Chicago Wolves

GP: 67 | W: 38 | L: 25 | OTL: 4 | P: 80
GF: 204 | GA: 195 | PP%: 16.43% | PK%: 88.84%
DG: Francis Lagace | Morale : 64 | Moyenne d'Équipe : N/A
Prochain matchs #985 vs San Antonio Rampage
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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
1Andrew AgozzinoX100.0060667773666865648064616258505015900
2Justin Scott (R)X100.0073747562746966567050596256505018200
3Steven Fogarty (R)X100.0062796662796663516450506550505019100
4Kevin Lynch (R)X100.0058756961756763506350546351505015900
5Tobias LindbergXX100.0079756064756163545051536350505017800
6Mitchell HeardX100.0062745862745259505950505850505018700
7Rod PelleyX100.0079727262726967506350506750646515200
8Tyler RandellXX100.0062726164725762505050505950505018400
9Chris BourqueX100.0058606967607368655065606257505013700
10Mitch MorozX100.0074787363785660505050506150505018600
11Alexandre GrenierX100.0066786968787578612555576554505018500
12Jan KostalekX100.0057686764686467502550505950505018400
13Mat ClarkX100.0065836264706266502550506450505015400
14William Wrenn (R)X100.0063756761756266502550506250505015900
15Mike Downing (R)X100.0058765962766266502550506050505018600
16Philip SamuelssonX100.0058726460726569502550506150505018500
Rayé
MOYENNE D'ÉQUIPE100.006574676473646653475253625251511730
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
1Jared Coreau100.005680708965597759686279706917400
2Marek Langhamer (R)100.005779696369686965646646626312000
Rayé
MOYENNE D'ÉQUIPE100.00578070766764736266646366661470
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Gerard Gallant84887885856681CAN526100,000$


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
1Justin ScottChicago Wolves (Van)LW472719461947570961611416.77%13104822.31581332206101122384062.64%18200010.8814010443
2Andrew AgozzinoChicago Wolves (Van)C47123244427535171155337.74%15113424.148122038193011112902262.41%135400010.7814000252
3Alexandre GrenierChicago Wolves (Van)D4711283916935103621060010.38%41111023.6310616802160224270210.00%000000.7011001432
4Rod PelleyChicago Wolves (Van)C4713253822755971011190110.92%987418.6028101611510151681062.57%70000000.8711010443
5Steven FogartyChicago Wolves (Van)C47827351344205340750310.67%886218.35291123191000024060.54%22300000.8111202041
6Tobias LindbergChicago Wolves (Van)C/LW67181230-414951871081691010.65%20106315.87448291900001832153.56%68900000.5603010232
7Philip SamuelssonChicago Wolves (Van)D4762329184158829581210.34%4598621.006511421930110243110.00%000000.5900001212
8William WrennChicago Wolves (Van)D4771724157607429482114.58%57104022.143710311950001251200.00%000000.4600000102
9Mat ClarkChicago Wolves (Van)D473182118105251212943106.98%56103121.951910241980112251000.00%000000.4100131001
10Tyler RandellChicago Wolves (Van)C/LW47101121123003642562117.86%555911.910003160000473250.00%7400000.7500000312
11Jan KostalekChicago Wolves (Van)D476111785606332300020.00%2476316.240115160003137100.00%000000.4500000221
12Kevin LynchChicago Wolves (Van)C479817131402148600015.00%459912.76325151231012362161.31%13700000.5700000003
13Mike DowningChicago Wolves (Van)D4741317680109226240116.67%2672715.48011429000068100.00%100000.4700002112
14Chris BourqueChicago Wolves (Van)LW2688163180295483339.64%463024.232681910800071542259.18%4900000.5102000022
15Mitchell HeardChicago Wolves (Van)C47771492352221400217.50%03878.240333270000123047.62%4200000.7200100021
16Mitch MorozChicago Wolves (Van)LW475712114410583970007.14%275416.06011109300021421047.32%11200000.3200002113
