Chill

GP: 82 | W: 52 | L: 27 | OTL: 3 | P: 107
GF: 361 | GA: 279 | PP%: 21.05% | PK%: 80.43%
DG: Yvon Bergeron | Morale : 50 | Moyenne d'Équipe : 51
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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 SPÂgeContratSalaire Moyen
1Cory ConacherXX100.00716473716371776248646166596465050620291600,000$
2Chris TerryXX100.00757083666975806450636366625454050620301860,000$
3Michael AmadioXX100.006242947371618570636159592557580506102321,145,000$
4Vitaly AbramovXX100.00686183696176796550626461614444050610212742,500$
5Morgan GeekieX100.00696773626778826480596662634444050600212763,333$
6Andy Miele (R)X100.00676278636274776680666261594444050600311600,000$
7Tommy Novak (R)X100.00736690686667686379655763544444050600221817,502$
8Taro HiroseX100.00654192635963717726655861254747050590233925,000$
9A.J. GreerXX100.00727356647664746349576164614646050590221725,000$
10Keegan KolesarX100.00818077658270715450574968454545050580221700,000$
11Matt Filipe (R)X100.00394343436837373943393943413230050400212700,000$
12Josh MahuraX100.00594093666569727125505060254646050580212700,000$
13Ben GleasonX100.00716976626969754825394159394444050560213770,000$
14Luke GreenX100.00756990606940404225284159394444050510212690,000$
15Markus Niemelainen (R)X100.00394343436737373943393943413230050410212700,000$
16Matthew Cairns (R)X100.00394343436837373943393943413230050410212700,000$
17Chris Martenet (R)X100.00344040407233333440343440373230050380231650,000$
Rayé
1Nolan StevensX100.00767090657070726278625765544444050600232842,500$
2Evan Barratt (R)X100.00534777696763745761554950515454050550204870,000$
3Filip Ahl (R)XX100.00344040408033333440343440373230050380221650,000$
4Nikita Korostelev (R)X100.00323737376931313237323237343230050350221525,000$
5Adam Marsh (R)X100.00323737374531313237323237343230050340221525,000$
6Gustav Bouramman (R)X100.00323737375731313237323237343230050360221525,000$
7Jordan Sambrook (R)X100.00323737373731313237323237343230050340211525,000$
MOYENNE D'ÉQUIPE100.0056536656665558524849485344424105051
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
1Keith Petruzzelli (R)100.0056746878495559585354555454050580
2Olle Eriksson Ek (R)100.0048676374424847484446465454050510
Rayé
1Kristian Oldham (R)100.0033373570333232323232313230050370
MOYENNE D'ÉQUIPE100.004659557441454646434444474605049
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire


Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du Joueur Nom de l'ÉquipePOSGP G A P +/- PIM PIM5 HIT HTT SHT OSB OSM SHT% SB MP AMG PPG PPA PPP PPS PPM PKG PKA PKP PKS PKM GW GT FO% FOT GA TA EG HT P/20 PSG PSS FW FL FT S1 S2 S3
1Vitaly AbramovChill (Nas)LW/RW824556101201806215142510929110.59%23169520.67913229120611271299345.66%17300001.1925000737
2Cory ConacherChill (Nas)LW/RW75375592212601421983801112819.74%43167522.34814225519201181723549.37%39700001.1015000655
3Andy MieleChill (Nas)C8230588815300911962656417611.32%43132816.207101730990001215158.15%130700011.3301000823
4A.J. GreerChill (Nas)LW/RW8030518125755201123334832248.98%29136617.0831215311030001403051.26%11900011.1900001531
5Michael AmadioChill (Nas)C/RW85324678180019188344782559.30%23164719.3849135321410141016257.71%86300010.9525000534
6Morgan GeekieChill (Nas)C8225507533395126196270811839.26%37142017.3253829990002323064.02%133400101.0611010143
7Chris TerryChill (Nas)LW/RW67373370252410821633657823810.14%42150322.44691556166000142167548.59%17700000.9305101352
8Taro HiroseChill (Nas)LW823137681120401112897419410.73%26114313.9522411400001475027.36%10600101.1900000233
9Nolan StevensChill (Nas)C8027336025320901711825116114.84%33121915.240003100001525257.29%103500000.9801000434
10Keegan KolesarChill (Nas)RW821939582034012396207541389.18%26103812.661344340000172049.32%7300001.1200000433
