ÉQUIPE100.0063556364646364604558575955636214658
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 Campbell100.0073778373707075706771556967171700
2Eamon McAdam100.0062707079656565656864556062176650
Rayé
1Jeff Malcolm100.0054645971585858585958555456125580
2Marcus Hogberg100.0055555555555555555555556565125550
3Filip Gustavsson (R)100.0055555555555555555555555060125540
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
1Mike ReillyMonsters (Clb)D24523283260293645122611.11%2058324.293141733119000191010.00%000000.9600000013
2Ryan SproulMonsters (Clb)D25123242230034283112293.23%2458123.271562299011095000.00%000000.8300000033
3Oscar LindbergMonsters (Clb)C2581321731537668122449.88%654021.6048122512211241183066.73%57100010.7800001220
4Oskar LindblomMonsters (Clb)LW2571219260162667154210.45%141316.523710251250002200040.63%3200000.9200000001
5Nick CousinsMonsters (Clb)C241081810100274864155415.63%539516.462249570112763061.42%32400000.9100000232
6Madison BoweyMonsters (Clb)D236915023547193261618.75%1755924.3253821100000190200.00%000000.5400100201
7Jake VirtanenColumbus Blue JacketsRW166814630029386415579.38%537523.4932518780117641059.63%16100100.7500000130
8Nikita SoshnikovMonsters (Clb)RW256814528033244383013.95%241516.6222412116000001076.19%2100000.6700000111
9David KampfMonsters (Clb)C957126207112481820.83%813414.990331121014300065.52%8700001.7800000300
10Dylan StromeMonsters (Clb)C219211360135857134415.79%234316.342028311012584164.42%32600000.6400000121
11Daniel AudetteMonsters (Clb)LW254610640161526102115.38%338815.53213581000002047.06%1700000.5200000011
12Daniel CatenacciMonsters (Clb)RW253369120171827131311.11%434413.780001180000150127.27%2200000.3500000011
13Brian LashoffMonsters (Clb)D25156635525860316.67%1839715.90123230000044000.00%000000.3000010011
14Nick TarnaskyMonsters (Clb)LW2512392603110124118.33%032613.05011027000011054.55%1100000.1800000000
15Mike BrownMonsters (Clb)RW25123-16010782512.50%01757.04101126000000025.00%800000.3400000000
16Chris KellyMonsters (Clb)C250220115914137190.00%21455.83000050001240050.53%9500000.2700001000
17Colin WhiteMonsters (Clb)C131122203621450.00%0685.23011040000321069.57%2300000.5900000000
18Ryan HaggertyMonsters (Clb)RW251123603194911.11%01024.1100011000030042.86%700000.3900000000
19Ville PokkaMonsters (Clb)D202027175252103620.00%1539519.80101557000059000.00%000000.1000010000
20Tim BozonMonsters (Clb)LW5011140304110.00%0367.2400000000000025.00%400000.5500000000
21Brendan LeipsicColumbus Blue JacketsC/LW1011000032000.00%02020.0801117000030073.33%1500001.0000000000
22Zack StortiniMonsters (Clb)C25000-120311010.00%1582.34000080000140062.50%3200000.0000000000
Stats d'équipe Total ou en Moyenne456771372141053172541743962817145312.26%133680114.9130528219011343472484718362.24%175600110.6300122121815
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)2520410.9131.55146808384370400.0000250511
2Eamon McAdamMonsters (Clb)10001.0000.0032000100000.0000025000
Stats d'équipe Total ou en Moyenne2620410.9151.52150108384470400.00002525511


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 Salaire Année 2 Salaire Année 3 Salaire Année 4 Salaire Année 5 Salaire Année 6 Salaire Année 7 Salaire Année 8 Salaire Année 9 Salaire Année 10 Link
Akim AliuMonsters (Clb)RW271989-04-23Yes225 Lbs6 ft4NoNoNo3Avec RestrictionPro & Farm500,000$0$0$No500,000$500,000$
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$0$No300,000$300,000$300,000$
Brian LashoffMonsters (Clb)D261990-07-15No212 Lbs6 ft3NoNoNo4Avec RestrictionPro & Farm300,000$0$0$No300,000$300,000$300,000$
Buddy RobinsonMonsters (Clb)RW251991-09-30No235 Lbs6 ft5NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No300,000$
Chris KellyMonsters (Clb)C361980-11-11No198 Lbs6 ft0NoNoNo2Sans RestrictionPro & Farm300,000$0$0$No300,000$
Cody KunykMonsters (Clb)RW261990-05-20Yes195 Lbs5 ft11NoNoNo3Avec RestrictionPro & Farm500,000$0$0$No500,000$500,000$
