Monsters

GP: 82 | W: 55 | L: 23 | OTL: 4 | P: 114
GF: 381 | GA: 278 | PP%: 23.58% | PK%: 77.09%
DG: Paul-André Desrochers | Morale : 50 | Moyenne d'Équipe : 47
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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
1David DesharnaisXX100.00473588735367806486676163536154050630
2Scottie UpshallXX100.00704379756961795542525874487466050630
3Patrick EavesXX100.00484387626971486740587550537264050610
4Linden VeyXX100.00503590726158375660565561514439050560
5Matt MartinX100.00916569627754544858484857484744050550
6Tanner GlassXX100.00675667677455374250404460486759050530
7Lucas LessioX100.00533586657349334435404762524036050510
8Cal O'ReillyX100.00463595716052353750383558564742050480
9Jordan GreenwayXX100.00523595608153353735383556483532050470
10Jordan Kyrou (R)XX100.00454545455445454545454545453230050450
11Jesse Gabrielle (R)X100.00404040407140404040404040403230050420
12Ryan Kujawinski (R)X100.00394343437137373943393943413230050420
13Steven KampferX100.00745075616268384035384174484842050570
14Adam PardyX100.00563573597858404235453968475649050560
15Adam ClendeningX100.00563583666365364535474366484136050550
16Ethan Bear (R)X100.00493582686856364635464558483532050530
17Dominik Masin (R)X100.00414545456139394145414145433230050440
18Caleb Jones (R)X100.00404040406740404040404040403230050420
Rayé
1Carter Verhaeghe (R)X100.00394343435637373943393943413230050410
2Linus Lindstrom (R)X100.00404040404940404040404040403230050410
3Matt Buckles (R)X100.00364040407135353640363640383230050400
4Nick Moutrey (R)XX100.00364040407235353640363640383230050400
5Dmytro Timashov (R)X100.00333737376133333337333337353230050370
6Connor Hall (R)X100.00434343436343434343434343433230050440
7Niklas Hansson (R)X100.00394343435337373943393943413230050420
8Mason Geertsen (R)X100.00364040406635353640363640383230050410
9Connor Hobbs (R)X100.00373737376437373737373737373230050400
10Ziyat Paigin (R)X100.00373737377037373737373737373230050400
11Anton Cederholm (R)X100.00333737376733333337333337353230050390
12Teemu Kivihalme (R)X100.00333737374533333337333337353230050370
MOYENNE D'ÉQUIPE100.0047415952654741424342425044403705047
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
1Reto Berra100.0046456184434646414565704540050510
2Tyler Parsons (R)100.0045454567454545454545453230050460
Rayé
1Joacim Eriksson100.0040454169393737383737363532050420
2Calvin Petersen (R)100.0035373567343333333333333230050380
MOYENNE D'ÉQUIPE100.004243467240404039404546363305044
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Ian Laperriere65707264687068QUE441500,000$


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
1Patrick EavesMonsters (Col)LW/RW7860651257927539893377822617.80%3137017.57161632802500000329251.92%10400061.82170101259
2Linden VeyMonsters (Col)C/RW82477412161160472102496819118.88%23156619.10724313826730392004358.37%178700011.5526000697
3Scottie UpshallMonsters (Col)LW/RW6853631166085151861223018922517.61%26139920.5812132560232112142468545.83%12000111.663400111104
4Colin WhiteColoradoC/RW572244662622064771675614213.17%393916.4841115301770112665236.05%23300001.4100000444
5Adam ClendeningMonsters (Col)D829566531500957512139817.44%81180622.0461521652490222265210.00%000000.7211000123
6Slater KoekkoekColoradoD69125163383807468110316910.91%66146721.2741317432200000129200.00%000000.8600000312
7Ivan BarbashevColoradoC/LW4327356238100261171734710315.61%1092421.49411153713612341735159.47%97200001.3401000354