11Tommy NovakChill (Nas)C822136572121533167211621349.95%16111713.63459251300000404061.08%141300121.0211100321
12Josh MahuraChill (Nas)D4833235114019358333443.61%60101421.15145291070000121010.00%000000.6900000010
13Jake WalmanNashvilleD618212918540160388727459.20%82141023.12145261520000163100.00%000000.4100000017
14Ben GleasonChill (Nas)D6832326255010148295516375.45%71122117.96011790000098000.00%000000.4300001010
15Evan BarrattChill (Nas)C8171926260298410622676.60%3087210.77000170000310054.79%52200000.6000000010
16Mark BarberioNashvilleD2841822-120050487525485.33%5263322.621232764011181100.00%000000.6900000003
17Dysin MayoNashvilleD664131721715186367817515.13%104148922.56202281560005169000.00%000000.2300100010
18Markus NiemelainenChill (Nas)D29055161003805380.00%1444915.51000231011028000.00%000000.2200000000
19Luke GreenChill (Nas)D26044121603814176170.00%4640515.60011431000127000.00%000000.2000000000
20Mirco MuellerNashvilleD3123-2206474414.29%17424.7511231000003010.00%000000.8100000000
21Matthew CairnsChill (Nas)D2012386023250320.00%1431515.77000116000013000.00%000000.1900000000
22Chris MartenetChill (Nas)D2000-100700000.00%13316.660000000001000.00%000000.0000000000
23Matt FilipeChill (Nas)LW2000100200000.00%0115.6600000000000066.67%300000.0000000000
Stats d'équipe Total ou en Moyenne13133656339983445404017152050379099825999.63%8162308817.5855931485161968246461613542057.74%752200350.86724313484146
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
1Keith PetruzzelliChill (Nas)48291610.9073.3826960115216340100.6676480142
2Casey DeSmithNashville1812510.9083.22104500566110000.5002180021
3Olle Eriksson EkChill (Nas)175510.9003.8871200464610100.80051076000
Stats d'équipe Total ou en Moyenne83462630.9063.4244540125427060200.692137676163


Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
Nom du Joueur Nom de l'ÉquipePOS Âge Date de Naissance Nouveau Joueur Poids Taille Non-Échange Disponible pour Échange Ballotage Forcé Contrat Type Salaire Actuel Salaire RestantCap Salariale Cap Salariale Restant Exclus du Cap Salarial Salaire Année 2Salaire Année 3Salaire Année 4Salaire Année 5Salaire Année 6Salaire Année 7Salaire Année 8Salaire Année 9Salaire Année 10Link
A.J. GreerChill (Nas)LW/RW221996-12-14No204 Lbs6 ft3NoNoNo1Pro & Farm725,000$72,500$0$NoLien
Adam MarshChill (Nas)LW221997-08-22Yes160 Lbs6 ft0NoNoNo1Pro & Farm525,000$52,500$0$NoLien
Andy MieleChill (Nas)C311988-04-14Yes175 Lbs5 ft9YesNoNo1Pro & Farm600,000$60,000$0$NoLien
Ben GleasonChill (Nas)D211998-03-25No185 Lbs6 ft1NoNoNo3Pro & Farm770,000$77,000$0$No770,000$770,000$Lien
Chris MartenetChill (Nas)D231996-09-25Yes212 Lbs6 ft7NoNoNo1Pro & Farm650,000$65,000$0$NoLien
Chris TerryChill (Nas)LW/RW301989-04-07No195 Lbs5 ft10YesNoNo1Pro & Farm860,000$86,000$0$NoLien
Cory ConacherChill (Nas)LW/RW291989-12-14No180 Lbs5 ft8YesNoNo1Pro & Farm600,000$60,000$0$NoLien
Evan BarrattChill (Nas)C201999-02-18Yes188 Lbs6 ft0NoNoNo4Pro & Farm870,000$87,000$0$No870,000$870,000$870,000$Lien
Filip AhlChill (Nas)LW/RW221997-06-12Yes225 Lbs6 ft4NoNoNo1Pro & Farm650,000$65,000$0$NoLien
Gustav BourammanChill (Nas)D221997-01-24Yes184 Lbs6 ft0NoNoNo1Pro & Farm525,000$52,500$0$NoLien
Jordan SambrookChill (Nas)D211998-04-11Yes193 Lbs6 ft2NoNoNo1Pro & Farm525,000$52,500$0$NoLien
Josh MahuraChill (Nas)D211998-05-05No178 Lbs6 ft0NoNoNo2Pro & Farm700,000$70,000$0$No700,000$Lien
Keegan KolesarChill (Nas)RW221997-04-08No227 Lbs6 ft2NoNoNo1Pro & Farm700,000$70,000$0$NoLien
Keith PetruzzelliChill (Nas)G201999-02-09Yes181 Lbs6 ft5NoNoNo4Pro & Farm700,000$70,000$0$No700,000$700,000$700,000$
Kristian OldhamChill (Nas)G221997-06-25Yes190 Lbs6 ft4NoNoNo1Pro & Farm525,000$52,500$0$NoLien