Stats d'équipe Total ou en Moyenne75115426642018392210011499271297142111.87%3291357518.0846821283742118358502401311059.61%356300020.62516469263332
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
1Jeff GlassVancouver Canucks2418420.9291.60139025375210200.8005240603
2Jared CoreauChicago Wolves (Van)2114610.9052.14123622444650000.5008212211
Stats d'équipe Total ou en Moyenne45321030.9181.85262747819860200.61513452814


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
Alexandre GrenierChicago Wolves (Van)D251991-09-05No200 Lbs6 ft5NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No300,000$
Andrew AgozzinoChicago Wolves (Van)C261991-01-02No187 Lbs5 ft10NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No300,000$
Chris BourqueChicago Wolves (Van)LW301986-01-28No174 Lbs5 ft8NoNoNo2Sans RestrictionPro & Farm300,000$0$0$No300,000$
Jan KostalekChicago Wolves (Van)D211995-02-16No181 Lbs6 ft1NoNoNo3Contrat d'EntréePro & Farm300,000$0$0$No300,000$300,000$
Jared CoreauChicago Wolves (Van)G251991-11-04No235 Lbs6 ft4NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No300,000$
Justin ScottChicago Wolves (Van)LW211995-08-13Yes201 Lbs6 ft1NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No300,000$300,000$300,000$
Kevin LynchChicago Wolves (Van)C251991-04-23Yes205 Lbs6 ft1NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Marek LanghamerChicago Wolves (Van)G221994-07-21Yes184 Lbs6 ft2NoNoNo3Contrat d'EntréePro & Farm300,000$0$0$No300,000$300,000$
Mat ClarkChicago Wolves (Van)D261990-10-16No225 Lbs6 ft3NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Mike DowningChicago Wolves (Van)D211995-05-19Yes205 Lbs6 ft2NoNoNo3Contrat d'EntréePro & Farm0$0$No
Mitch MorozChicago Wolves (Van)LW221994-05-02No214 Lbs6 ft2NoNoNo2Contrat d'EntréePro & Farm300,000$0$0$No300,000$
Mitchell HeardChicago Wolves (Van)C241992-03-12No200 Lbs6 ft1NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Philip SamuelssonChicago Wolves (Van)D251991-07-25No194 Lbs6 ft2NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No300,000$
Rod PelleyChicago Wolves (Van)C321984-08-31No200 Lbs5 ft11NoNoNo1Sans RestrictionPro & Farm500,000$0$0$No
Steven FogartyChicago Wolves (Van)C231993-04-18Yes212 Lbs6 ft3NoNoNo4Avec RestrictionPro & Farm300,000$0$0$No300,000$300,000$300,000$
Tobias LindbergChicago Wolves (Van)C/LW211995-07-22No201 Lbs6 ft2NoNoNo3Contrat d'EntréePro & Farm300,000$0$0$No300,000$300,000$
Tyler RandellChicago Wolves (Van)C/LW251991-06-15No197 Lbs6 ft1NoNoNo3Avec RestrictionPro & Farm300,000$0$0$No300,000$300,000$
William WrennChicago Wolves (Van)D251991-03-16Yes209 Lbs6 ft1NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No300,000$
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
1824.39201 Lbs6 ft12.28294,444$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Chris BourqueAndrew AgozzinoTobias Lindberg40122
2Justin ScottRod PelleySteven Fogarty30122
3Mitch MorozTobias LindbergAndrew Agozzino20122
4Tyler RandellSteven FogartyChris Bourque10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Alexandre GrenierMat Clark40122
2William WrennPhilip Samuelsson30122
3Mike DowningJan Kostalek20122
4Alexandre GrenierMat Clark10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Chris BourqueAndrew AgozzinoTobias Lindberg60122
2Justin ScottRod PelleySteven Fogarty40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Alexandre GrenierMat Clark60122
2William WrennPhilip Samuelsson40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Andrew AgozzinoChris Bourque60122