8Jakub VranaColoradoLW/RW3229225120201636145438520.00%350515.8084122994000013254.35%4600012.0202000532
9Adam PardyMonsters (Col)D8294049315201157310049719.00%102171420.91391239265000123801100.00%100000.5700000004
10Ethan BearMonsters (Col)D829334248560815869244413.04%51139116.97371025940000123110.00%000000.6011000213
11Tanner GlassMonsters (Col)LW/RW82192342159420113711284010614.84%14114713.992571310410171671058.95%9500000.7323103144
12Steven KampferMonsters (Col)D71928374114301817011525807.83%85148920.984711341100114222110.00%000000.5000105202
13Matt MartinMonsters (Col)LW73627339140201774211433805.26%693712.841341670000070166.23%7700000.7000301012
14Lucas LessioMonsters (Col)LW82191130114034701463810513.01%1391111.1121355100061153138.33%6000000.6604000200
15Cal O'ReillyMonsters (Col)C8282129126071098319759.64%7107713.141456900001620052.74%111300000.5402000120
16Carl DahlstromColoradoD609182726260544482195410.98%75117419.57448301650220167100.00%000000.4600000020
17Jordan GreenwayMonsters (Col)LW/RW7151924910035285523379.09%973110.300225950000661150.85%5900000.6611000002
18David DesharnaisMonsters (Col)C/LW208152380094665184612.31%640520.2913420660003740067.22%47900001.1304000211
19Anthony DuclairColoradoLW/RW5448700792441316.67%09819.60011314000081044.44%900001.6300000101
20Jordan KyrouMonsters (Col)C/RW82448-1449568337013535.71%085310.41000030000021047.14%28000000.1900100000
21Dominik MasinMonsters (Col)D272571149543892822.22%2044516.52000119000035100.00%000000.3100010000
22Jesse GabrielleMonsters (Col)LW76257-141606611241188.33%27349.670000310000330047.95%7300000.1900000000
23Ryan KujawinskiMonsters (Col)C55347-1514034302321513.04%44778.6900000000000043.86%44000000.2900000000
24Carter VerhaegheMonsters (Col)C19044095101210130.00%01759.2200000000020047.31%18600000.4600100000
25Caleb JonesMonsters (Col)D13000101402241000.00%1019815.240000200005000.00%000000.0000000000
26Dmytro TimashovMonsters (Col)LW6000-300400020.00%0579.5200001000000050.00%200000.0000000000
27Nick MoutreyMonsters (Col)C/LW9000-420911010.00%0859.4400002000020055.56%900000.0000000000
Stats d'équipe Total ou en Moyenne15083756711046494915105161615132722762193313.78%6192408615.978215323557928466915532450492254.79%614500190.8711367210565054
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
1Tyler ParsonsMonsters (Col)40231030.8913.1821712211510530000.588173052030
2Jonas GustavssonColorado3119700.8623.33153403856180110.833123011010
3Reto BerraMonsters (Col)2313610.8643.51124800735370300.75082219000
Stats d'équipe Total ou en Moyenne94552340.8763.3149542527322080410.703378282040


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
Adam ClendeningMonsters (Col)D241992-10-26No196 Lbs6 ft0NoNoNo1Avec RestrictionPro & Farm818,000$81,800$0$NoLien
Adam PardyMonsters (Col)D331984-03-29No227 Lbs6 ft4NoNoNo5Sans RestrictionPro & Farm1,000,000$100,000$0$NoLien
Anton CederholmMonsters (Col)D221995-02-21Yes204 Lbs6 ft1NoNoNo2Avec RestrictionPro & Farm615,000$61,500$0$NoLien
Cal O'ReillyMonsters (Col)C311986-09-30No188 Lbs6 ft0NoNoNo1Sans RestrictionPro & Farm700,000$70,000$0$NoLien
Caleb JonesMonsters (Col)D201997-06-06Yes205 Lbs6 ft1NoNoNo4Contrat d'EntréePro & Farm655,000$65,500$0$NoLien
Calvin PetersenMonsters (Col)G221994-10-19Yes183 Lbs6 ft2NoNoNo2Avec RestrictionPro & Farm525,000$52,500$0$NoLien
Carter VerhaegheMonsters (Col)C221995-08-14Yes181 Lbs6 ft1NoNoNo2Avec RestrictionPro & Farm743,000$74,300$0$NoLien