Luke GreenChill (Nas)D211998-01-11No188 Lbs6 ft1NoNoNo2Pro & Farm690,000$69,000$0$No690,000$Lien
Markus NiemelainenChill (Nas)D211998-06-08Yes200 Lbs6 ft5NoNoNo2Pro & Farm700,000$70,000$0$No700,000$Lien
Matt FilipeChill (Nas)LW211997-12-31Yes197 Lbs6 ft2NoNoNo2Pro & Farm700,000$70,000$0$No700,000$Lien
Matthew CairnsChill (Nas)D211998-04-27Yes205 Lbs6 ft3NoNoNo2Pro & Farm700,000$70,000$0$No700,000$Lien
Michael AmadioChill (Nas)C/RW231996-05-13No190 Lbs6 ft1NoNoNo2Pro & Farm1,145,000$114,500$0$No1,145,000$Lien
Morgan GeekieChill (Nas)C211998-07-20No179 Lbs6 ft2NoNoNo2Pro & Farm763,333$76,333$0$No763,333$Lien
Nikita KorostelevChill (Nas)RW221997-02-08Yes201 Lbs6 ft1NoNoNo1Pro & Farm525,000$52,500$0$NoLien
Nolan StevensChill (Nas)C231996-07-21No183 Lbs6 ft3NoNoNo2Pro & Farm842,500$84,250$0$No842,500$Lien
Olle Eriksson EkChill (Nas)G201999-06-22Yes183 Lbs6 ft3NoNoNo4Pro & Farm773,889$77,389$0$No773,889$773,889$773,889$
Taro HiroseChill (Nas)LW231996-06-30No161 Lbs5 ft10NoNoNo3Pro & Farm925,000$92,500$0$No925,000$925,000$Lien
Tommy NovakChill (Nas)C221997-04-28Yes179 Lbs6 ft1NoNoNo1Pro & Farm817,502$81,750$0$NoLien
Vitaly AbramovChill (Nas)LW/RW211998-05-08No172 Lbs5 ft9NoNoNo2Pro & Farm742,500$74,250$0$No742,500$Lien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2722.48189 Lbs6 ft11.81712,953$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Cory ConacherMichael AmadioChris Terry40122
2Vitaly AbramovAndy MieleA.J. Greer30122
3Taro HiroseMorgan GeekieKeegan Kolesar20122
4Matt FilipeTommy NovakCory Conacher10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Josh MahuraBen Gleason40122
2Luke GreenMarkus Niemelainen30122
3Matthew CairnsChris Martenet20122
4Josh MahuraBen Gleason10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Cory ConacherMichael AmadioChris Terry60122
2Vitaly AbramovAndy MieleA.J. Greer40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Josh MahuraBen Gleason60122
2Luke GreenMarkus Niemelainen40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Cory ConacherChris Terry60122
2Vitaly AbramovMichael Amadio40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Josh MahuraBen Gleason60122
2Luke GreenMarkus Niemelainen40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Cory Conacher60122Josh MahuraBen Gleason60122
2Chris Terry40122Luke GreenMarkus Niemelainen40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Cory ConacherChris Terry60122
2Vitaly AbramovMichael Amadio40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Josh MahuraBen Gleason60122
2Luke GreenMarkus Niemelainen40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Cory ConacherMichael AmadioChris TerryJosh MahuraBen Gleason
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Cory ConacherMichael AmadioChris TerryJosh MahuraBen Gleason
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Morgan Geekie, Tommy Novak, Taro HiroseMorgan Geekie, Tommy NovakTaro Hirose
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Matthew Cairns, Chris Martenet, Luke GreenMatthew CairnsChris Martenet, Luke Green
Tirs de Pénalité
Cory Conacher, Chris Terry, Vitaly Abramov, Michael Amadio, Andy Miele
Gardien
#1 : Keith Petruzzelli, #2 : Olle Eriksson Ek


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
1Admirals310010101284210010008531000001043161.00012193100142119968118119012291284359925277613215.38%60100.00%01913327258.47%1582283555.80%777142554.53%2124151917925731035532
2Baby Hawks514000001320-72020000058-331200000812-420.2001322350014211996817111901229128435210484612420525.00%180100.00%01913327258.47%1582283555.80%777142554.53%2124151917925731035532
3Bears220000001082110000003211100000076141.0001018280014211996810511901229128435631018569222.22%8275.00%01913327258.47%1582283555.80%777142554.53%2124151917925731035532