2Justin ScottRod Pelley40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Alexandre GrenierMat Clark60122
2William WrennPhilip Samuelsson40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Andrew Agozzino60122Alexandre GrenierMat Clark60122
2Chris Bourque40122William WrennPhilip Samuelsson40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Andrew AgozzinoChris Bourque60122
2Justin ScottRod Pelley40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Alexandre GrenierMat Clark60122
2William WrennPhilip Samuelsson40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Chris BourqueAndrew AgozzinoTobias LindbergAlexandre GrenierMat Clark
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Chris BourqueAndrew AgozzinoTobias LindbergAlexandre GrenierMat Clark
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Kevin Lynch, Mitchell Heard, Mitch MorozKevin Lynch, Mitchell HeardMitch Moroz
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Mike Downing, Jan Kostalek, William WrennMike DowningJan Kostalek, William Wrenn
Tirs de Pénalité
Andrew Agozzino, Chris Bourque, Justin Scott, Rod Pelley, Tobias Lindberg
Gardien
#1 : , #2 :


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
1Abbotsford Heat31200000911-2211000005411010000047-320.33391726007369569795616766343510425556318422.22%24195.83%01109199855.51%1093213451.22%52799253.13%160411091655480795396
2Adirondack Phantoms21001000514100010002111100000030341.0005101501736956937561676634354917423715213.33%20195.00%01109199855.51%1093213451.22%52799253.13%160411091655480795396
3Albany Devils2010000124-21010000012-11000000112-110.2502350073695693356167663435621739569111.11%17288.24%01109199855.51%1093213451.22%52799253.13%160411091655480795396
4Binghampton Senateurs1010000034-1000000000001010000034-100.000369007369569265616766343531102216100.00%10370.00%01109199855.51%1093213451.22%52799253.13%160411091655480795396
5Bridgeport Sound Tigers22000000404110000002021100000020241.00047110273695695256167663435245185324312.50%80100.00%01109199855.51%1093213451.22%52799253.13%160411091655480795396
6Charlotte Checkers3200100014771100000032121001000115661.00014274101736956910956167663435892736859444.44%18194.44%11109199855.51%1093213451.22%52799253.13%160411091655480795396
7Connecticut Whale22000000752110000004311100000032141.00071219007369569615616766343543185065300.00%18288.89%01109199855.51%1093213451.22%52799253.13%160411091655480795396
8Grand Rapids Griffins3210000012102211000008711100000043140.667122234007369569805616766343512129477112325.00%22290.91%01109199855.51%1093213451.22%52799253.13%160411091655480795396
9Hamilton Bulldogs21100000550000000000002110000055020.500510150073695694356167663435712726308112.50%120100.00%01109199855.51%1093213451.22%52799253.13%160411091655480795396
10Hershey Bears2010100023-11010000013-21000100010120.5002460173695693656167663435311745521200.00%19194.74%01109199855.51%1093213451.22%52799253.13%160411091655480795396
11Houston Aeros22000000945110000004221100000052341.00091726007369569595616766343541438499444.44%14378.57%01109199855.51%1093213451.22%52799253.13%160411091655480795396
12Lake Erie Monsters321000001385211000008711100000051440.667132639007369569140561676634359523189316212.50%8187.50%01109199855.51%1093213451.22%52799253.13%160411091655480795396
13Manchester Monarchs2110000010641010000046-21100000060620.50010182811736956910256167663435631916507342.86%7185.71%01109199855.51%1093213451.22%52799253.13%160411091655480795396