Connor HallMonsters (Col)D191998-02-21Yes192 Lbs6 ft4NoNoNo4Contrat d'EntréePro & Farm700,000$70,000$0$NoLien
Connor HobbsMonsters (Col)D201997-01-04Yes197 Lbs6 ft1NoNoNo4Contrat d'EntréePro & Farm730,000$73,000$0$NoLien
David DesharnaisMonsters (Col)C/LW311986-09-14No180 Lbs5 ft7YesNoNo6Sans RestrictionPro & Farm2,200,000$220,000$0$NoLien
Dmytro TimashovMonsters (Col)LW211996-10-01Yes192 Lbs5 ft9NoNoNo2Contrat d'EntréePro & Farm925,000$92,500$0$NoLien
Dominik MasinMonsters (Col)D211996-02-01Yes189 Lbs6 ft2NoNoNo2Contrat d'EntréePro & Farm667,000$66,700$0$NoLien
Ethan BearMonsters (Col)D201997-06-26Yes209 Lbs5 ft11NoNoNo4Contrat d'EntréePro & Farm655,000$65,500$0$NoLien
Jesse GabrielleMonsters (Col)LW201997-06-17Yes205 Lbs6 ft0NoNoNo4Contrat d'EntréePro & Farm742,500$74,250$0$NoLien
Joacim ErikssonMonsters (Col)G271990-04-09No189 Lbs6 ft1NoNoNo4Avec RestrictionPro & Farm750,000$75,000$0$NoLien
Jordan GreenwayMonsters (Col)LW/RW201997-02-16No226 Lbs6 ft6NoNoNo3Contrat d'EntréePro & Farm825,000$82,500$0$NoLien
Jordan KyrouMonsters (Col)C/RW191998-05-05Yes177 Lbs6 ft0NoNoNo4Contrat d'EntréePro & Farm742,500$74,250$0$NoLien
Linden VeyMonsters (Col)C/RW261991-07-17No189 Lbs6 ft0YesNoNo2Avec RestrictionPro & Farm479,150$47,915$0$NoLien
Linus LindstromMonsters (Col)C191998-01-08Yes168 Lbs5 ft11NoNoNo4Contrat d'EntréePro & Farm650,000$65,000$0$NoLien
Lucas LessioMonsters (Col)LW241993-01-23No212 Lbs6 ft1NoNoNo3Avec RestrictionPro & Farm600,000$60,000$0$NoLien
Mason GeertsenMonsters (Col)D221995-04-19Yes199 Lbs6 ft3NoNoNo2Avec RestrictionPro & Farm650,000$65,000$0$NoLien
Matt BucklesMonsters (Col)C221995-05-05Yes205 Lbs6 ft1NoNoNo2Avec RestrictionPro & Farm650,000$65,000$0$NoLien
Matt MartinMonsters (Col)LW281989-05-08No220 Lbs6 ft3YesNoNo6Sans RestrictionPro & Farm850,000$85,000$0$NoLien
Nick MoutreyMonsters (Col)C/LW221995-06-24Yes208 Lbs6 ft2NoNoNo2Avec RestrictionPro & Farm925,000$92,500$0$NoLien
Niklas HanssonMonsters (Col)D221995-01-08Yes175 Lbs6 ft0NoNoNo2Avec RestrictionPro & Farm700,000$70,000$0$NoLien
Patrick EavesMonsters (Col)LW/RW331984-05-01No202 Lbs5 ft10YesNoNo6Sans RestrictionPro & Farm1,850,000$185,000$0$NoLien
Reto BerraMonsters (Col)G301987-01-03No218 Lbs6 ft4YesNoNo4Sans RestrictionPro & Farm700,000$70,000$0$NoLien
Ryan KujawinskiMonsters (Col)C221995-03-30Yes204 Lbs6 ft1NoNoNo2Avec RestrictionPro & Farm667,000$66,700$0$NoLien
Scottie UpshallMonsters (Col)LW/RW331983-10-07No200 Lbs6 ft0NoNoNo3Sans RestrictionPro & Farm1,650,000$165,000$0$NoLien
Steven KampferMonsters (Col)D291988-09-24No195 Lbs5 ft11YesNoNo6Sans RestrictionPro & Farm750,000$75,000$0$NoLien
Tanner GlassMonsters (Col)LW/RW331983-11-29No213 Lbs6 ft1NoNoNo1Sans RestrictionPro & Farm600,000$60,000$0$NoLien
Teemu KivihalmeMonsters (Col)D221995-06-14Yes161 Lbs5 ft11NoNoNo2Avec RestrictionPro & Farm525,000$52,500$0$NoLien
Tyler ParsonsMonsters (Col)G201997-09-18Yes185 Lbs6 ft1NoNoNo4Contrat d'EntréePro & Farm742,500$74,250$0$NoLien
Ziyat PaiginMonsters (Col)D221995-02-08Yes209 Lbs6 ft6NoNoNo4Avec RestrictionPro & Farm792,500$79,250$0$NoLien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
3424.15197 Lbs6 ft13.21816,887$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Jordan GreenwayLinden VeyPatrick Eaves40122
2Matt MartinDavid DesharnaisScottie Upshall30122
3Lucas LessioCal O'ReillyTanner Glass20122
4Jesse GabrielleRyan KujawinskiJordan Kyrou10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Steven KampferAdam Pardy40122
2Ethan BearAdam Clendening30122