4Bruins220000001055110000004221100000063341.00010182800142119968801190122912843561238504125.00%40100.00%01913327258.47%1582283555.80%777142554.53%2124151917925731035532
5Cabaret Lady Mary Ann220000001147110000006241100000052341.000112233001421199681451190122912843567191060500.00%50100.00%01913327258.47%1582283555.80%777142554.53%2124151917925731035532
6Caroline22000000734110000004221100000031241.00071219001421199687711901229128435592527274250.00%9188.89%01913327258.47%1582283555.80%777142554.53%2124151917925731035532
7Chiefs412000011318-52110000078-120100001610-430.37513243700142119968166119012291284351654732104900.00%16756.25%01913327258.47%1582283555.80%777142554.53%2124151917925731035532
8Comets32100000151051100000042221100000118340.667152843001421199681301190122912843511834265811218.18%13376.92%01913327258.47%1582283555.80%777142554.53%2124151917925731035532
9Cougars2010001079-2100000104311010000036-320.50071118001421199688611901229128435551213528225.00%3166.67%01913327258.47%1582283555.80%777142554.53%2124151917925731035532
10Crunch21100000912-31010000016-51100000086220.5009172600142119968931190122912843595233764200.00%10370.00%01913327258.47%1582283555.80%777142554.53%2124151917925731035532
11Heat33000000197122200000013491100000063361.00019355400142119968141119012291284358926168110440.00%7271.43%01913327258.47%1582283555.80%777142554.53%2124151917925731035532
12Jayhawks302000101013-31010000045-12010001068-220.3331014240014211996813211901229128435902516668225.00%8275.00%01913327258.47%1582283555.80%777142554.53%2124151917925731035532
13Las Vegas30300000711-42020000068-21010000013-200.0007121900142119968129119012291284359140225715213.33%11372.73%01913327258.47%1582283555.80%777142554.53%2124151917925731035532
14Manchots220000001156110000005231100000063341.000112132001421199687611901229128435903130445360.00%14285.71%01913327258.47%1582283555.80%777142554.53%2124151917925731035532
15Marlies210000018711000000145-11100000042230.75081321001421199688311901229128435681614513133.33%7271.43%01913327258.47%1582283555.80%777142554.53%2124151917925731035532
16Minnesota55000000309213300000016882200000014113101.000305888011421199683531190122912843520353281258225.00%13192.31%01913327258.47%1582283555.80%777142554.53%2124151917925731035532
17Monarchs31100001131301010000034-121000001109130.50013233600142119968156119012291284351183310878112.50%5180.00%01913327258.47%1582283555.80%777142554.53%2124151917925731035532
18Monsters220000001183110000005411100000064241.0001118290014211996810011901229128435662110438337.50%5260.00%01913327258.47%1582283555.80%777142554.53%2124151917925731035532
19Monsters413000001218-62020000079-22110000059-420.25012223400142119968133119012291284351455534858112.50%17288.24%01913327258.47%1582283555.80%777142554.53%2124151917925731035532
20Oceanics413000001319-62110000088020200000511-620.250132235001421199681421190122912843516234459917423.53%19478.95%01913327258.47%1582283555.80%777142554.53%2124151917925731035532
21Oil Kings32100000131301100000043121100000910-140.66713253800142119968121119012291284351525318839222.22%8275.00%01913327258.47%1582283555.80%777142554.53%2124151917925731035532
22Phantoms2110000089-11010000035-21100000054120.500814220014211996873119012291284357322104310220.00%5260.00%11913327258.47%1582283555.80%777142554.53%2124151917925731035532
23Rocket220000001248110000005141100000073441.0001219310014211996811411901229128435691815437228.57%5260.00%01913327258.47%1582283555.80%777142554.53%2124151917925731035532
24Senators22000000963110000004311100000053241.00091726001421199687611901229128435742712512150.00%6183.33%01913327258.47%1582283555.80%777142554.53%2124151917925731035532