Colin WhiteMonsters (Clb)C191997-01-30Yes190 Lbs6 ft1NoNoNo4Contrat d'EntréePro & Farm900,000$0$0$No900,000$900,000$900,000$
Daniel AudetteMonsters (Clb)LW201996-05-06No176 Lbs5 ft8NoNoNo3Contrat d'EntréePro & Farm500,000$0$0$No500,000$500,000$
Daniel CatenacciMonsters (Clb)RW231993-03-09No186 Lbs5 ft9NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No300,000$
David KampfMonsters (Clb)C221995-01-12Yes191 Lbs6 ft2NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No300,000$300,000$300,000$
Dylan StromeMonsters (Clb)C191997-03-07Yes185 Lbs6 ft3NoNoNo4Contrat d'EntréePro & Farm900,000$0$0$No900,000$900,000$900,000$
Eamon McAdamMonsters (Clb)G221994-09-23No199 Lbs6 ft3NoNoNo3Contrat d'EntréePro & Farm300,000$0$0$No300,000$300,000$
Emil PetterssonMonsters (Clb)C221994-01-14Yes176 Lbs6 ft2NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No300,000$300,000$300,000$
Filip GustavssonMonsters (Clb)G181998-06-07Yes185 Lbs6 ft2NoNoNo4Contrat d'EntréePro & Farm500,000$0$0$No500,000$500,000$500,000$
Jack CampbellMonsters (Clb)G251992-01-09No195 Lbs6 ft3NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Jayce HawrylukMonsters (Clb)LW211996-01-01Yes188 Lbs5 ft10NoNoNo3Contrat d'EntréePro & Farm500,000$0$0$No500,000$500,000$
Jeff MalcolmMonsters (Clb)G271989-04-13No179 Lbs6 ft2NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No300,000$
Jeremy RoyMonsters (Clb)D191997-05-14Yes187 Lbs6 ft0NoNoNo4Contrat d'EntréePro & Farm500,000$0$0$No500,000$500,000$500,000$
John NegrinMonsters (Clb)D271989-03-25No194 Lbs6 ft2NoNoNo3Avec RestrictionPro & Farm500,000$0$0$No500,000$500,000$
Joshua WinquistMonsters (Clb)LW231993-09-06No185 Lbs5 ft11NoNoNo3Avec RestrictionPro & Farm300,000$0$0$No300,000$300,000$
Josiah DidierMonsters (Clb)D231993-04-08No203 Lbs6 ft2NoNoNo3Avec RestrictionPro & Farm300,000$0$0$No300,000$300,000$
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$0$No300,000$300,000$300,000$
Matt BucklesMonsters (Clb)C211995-05-05Yes218 Lbs6 ft3NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No300,000$300,000$300,000$
Mike BrownMonsters (Clb)RW311985-06-23No205 Lbs5 ft11NoNoNo1Sans RestrictionPro & Farm300,000$0$0$No
Mike ReillyMonsters (Clb)D231993-07-13No156 Lbs5 ft11NoNoNo4Avec RestrictionPro & Farm500,000$0$0$No500,000$500,000$500,000$
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$0$No300,000$300,000$
Nick TarnaskyMonsters (Clb)LW321984-11-24No230 Lbs6 ft2NoNoNo4Sans RestrictionPro & Farm300,000$0$0$No300,000$300,000$300,000$
Nikita SoshnikovMonsters (Clb)RW231993-10-14No183 Lbs5 ft11NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No300,000$
Olivier ArchambaultMonsters (Clb)LW231993-02-15Yes176 Lbs5 ft11NoNoNo4Avec RestrictionPro & Farm500,000$0$0$No500,000$500,000$500,000$
Oscar LindbergMonsters (Clb)C251991-10-28No195 Lbs6 ft1NoNoNo3Avec RestrictionPro & Farm500,000$0$0$No500,000$500,000$
Oskar LindblomMonsters (Clb)LW201996-08-15Yes192 Lbs6 ft1NoNoNo4Contrat d'EntréePro & Farm500,000$0$0$No500,000$500,000$500,000$
Quinton HowdenMonsters (Clb)C241992-01-20No189 Lbs6 ft2NoNoNo3Avec RestrictionPro & Farm300,000$0$0$No300,000$300,000$
Robin NorellMonsters (Clb)D211995-02-17Yes195 Lbs5 ft11NoNoNo3Contrat d'EntréePro & Farm300,000$0$0$No300,000$300,000$
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$0$No300,000$300,000$
Stephen MacAulayMonsters (Clb)C241992-04-20Yes182 Lbs6 ft2NoNoNo4Avec RestrictionPro & Farm500,000$0$0$No500,000$500,000$500,000$
Tim BozonMonsters (Clb)LW221994-03-24No196 Lbs6 ft1NoNoNo3Contrat d'EntréePro & Farm300,000$0$0$No300,000$300,000$
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$0$No500,000$500,000$500,000$
Zack StortiniMonsters (Clb)C311985-09-10No230 Lbs6 ft4NoNoNo3Sans RestrictionPro & Farm500,000$0$0$No500,000$500,000$
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
4724.00196 Lbs6 ft12.77427,678$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Oskar LindblomOscar LindbergNikita Soshnikov40122