3Caleb JonesDominik Masin20122
4Steven KampferAdam Pardy10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Scottie UpshallLinden VeyPatrick Eaves60122
2Lucas LessioDavid DesharnaisJordan Greenway40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Steven KampferEthan Bear60122
2Adam PardyAdam Clendening40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1David DesharnaisScottie Upshall60122
2Linden VeyLucas Lessio40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Steven KampferEthan Bear60122
2Adam PardyAdam Clendening40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1David Desharnais60122Steven KampferAdam Pardy60122
2Cal O'Reilly40122Ethan BearAdam Clendening40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1David DesharnaisPatrick Eaves60122
2Linden VeyScottie Upshall40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Steven KampferAdam Pardy60122
2Ethan BearAdam Clendening40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Patrick EavesLinden VeyScottie UpshallSteven KampferEthan Bear
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Lucas LessioDavid DesharnaisScottie UpshallSteven KampferAdam Pardy
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Linden Vey, David Desharnais, Cal O'ReillyJordan Greenway, Tanner GlassLucas Lessio
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Ethan Bear, Dominik Masin, Adam PardyEthan BearDominik Masin, Adam Pardy
Tirs de Pénalité
David Desharnais, Patrick Eaves, Linden Vey, Tanner Glass, Lucas Lessio
Gardien
#1 : Reto Berra, #2 : Tyler Parsons


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
1Admirals32100000151231010000034-122000000128440.6671526410015114085127685593191657942137529222.22%11372.73%01460261055.94%1288230955.78%791146753.92%2109144417556031095575
2Baby Hawks532000002218432100000141042110000088060.60022416301151140851215285593191657128384811121523.81%23769.57%01460261055.94%1288230955.78%791146753.92%2109144417556031095575
3Bears22000000853110000003211100000053241.000814220015114085126985593191657481418429333.33%9188.89%01460261055.94%1288230955.78%791146753.92%2109144417556031095575
4Bruins21100000761110000005231010000024-220.50071219001511408512628559319165733622367114.29%11281.82%01460261055.94%1288230955.78%791146753.92%2109144417556031095575
5Cabaret Lady Mary Ann21100000990110000005411010000045-120.5009162500151140851293855931916575213184510110.00%8537.50%01460261055.94%1288230955.78%791146753.92%2109144417556031095575
6Caroline220000001239110000005141100000072541.00012223400151140851294855931916574318233313323.08%9277.78%01460261055.94%1288230955.78%791146753.92%2109144417556031095575
7Chiefs413000001215-320200000511-62110000074320.2501219310015114085121018559319165712230577315533.33%21385.71%01460261055.94%1288230955.78%791146753.92%2109144417556031095575
8Chill43000001191092100000186222000000114770.875193352001511408512151855931916579124388915533.33%180100.00%11460261055.94%1288230955.78%791146753.92%2109144417556031095575
9Comets321000001587211000007701100000081740.66715304500151140851291855931916577830186314535.71%9277.78%01460261055.94%1288230955.78%791146753.92%2109144417556031095575
10Cougars202000001012-21010000056-11010000056-100.000101727001511408512438559319165782164034600.00%14750.00%01460261055.94%1288230955.78%791146753.92%2109144417556031095575
11Crunch21100000642110000004131010000023-120.50069150015114085126385593191657335452915426.67%100100.00%01460261055.94%1288230955.78%791146753.92%2109144417556031095575