14Milwaukee Admirals2010001036-31010000015-41000001021120.5003470073695693256167663435571348421000.00%23291.30%01109199855.51%1093213451.22%52799253.13%160411091655480795396
15Norfolk Admirals3210000016971100000052321100000117440.667163046007369569137561676634358920306916212.50%150100.00%11109199855.51%1093213451.22%52799253.13%160411091655480795396
16Oklahoma City Barons530001101814442000110161331100000021190.90018345200736956919156167663435179529413117423.53%38489.47%01109199855.51%1093213451.22%52799253.13%160411091655480795396
17Peoria Rivermen1010000023-11010000023-10000000000000.0002460073695692656167663435601614103133.33%7357.14%01109199855.51%1093213451.22%52799253.13%160411091655480795396
18Portland Pirates2110000057-2110000004221010000015-420.500581300736956933561676634355614344110220.00%17288.24%01109199855.51%1093213451.22%52799253.13%160411091655480795396
19Providence Bruins3120000069-3110000004132020000028-620.3336101600736956958561676634359419405724312.50%20290.00%01109199855.51%1093213451.22%52799253.13%160411091655480795396
20Rochester Americans31200000212-101010000007-72110000025-320.3332460173695695856167663435862865531800.00%19478.95%01109199855.51%1093213451.22%52799253.13%160411091655480795396
21Rockford IceHogs31200000713-61010000025-32110000058-320.33371421007369569845616766343510032386921314.29%17476.47%01109199855.51%1093213451.22%52799253.13%160411091655480795396
22San Antonio Rampage3200001016124100000107612200000096361.0001628440073695691365616766343514225388411436.36%18194.44%01109199855.51%1093213451.22%52799253.13%160411091655480795396
23Springfield Falcons11000000321000000000001100000032121.000369007369569175616766343523728227114.29%14285.71%11109199855.51%1093213451.22%52799253.13%160411091655480795396
24St-John Ice Caps21000001642110000004131000000123-130.7506111700736956941561676634354623364513215.38%17194.12%01109199855.51%1093213451.22%52799253.13%160411091655480795396
25Syracuse Crunch30200100613-72010010058-31010000015-410.16761117007369569505616766343511135695314214.29%20385.00%01109199855.51%1093213451.22%52799253.13%160411091655480795396
26Texas Stars31200000612-620200000311-81100000031220.3336101600736956965561676634359324627028310.71%25388.00%01109199855.51%1093213451.22%52799253.13%160411091655480795396
27Toronto Marlies11000000514000000000001100000051421.00051015007369569415616766343513613253133.33%50100.00%01109199855.51%1093213451.22%52799253.13%160411091655480795396
Total6732250323220419593214130122099102-3351812020121059312800.5972043795831773695691888561676634352071578109615443595916.43%4665288.84%31109199855.51%1093213451.22%52799253.13%160411091655480795396
29Wilkes-Barre Penguins1010000023-1000000000001010000023-100.000246007369569165616766343525312217114.29%6183.33%01109199855.51%1093213451.22%52799253.13%160411091655480795396
30Worchester Sharks2110000067-1110000004131010000026-420.5006121800736956946561676634357323233214321.43%8275.00%01109199855.51%1093213451.22%52799253.13%160411091655480795396
_Since Last GM Reset6732250323220419593214130122099102-3351812020121059312800.5972043795831773695691888561676634352071578109615443595916.43%4665288.84%31109199855.51%1093213451.22%52799253.13%160411091655480795396
_Vs Conference3719130113012111831979001205972-131812401010624616470.63512122734802736956911435616766343512513315928751833418.58%2502988.40%11109199855.51%1093213451.22%52799253.13%160411091655480795396
_Vs Division173500010645410101400000382810721000102626080.2356411918311736956958856167663435564153252386821821.95%1091090.83%11109199855.51%1093213451.22%52799253.13%160411091655480795396