25Sharks33000000205152200000013491100000071661.00020365600142119968172119012291284358429186610110.00%9277.78%01913327258.47%1582283555.80%777142554.53%2124151917925731035532
26Sound Tigers220000001275110000006421100000063341.00012223400142119968991190122912843567121547900.00%5180.00%01913327258.47%1582283555.80%777142554.53%2124151917925731035532
27Spiders2020000069-31010000034-11010000035-200.0006111700142119968661190122912843567171647500.00%8187.50%01913327258.47%1582283555.80%777142554.53%2124151917925731035532
28Stars4310000022111121100000107322000000124860.750223860001421199682251190122912843514134358910330.00%14378.57%01913327258.47%1582283555.80%777142554.53%2124151917925731035532
29Thunder21100000642110000004131010000023-120.500610160014211996873119012291284355082035400.00%10190.00%11913327258.47%1582283555.80%777142554.53%2124151917925731035532
Total8248270103336127982412414010111751304541241300022186149371070.652361642100301142119968371711901229128435296583564419562475221.05%2765480.43%21913327258.47%1582283555.80%777142554.53%2124151917925731035532
30Wolf Pack220000001248110000006151100000063341.000122133001421199688211901229128435741516436233.33%8187.50%01913327258.47%1582283555.80%777142554.53%2124151917925731035532
_Since Last GM Reset8248270103336127982412414010111751304541241300022186149371070.652361642100301142119968371711901229128435296583564419562475221.05%2765480.43%21913327258.47%1582283555.80%777142554.53%2124151917925731035532
_Vs Conference35238010121611174418124010017954251711400011826319520.7431612834440014211996815011190122912843512163232698381132320.35%1192281.51%21913327258.47%1582283555.80%777142554.53%2124151917925731035532
_Vs Division168400002725121842000013223984200001402812180.56372127199001421199687501190122912843553914612940635720.00%501080.00%11913327258.47%1582283555.80%777142554.53%2124151917925731035532

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
82107W3361642100337172965835644195601
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
8248271033361279
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4124141011175130
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
4124130022186149
Derniers 10 Matchs
WLOTWOTL SOWSOL
550000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
2475221.05%2765480.43%2
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
11901229128435142119968
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
1913327258.47%1582283555.80%777142554.53%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
2124151917925731035532


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 - 2020-10-239Minnesota4Chill8WSommaire du Match
4 - 2020-10-2525Cougars3Chill4WXXSommaire du Match
7 - 2020-10-2841Sharks1Chill7WSommaire du Match
9 - 2020-10-3052Bears2Chill3WSommaire du Match
11 - 2020-11-0163Chill7Monarchs5WSommaire du Match
14 - 2020-11-0490Chill1Las Vegas3LSommaire du Match
16 - 2020-11-06104Chill2Jayhawks5LSommaire du Match
18 - 2020-11-08121Cabaret Lady Mary Ann2Chill6WSommaire du Match
21 - 2020-11-11138Admirals2Chill4WSommaire du Match
23 - 2020-11-13150Minnesota1Chill4WSommaire du Match
25 - 2020-11-15164Chill2Thunder3LSommaire du Match
28 - 2020-11-18185Baby Hawks5Chill4LSommaire du Match
30 - 2020-11-20194Heat2Chill6WSommaire du Match
32 - 2020-11-22205Wolf Pack1Chill6WSommaire du Match
34 - 2020-11-24222Chill3Cougars6LSommaire du Match
37 - 2020-11-27244Chill4Monsters2WSommaire du Match
39 - 2020-11-29262Chill7Sharks1WSommaire du Match
42 - 2020-12-02277Chill7Comets2WSommaire du Match
46 - 2020-12-06310Baby Hawks3Chill1LSommaire du Match
49 - 2020-12-09325Oceanics4Chill2LSommaire du Match
51 - 2020-12-11339Comets2Chill4WSommaire du Match
53 - 2020-12-13358Chill2Chiefs5LSommaire du Match