12Heat32100000171431100000083521100000911-240.66717314800151140851210885593191657722527598225.00%11463.64%01460261055.94%1288230955.78%791146753.92%2109144417556031095575
13Jayhawks30200001816-81000000145-120200000411-710.167815230015114085128685593191657932164609111.11%17382.35%11460261055.94%1288230955.78%791146753.92%2109144417556031095575
14Las Vegas321000001183211000008621100000032140.66711203100151140851299855931916578416286211218.18%13376.92%11460261055.94%1288230955.78%791146753.92%2109144417556031095575
15Manchots220000001046110000006331100000041341.00010172700151140851265855931916573315214210110.00%8187.50%01460261055.94%1288230955.78%791146753.92%2109144417556031095575
16Marlies220000001266110000006331100000063341.00012223400151140851290855931916577724293613538.46%11281.82%01460261055.94%1288230955.78%791146753.92%2109144417556031095575
17Minnesota430000012218422000000853210000011413170.8752236580015114085121308559319165711027638116637.50%24962.50%01460261055.94%1288230955.78%791146753.92%2109144417556031095575
18Monarchs321000001715222000000161061010000015-440.66717314800151140851299855931916571122530537114.29%15473.33%11460261055.94%1288230955.78%791146753.92%2109144417556031095575
19Monsters2010100078-1100010005411010000024-220.500712191015114085126885593191657561216371119.09%8275.00%01460261055.94%1288230955.78%791146753.92%2109144417556031095575
20Oceanics52200010252322110000012102311000101313060.6002542670015114085121458559319165716456489624625.00%24962.50%11460261055.94%1288230955.78%791146753.92%2109144417556031095575
21Oil Kings3300000013211220000007251100000060661.000132538011511408512104855931916576813205417529.41%10280.00%01460261055.94%1288230955.78%791146753.92%2109144417556031095575
22Phantoms2200000014212110000007071100000072541.0001427410115114085128385593191657572121404375.00%80100.00%01460261055.94%1288230955.78%791146753.92%2109144417556031095575
23Rocket22000000615110000004131100000020241.0006111701151140851265855931916573310284511327.27%13192.31%01460261055.94%1288230955.78%791146753.92%2109144417556031095575
24Senators220000001367110000006511100000071641.000132538001511408512618559319165740926409111.11%11190.91%01460261055.94%1288230955.78%791146753.92%2109144417556031095575
25Sharks311000101614211000000532201000101111040.6671626420015114085121208559319165710934277021523.81%10280.00%01460261055.94%1288230955.78%791146753.92%2109144417556031095575
26Sound Tigers22000000954110000004131100000054141.0009142300151140851279855931916573818263513215.38%8275.00%11460261055.94%1288230955.78%791146753.92%2109144417556031095575
27Spiders20100001811-31000000156-11010000035-210.250816240015114085126285593191657671821356233.33%11463.64%01460261055.94%1288230955.78%791146753.92%2109144417556031095575
28Stars4300001017710220000009272100001085381.000172643011511408512122855931916576218266615213.33%8187.50%01460261055.94%1288230955.78%791146753.92%2109144417556031095575
29Thunder2010001068-2100000103211010000036-320.50061016001511408512528559319165760161441600.00%70100.00%01460261055.94%1288230955.78%791146753.92%2109144417556031095575
Total8250230104438127810341288010131961296741221500031185149361140.6953816721053151511408512272385593191657220961592116023528323.58%3718577.09%61460261055.94%1288230955.78%791146753.92%2109144417556031095575
31Wolf Pack220000001587110000009451100000064241.0001527420015114085129085593191657702222437114.29%11372.73%01460261055.94%1288230955.78%791146753.92%2109144417556031095575