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
6780W1204379583188820715781096154417
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
6732253232204195
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
321413122099102
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
351812201210593
Derniers 10 Matchs
WLOTWOTL SOWSOL
810010
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
3595916.43%4665288.84%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
561676634357369569
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
1109199855.51%1093213451.22%52799253.13%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
160411091655480795396


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
4 - 2017-10-0421Oklahoma City Barons4Chicago Wolves5WSommaire du Match
5 - 2017-10-0536Oklahoma City Barons3Chicago Wolves5WSommaire du Match
8 - 2017-10-0849Chicago Wolves0Rochester Americans5LSommaire du Match
10 - 2017-10-1056Chicago Wolves2Worchester Sharks6LSommaire du Match
11 - 2017-10-1169Chicago Wolves1Rockford IceHogs7LSommaire du Match
14 - 2017-10-1482Oklahoma City Barons4Chicago Wolves3LXSommaire du Match
16 - 2017-10-16104Rochester Americans7Chicago Wolves0LSommaire du Match
18 - 2017-10-18122Lake Erie Monsters5Chicago Wolves3LSommaire du Match
20 - 2017-10-20138Chicago Wolves0Providence Bruins5LSommaire du Match
21 - 2017-10-21147Chicago Wolves6Charlotte Checkers5WXSommaire du Match
23 - 2017-10-23162Texas Stars6Chicago Wolves2LSommaire du Match
24 - 2017-10-24178Chicago Wolves5San Antonio Rampage4WSommaire du Match
27 - 2017-10-27187Chicago Wolves1Hamilton Bulldogs4LSommaire du Match
29 - 2017-10-29194Chicago Wolves4Norfolk Admirals5LSommaire du Match
30 - 2017-10-30206Grand Rapids Griffins5Chicago Wolves3LSommaire du Match
32 - 2017-11-01227San Antonio Rampage6Chicago Wolves7WXXSommaire du Match
34 - 2017-11-03249Manchester Monarchs6Chicago Wolves4LSommaire du Match
36 - 2017-11-05263Chicago Wolves4Abbotsford Heat7LSommaire du Match
38 - 2017-11-07275Chicago Wolves1Syracuse Crunch5LSommaire du Match
39 - 2017-11-08289Peoria Rivermen3Chicago Wolves2LSommaire du Match
41 - 2017-11-10306Chicago Wolves2St-John Ice Caps3LXXSommaire du Match
42 - 2017-11-11317Oklahoma City Barons2Chicago Wolves3WXXSommaire du Match
44 - 2017-11-13336Grand Rapids Griffins2Chicago Wolves5WSommaire du Match
45 - 2017-11-14343Chicago Wolves3Binghampton Senateurs4LSommaire du Match
47 - 2017-11-16362Chicago Wolves5Lake Erie Monsters1WSommaire du Match
50 - 2017-11-19377Adirondack Phantoms1Chicago Wolves2WXSommaire du Match
52 - 2017-11-21396Chicago Wolves2Wilkes-Barre Penguins3LSommaire du Match
53 - 2017-11-22404Chicago Wolves2Rochester Americans0WSommaire du Match
54 - 2017-11-23417Albany Devils2Chicago Wolves1LSommaire du Match
57 - 2017-11-26431Chicago Wolves1Portland Pirates5LSommaire du Match
58 - 2017-11-27442Chicago Wolves3Springfield Falcons2WSommaire du Match
59 - 2017-11-28449Abbotsford Heat3Chicago Wolves5WSommaire du Match
61 - 2017-11-30471Chicago Wolves1Hershey Bears0WXSommaire du Match
62 - 2017-12-01478Charlotte Checkers2Chicago Wolves3WSommaire du Match
64 - 2017-12-03497Chicago Wolves4San Antonio Rampage2WSommaire du Match
65 - 2017-12-04507Texas Stars5Chicago Wolves1LSommaire du Match
69 - 2017-12-08530Hershey Bears3Chicago Wolves1LSommaire du Match
70 - 2017-12-09539Chicago Wolves3Connecticut Whale2WSommaire du Match
74 - 2017-12-13563Chicago Wolves4Rockford IceHogs1WSommaire du Match
75 - 2017-12-14568St-John Ice Caps1Chicago Wolves4WSommaire du Match