55 - 2020-12-15370Chiefs5Chill2LSommaire du Match
57 - 2020-12-17385Las Vegas3Chill2LSommaire du Match
59 - 2020-12-19401Chill3Caroline1WSommaire du Match
60 - 2020-12-20409Chill5Cabaret Lady Mary Ann2WSommaire du Match
63 - 2020-12-23430Thunder1Chill4WSommaire du Match
67 - 2020-12-27460Spiders4Chill3LSommaire du Match
70 - 2020-12-30475Sharks3Chill6WSommaire du Match
72 - 2021-01-01487Chill8Crunch6WSommaire du Match
74 - 2021-01-03505Stars5Chill4LSommaire du Match
76 - 2021-01-05520Chill6Wolf Pack3WSommaire du Match
77 - 2021-01-06527Chill6Sound Tigers3WSommaire du Match
79 - 2021-01-08542Chill5Senators3WSommaire du Match
81 - 2021-01-10556Chill6Bruins3WSommaire du Match
83 - 2021-01-12576Jayhawks5Chill4LSommaire du Match
87 - 2021-01-16587Manchots2Chill5WSommaire du Match
88 - 2021-01-17597Chill6Manchots3WSommaire du Match
92 - 2021-01-21626Chill4Stars2WSommaire du Match
95 - 2021-01-24652Chill3Monarchs4LXXSommaire du Match
96 - 2021-01-25658Chill4Admirals3WXXSommaire du Match
98 - 2021-01-27671Bruins2Chill4WSommaire du Match
100 - 2021-01-29684Chill4Baby Hawks3WSommaire du Match
103 - 2021-02-01703Chill2Oceanics5LSommaire du Match
105 - 2021-02-03723Chill4Oil Kings6LSommaire du Match
107 - 2021-02-05735Admirals3Chill4WXSommaire du Match
109 - 2021-02-07752Crunch6Chill1LSommaire du Match
118 - 2021-02-16770Marlies5Chill4LXXSommaire du Match
120 - 2021-02-18777Chill7Bears6WSommaire du Match
121 - 2021-02-19783Chill3Spiders5LSommaire du Match
123 - 2021-02-21801Las Vegas5Chill4LSommaire du Match
126 - 2021-02-24822Chill3Oceanics6LSommaire du Match
128 - 2021-02-26836Chill6Heat3WSommaire du Match
130 - 2021-02-28845Chill5Oil Kings4WSommaire du Match
132 - 2021-03-02864Chill4Comets6LSommaire du Match
135 - 2021-03-05886Sound Tigers4Chill6WSommaire du Match
137 - 2021-03-07896Chill4Chiefs5LXXSommaire du Match
138 - 2021-03-08910Chiefs3Chill5WSommaire du Match
140 - 2021-03-10925Caroline2Chill4WSommaire du Match
143 - 2021-03-13943Chill2Baby Hawks4LSommaire du Match
144 - 2021-03-14955Monsters4Chill5WSommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
147 - 2021-03-17977Senators3Chill4WSommaire du Match
149 - 2021-03-19991Heat2Chill7WSommaire du Match
151 - 2021-03-211008Monsters4Chill3LSommaire du Match
153 - 2021-03-231018Oil Kings3Chill4WSommaire du Match
154 - 2021-03-241023Chill8Minnesota1WSommaire du Match
156 - 2021-03-261039Stars2Chill6WSommaire du Match
158 - 2021-03-281051Chill8Stars2WSommaire du Match
161 - 2021-03-311071Chill7Rocket3WSommaire du Match
163 - 2021-04-021083Chill4Marlies2WSommaire du Match
165 - 2021-04-041105Chill6Monsters4WSommaire du Match
166 - 2021-04-051116Chill6Minnesota0WSommaire du Match
170 - 2021-04-091142Monsters5Chill4LSommaire du Match
172 - 2021-04-111159Phantoms5Chill3LSommaire du Match
173 - 2021-04-121167Chill2Baby Hawks5LSommaire du Match
175 - 2021-04-141183Oceanics4Chill6WSommaire du Match
177 - 2021-04-161197Monarchs4Chill3LSommaire du Match
179 - 2021-04-181214Chill4Jayhawks3WXXSommaire du Match
180 - 2021-04-191222Chill1Monsters7LSommaire du Match
183 - 2021-04-221240Rocket1Chill5WSommaire du Match
184 - 2021-04-231246Chill5Phantoms4WSommaire du Match
186 - 2021-04-251267Minnesota3Chill4WSommaire du Match



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité de l'Aréna20001000
Prix des Billets3818
Assistance77,85630,468
Assistance PCT94.95%74.31%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
0 2642 - 88.07% 85,535$3,506,952$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
2,167,998$ 1,924,972$ 1,924,972$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
10,349$ 2,187,709$ 27 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 0 10,349$ 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