2Daniel AudetteNick CousinsMike Brown30122
3Nick TarnaskyDylan StromeDaniel Catenacci20122
4David KampfRyan Haggerty10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Madison BoweyMike Reilly40122
2Ryan SproulVille Pokka30122
3Brian LashoffMadison Bowey20122
4Mike ReillyRyan Sproul10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Oskar LindblomOscar LindbergNikita Soshnikov60122
2Daniel AudetteNick CousinsMike Brown40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Madison BoweyMike Reilly60122
2Ryan SproulVille Pokka40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Oscar LindbergNick Cousins60122
2Dylan StromeDavid Kampf40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Madison BoweyMike Reilly60122
2Ryan SproulVille Pokka40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Oscar Lindberg60122Madison BoweyMike Reilly60122
2Nick Cousins40122Ryan SproulVille Pokka40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Oscar LindbergNick Cousins60122
2Dylan StromeDavid Kampf40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Madison BoweyMike Reilly60122
2Ryan SproulVille Pokka40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Oskar LindblomOscar LindbergNikita SoshnikovMadison BoweyMike Reilly
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Oskar LindblomOscar LindbergNikita SoshnikovMadison BoweyMike Reilly
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Chris Kelly, Zack Stortini, Daniel CatenacciChris Kelly, Zack StortiniDaniel Catenacci
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Brian Lashoff, Ville Pokka, Madison BoweyBrian LashoffVille Pokka, Madison Bowey
Tirs de Pénalité
Oscar Lindberg, Nick Cousins, Dylan Strome, David Kampf, 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
1Admirals11000000404000000000001100000040421.00047110129292302522719922308161212325.00%30100.00%050980563.23%38463660.38%20233161.03%721529487167293159
2Americans11000000211000000000001100000021121.00024600292923029227199223011616151218.33%8187.50%050980563.23%38463660.38%20233161.03%721529487167293159
3Bears22000000606000000000002200000060641.000611170229292304222719922303517183414428.57%90100.00%050980563.23%38463660.38%20233161.03%721529487167293159
4Comets11000000303000000000001100000030321.00034701292923022227199223016719237114.29%70100.00%050980563.23%38463660.38%20233161.03%721529487167293159
5Crunch2010010057-22010010057-20000000000010.2505813002929230582271992230339263613215.38%13284.62%050980563.23%38463660.38%20233161.03%721529487167293159
6Devils11000000321000000000001100000032121.0003690029292301922719922302478206233.33%4175.00%050980563.23%38463660.38%20233161.03%721529487167293159
7Griffins11000000404110000004040000000000021.00048120129292302622719922303182624500.00%60100.00%050980563.23%38463660.38%20233161.03%721529487167293159
8IceHogs33000000817220000006061100000021161.000811190229292307322719922306418404711436.36%18194.44%050980563.23%38463660.38%20233161.03%721529487167293159
9Marlies55000000267193300000014410220000001239101.00026457101292923018322719922308026489422836.36%220100.00%250980563.23%38463660.38%20233161.03%721529487167293159
10Penguins3120000079-22110000045-11010000034-120.333713200029292305822719922305020394022313.64%17288.24%050980563.23%38463660.38%20233161.03%721529487167293159
11Phantoms2110000037-4000000000002110000037-420.500358002929230422271992230511343301715.88%19478.95%050980563.23%38463660.38%20233161.03%721529487167293159
12Rocket22000000835220000008350000000000041.00081523002929230552271992230258244218316.67%12191.67%150980563.23%38463660.38%20233161.03%721529487167293159
Total25204001008138431292001004119221311200000401921410.8208114022108292923064922719922304471443214341623219.75%1421291.55%350980563.23%38463660.38%20233161.03%721529487167293159
14Wolves11000000211000000000001100000021121.000235002929230172271992230194817300.00%40100.00%050980563.23%38463660.38%20233161.03%721529487167293159