_Since Last GM Reset8250230104438127810341288010131961296741221500031185149361140.6953816721053151511408512272385593191657220961592116023528323.58%3718577.09%61460261055.94%1288230955.78%791146753.92%2109144417556031095575
_Vs Conference422514000121801354522156000019364292010800011877116540.64318031849804151140851213518559319165710602805058151814424.31%1904974.21%21460261055.94%1288230955.78%791146753.92%2109144417556031095575
_Vs Division2682000101179126135100000564412133100010614714180.346117197314021511408512801855931916576771932805161062927.36%1182975.42%21460261055.94%1288230955.78%791146753.92%2109144417556031095575

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
82114W4381672105327232209615921160215
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
8250231044381278
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
412881013196129
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
4122150031185149
Derniers 10 Matchs
WLOTWOTL SOWSOL
810001
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
3528323.58%3718577.09%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
855931916571511408512
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
1460261055.94%1288230955.78%791146753.92%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
2109144417556031095575


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
2 - 2018-10-0413Minnesota1Monsters2WSommaire du Match
4 - 2018-10-0627Phantoms0Monsters7WSommaire du Match
7 - 2018-10-0938Monsters2Monsters4LSommaire du Match
9 - 2018-10-1146Monsters2Crunch3LSommaire du Match
11 - 2018-10-1370Heat3Monsters8WSommaire du Match
14 - 2018-10-1679Monsters6Wolf Pack4WSommaire du Match
16 - 2018-10-1891Monsters3Spiders5LSommaire du Match
18 - 2018-10-20103Monsters7Caroline2WSommaire du Match
20 - 2018-10-22118Monsters7Phantoms2WSommaire du Match
22 - 2018-10-24132Thunder2Monsters3WXXSommaire du Match
24 - 2018-10-26147Senators5Monsters6WSommaire du Match
25 - 2018-10-27156Monsters7Minnesota8LXXSommaire du Match
30 - 2018-11-01187Monsters5Heat8LSommaire du Match
31 - 2018-11-02193Monsters8Comets1WSommaire du Match
36 - 2018-11-07225Chill2Monsters5WSommaire du Match
38 - 2018-11-09240Monsters6Oceanics5WXXSommaire du Match
40 - 2018-11-11259Monsters6Oil Kings0WSommaire du Match
43 - 2018-11-14275Bruins2Monsters5WSommaire du Match
45 - 2018-11-16289Bears2Monsters3WSommaire du Match
47 - 2018-11-18306Monsters6Admirals4WSommaire du Match
50 - 2018-11-21331Monsters1Monarchs5LSommaire du Match
52 - 2018-11-23343Monsters3Jayhawks6LSommaire du Match
53 - 2018-11-24355Stars0Monsters6WSommaire du Match
56 - 2018-11-27371Monsters6Chill1WSommaire du Match
57 - 2018-11-28381Manchots3Monsters6WSommaire du Match
59 - 2018-11-30393Chiefs5Monsters1LSommaire du Match
61 - 2018-12-02411Monsters5Cougars6LSommaire du Match
63 - 2018-12-04419Monsters4Manchots1WSommaire du Match
65 - 2018-12-06430Monsters4Cabaret Lady Mary Ann5LSommaire du Match
67 - 2018-12-08449Monsters3Thunder6LSommaire du Match
70 - 2018-12-11474Oil Kings1Monsters3WSommaire du Match
73 - 2018-12-14492Monsters1Chiefs3LSommaire du Match
74 - 2018-12-15503Stars2Monsters3WSommaire du Match
76 - 2018-12-17516Sound Tigers1Monsters4WSommaire du Match
78 - 2018-12-19529Rocket1Monsters4WSommaire du Match
80 - 2018-12-21544Baby Hawks6Monsters3LSommaire du Match
81 - 2018-12-22551Monsters1Jayhawks5LSommaire du Match
86 - 2018-12-27577Monsters3Las Vegas2WSommaire du Match