78 - 2017-12-17592Houston Aeros2Chicago Wolves4WSommaire du Match
80 - 2017-12-19599Chicago Wolves5Charlotte Checkers0WSommaire du Match
81 - 2017-12-20613Chicago Wolves2Bridgeport Sound Tigers0WSommaire du Match
85 - 2017-12-24625Syracuse Crunch3Chicago Wolves2LXSommaire du Match
88 - 2017-12-27639Chicago Wolves7Norfolk Admirals2WSommaire du Match
89 - 2017-12-28655Milwaukee Admirals5Chicago Wolves1LSommaire du Match
91 - 2017-12-30668Chicago Wolves1Albany Devils2LXXSommaire du Match
92 - 2017-12-31680Chicago Wolves2Oklahoma City Barons1WSommaire du Match
93 - 2018-01-01687Syracuse Crunch5Chicago Wolves3LSommaire du Match
95 - 2018-01-03706Chicago Wolves5Toronto Marlies1WSommaire du Match
97 - 2018-01-05717Abbotsford Heat1Chicago Wolves0LSommaire du Match
99 - 2018-01-07725Chicago Wolves2Providence Bruins3LSommaire du Match
101 - 2018-01-09739Chicago Wolves4Hamilton Bulldogs1WSommaire du Match
102 - 2018-01-10749Worchester Sharks1Chicago Wolves4WSommaire du Match
104 - 2018-01-12771Chicago Wolves4Grand Rapids Griffins3WSommaire du Match
105 - 2018-01-13778Connecticut Whale3Chicago Wolves4WSommaire du Match
107 - 2018-01-15797Chicago Wolves6Manchester Monarchs0WSommaire du Match
109 - 2018-01-17809Bridgeport Sound Tigers0Chicago Wolves2WSommaire du Match
112 - 2018-01-20836Chicago Wolves5Houston Aeros2WSommaire du Match
114 - 2018-01-22841Norfolk Admirals2Chicago Wolves5WSommaire du Match
115 - 2018-01-23861Providence Bruins1Chicago Wolves4WSommaire du Match
118 - 2018-01-26881Chicago Wolves3Texas Stars1WSommaire du Match
120 - 2018-01-28897Portland Pirates2Chicago Wolves4WSommaire du Match
122 - 2018-01-30918Chicago Wolves2Milwaukee Admirals1WXXSommaire du Match
123 - 2018-01-31924Chicago Wolves3Adirondack Phantoms0WSommaire du Match
124 - 2018-02-01933Rockford IceHogs5Chicago Wolves2LSommaire du Match
127 - 2018-02-04958Lake Erie Monsters2Chicago Wolves5WSommaire du Match
132 - 2018-02-09985San Antonio Rampage-Chicago Wolves-
137 - 2018-02-141011Wilkes-Barre Penguins-Chicago Wolves-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
139 - 2018-02-161026Chicago Wolves-Manchester Monarchs-
141 - 2018-02-181042Chicago Wolves-Houston Aeros-
142 - 2018-02-191046Rochester Americans-Chicago Wolves-
144 - 2018-02-211071Toronto Marlies-Chicago Wolves-
145 - 2018-02-221078Chicago Wolves-Worchester Sharks-
149 - 2018-02-261104Wilkes-Barre Penguins-Chicago Wolves-
152 - 2018-03-011126Toronto Marlies-Chicago Wolves-
155 - 2018-03-041151Binghampton Senateurs-Chicago Wolves-
159 - 2018-03-081175Hamilton Bulldogs-Chicago Wolves-
161 - 2018-03-101192Chicago Wolves-Peoria Rivermen-
163 - 2018-03-121202Springfield Falcons-Chicago Wolves-
167 - 2018-03-161222Chicago Wolves-Peoria Rivermen-
168 - 2018-03-171230Chicago Wolves-Milwaukee Admirals-



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
9 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
113,257$ 53,000$ 48,760$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 35,762$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 38 905$ 34,390$




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
126732250323220419593214130122099102-3351812020121059312802043795831773695691888561676634352071578109615443595916.43%4665288.84%31109199855.51%1093213451.22%52799253.13%160411091655480795396
Total Saison Régulière6732250323220419593214130122099102-3351812020121059312802043795831773695691888561676634352071578109615443595916.43%4665288.84%31109199855.51%1093213451.22%52799253.13%160411091655480795396