_Since Last GM Reset25204001008138431292001004119221311200000401921410.8208114022108292923064922719922304471443214341623219.75%1421291.55%350980563.23%38463660.38%20233161.03%721529487167293159
_Vs Conference1054001002425-141200100912-36420000015132110.550244367022929230219227199223019366134160721216.67%62985.48%050980563.23%38463660.38%20233161.03%721529487167293159
_Vs Division11210000045182780000000311417321000001441040.1824580125022929230351227199223018057140211701420.00%61493.44%350980563.23%38463660.38%20233161.03%721529487167293159

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
2541L28114022164944714432143408
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
2520401008138
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
129201004119
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
1311200004019
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
1623219.75%1421291.55%3
Tirs en 1e PériodeTirs en 2e PériodeTirs en 3e PériodeTirs en 4e PériodeButs en 1e PériodeButs en 2e PériodeButs en 3e PériodeButs en 4e Période
22719922302929230
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
50980563.23%38463660.38%20233161.03%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
721529487167293159


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 - 2018-11-16395Monsters-Americans-
74 - 2018-11-17404Americans-Monsters-
78 - 2018-11-21426Monsters-Griffins-
80 - 2018-11-23436Senators-Monsters-
81 - 2018-11-24449Senators-Monsters-
85 - 2018-11-28465Americans-Monsters-
87 - 2018-11-30477Griffins-Monsters-
88 - 2018-12-01492Monsters-Griffins-
95 - 2018-12-08531Comets-Monsters-
96 - 2018-12-09545Comets-Monsters-
99 - 2018-12-12553Monsters-Senators-
101 - 2018-12-14563Monsters-Crunch-
102 - 2018-12-15582Monsters-Devils-
108 - 2018-12-21610Monsters-Rocket-
109 - 2018-12-22616Monsters-Rocket-
113 - 2018-12-26647Marlies-Monsters-
114 - 2018-12-27653Wolves-Monsters-
116 - 2018-12-29675Wolves-Monsters-
122 - 2019-01-04688Monsters-Penguins-
123 - 2019-01-05702Monsters-Crunch-
126 - 2019-01-08713Monsters-Checkers-
127 - 2019-01-09716Monsters-Checkers-
130 - 2019-01-12739Devils-Monsters-
131 - 2019-01-13749Devils-Monsters-
133 - 2019-01-15757Americans-Monsters-
136 - 2019-01-18769Monsters-Senators-
137 - 2019-01-19783Monsters-Senators-
138 - 2019-01-20799Monsters-Comets-
141 - 2019-01-23811Monsters-Americans-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
143 - 2019-01-25819Admirals-Monsters-
145 - 2019-01-27841Admirals-Monsters-
149 - 2019-01-31855Rocket-Monsters-
150 - 2019-02-01859Rocket-Monsters-
151 - 2019-02-02868Monsters-Marlies-
156 - 2019-02-07896Senators-Monsters-
157 - 2019-02-08898Senators-Monsters-
162 - 2019-02-13934Monsters-Admirals-
164 - 2019-02-15950Monsters-Wolves-
165 - 2019-02-16960Monsters-IceHogs-
171 - 2019-02-22988Monsters-Americans-
172 - 2019-02-23996Bears-Monsters-
173 - 2019-02-241009Bears-Monsters-
178 - 2019-03-011028Phantoms-Monsters-
179 - 2019-03-021041Phantoms-Monsters-
183 - 2019-03-061066Monsters-Rocket-
185 - 2019-03-081078Monsters-Rocket-
186 - 2019-03-091090Monsters-Senators-
188 - 2019-03-111104Americans-Monsters-
191 - 2019-03-141114Checkers-Monsters-
192 - 2019-03-151115Checkers-Monsters-
194 - 2019-03-171145Monsters-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
115,801$ 201,009$ 133,818$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 78,664$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 122 1,552$ 189,344$




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
1325204001008138431292001004119221311200000401921418114022108292923064922719922304471443214341623219.75%1421291.55%350980563.23%38463660.38%20233161.03%721529487167293159
Total Saison Régulière25204001008138431292001004119221311200000401921418114022108292923064922719922304471443214341623219.75%1421291.55%350980563.23%38463660.38%20233161.03%721529487167293159
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