88 - 2018-12-29595Baby Hawks0Monsters5WSommaire du Match
90 - 2018-12-31607Monarchs5Monsters9WSommaire du Match
92 - 2019-01-02619Sharks3Monsters5WSommaire du Match
94 - 2019-01-04633Wolf Pack4Monsters9WSommaire du Match
98 - 2019-01-08665Monsters3Oceanics5LSommaire du Match
99 - 2019-01-09669Monsters4Heat3WSommaire du Match
102 - 2019-01-12691Monsters2Rocket0WSommaire du Match
104 - 2019-01-14706Monsters6Marlies3WSommaire du Match
106 - 2019-01-16721Monsters7Senators1WSommaire du Match
109 - 2019-01-19741Monarchs5Monsters7WSommaire du Match
111 - 2019-01-21756Chill4Monsters3LXXSommaire du Match
113 - 2019-01-23767Minnesota4Monsters6WSommaire du Match
123 - 2019-02-02800Comets4Monsters5WSommaire du Match
126 - 2019-02-05819Monsters4Monsters5WXSommaire du Match
128 - 2019-02-07827Monsters5Bears3WSommaire du Match
130 - 2019-02-09841Monsters5Sound Tigers4WSommaire du Match
131 - 2019-02-10854Monsters2Bruins4LSommaire du Match
133 - 2019-02-12873Marlies3Monsters6WSommaire du Match
135 - 2019-02-14882Monsters4Oceanics3WSommaire du Match
137 - 2019-02-16894Chiefs6Monsters4LSommaire du Match
139 - 2019-02-18913Las Vegas3Monsters6WSommaire du Match
141 - 2019-02-20926Oceanics6Monsters4LSommaire du Match
143 - 2019-02-22941Monsters2Baby Hawks3LSommaire du Match
144 - 2019-02-23951Monsters5Chill3WSommaire du Match
146 - 2019-02-25966Cabaret Lady Mary Ann4Monsters5WSommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
148 - 2019-02-27982Comets3Monsters2LSommaire du Match
150 - 2019-03-01998Monsters3Sharks4LSommaire du Match
152 - 2019-03-031012Monsters6Admirals4WSommaire du Match
154 - 2019-03-051026Cougars6Monsters5LSommaire du Match
156 - 2019-03-071039Monsters3Stars1WSommaire du Match
158 - 2019-03-091048Crunch1Monsters4WSommaire du Match
160 - 2019-03-111070Caroline1Monsters5WSommaire du Match
164 - 2019-03-151096Admirals4Monsters3LSommaire du Match
166 - 2019-03-171111Spiders6Monsters5LXXSommaire du Match
168 - 2019-03-191129Monsters7Minnesota5WSommaire du Match
170 - 2019-03-211143Monsters5Stars4WXXSommaire du Match
172 - 2019-03-231152Baby Hawks4Monsters6WSommaire du Match
173 - 2019-03-241167Monsters6Baby Hawks5WSommaire du Match
176 - 2019-03-271188Las Vegas3Monsters2LSommaire du Match
178 - 2019-03-291200Jayhawks5Monsters4LXXSommaire du Match
181 - 2019-04-011225Monsters6Chiefs1WSommaire du Match
182 - 2019-04-021236Oil Kings1Monsters4WSommaire du Match
184 - 2019-04-041251Oceanics4Monsters8WSommaire du Match
186 - 2019-04-061271Monsters8Sharks7WXXSommaire du Match



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité de l'Aréna20001000
Prix des Billets3515
Assistance61,84330,360
Assistance PCT75.42%74.05%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
0 2249 - 74.96% 63,900$2,619,905$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
2,813,238$ 2,777,415$ 2,777,415$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
14,852$ 2,813,238$ 34 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 0 14,852$ 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
20188250230104438127810341288010131961296741221500031185149361143816721053151511408512272385593191657220961592116023528323.58%3718577.09%61460261055.94%1288230955.78%791146753.92%2109144417556031095575
Total Saison Régulière8250230104438127810341288010131961296741221500031185149361143816721053151511408512272385593191657220961592116023528323.58%3718577.09%61460261055.94%1288230955.78%791146753.92%2109144417556031095575