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Chicago Wolves
GP: 10 | W: 7 | L: 3 | OTL: 0 | P: 14
GF: 59 | GA: 52 | PP%: 32.14% | PK%: 61.90%
DG: Camil Costandi | Morale : 55 | Moyenne d’équipe : 57
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Centre de jeu
Chicoutimi Sagueneens
6-4-0, 12pts
7
FINAL
12 Chicago Wolves
7-3-0, 14pts
Team Stats
L2StreakW2
4-1-0Home Record5-0-0
2-3-0Away Record2-3-0
6-4-0Last 10 Games7-3-0
6.70Buts par match 5.90
5.80Buts contre par match 5.20
37.14%Pourcentage en avantage numérique32.14%
68.97%Pourcentage en désavantage numérique61.90%
Chicago Wolves
7-3-0, 14pts
5
FINAL
4 Bridgeport Sound Tigers
4-5-1, 9pts
Team Stats
W2StreakSOL1
5-0-0Home Record3-2-0
2-3-0Away Record1-3-1
7-3-0Last 10 Games4-5-1
5.90Buts par match 5.80
5.20Buts contre par match 5.10
32.14%Pourcentage en avantage numérique45.45%
61.90%Pourcentage en désavantage numérique70.97%
Meneurs d'équipe
Buts
C.J. Suess
10
Passes
Valtteri Puustinen
13
Points
C.J. Suess
20
Plus/Moins
Dean Stewart
9
Victoires
Nico Daws
7
Pourcentage d’arrêts
Nico Daws
0.883

Statistiques d’équipe
Buts pour
59
5.90 GFG
Tirs pour
431
43.10 Avg
Pourcentage en avantage numérique
32.1%
9 GF
Début de zone offensive
34.7%
Buts contre
52
5.20 GAA
Tirs contre
378
37.80 Avg
Pourcentage en désavantage numérique
61.9%
8 GA
Début de la zone défensive
31.8%
Informations de l'équipe

Directeur généralCamil Costandi
EntraîneurNolan Pratt
DivisionMarcel Dionne
ConférenceConference 1
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance0
Billets de saison300


Informations de la formation

Équipe Pro25
Équipe Mineure21
Limite contact 46 / 50
Espoirs29


Historique d'équipe

Saison actuelle7-3-0 (14PTS)
Historique85-128-20 (0.365%)
Apparitions en séries éliminatoires 2
Historique en séries éliminatoires (W-L)0-0
Coupe Stanley0


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
1Marco Rossi (R)0X100.006964797764606064806460625744446450600201700,000$
2C.J. Suess0X100.007569896669656661505661645844446350590281775,000$
3Valtteri Puustinen (R)0XX100.007364936564626361505662635944446450580231700,000$
4Cole Smith (R)0X100.009146996574537155265055742544446350580261750,000$
5Jackson Cates (R)0XX100.006341996770545657695059702545456150570241700,000$
6Hudson Fasching0X100.008044996574556255255055677555556150570261750,000$
7William Lockwood (R)0X100.009993806765596857255055652545456150570241750,000$
8Adam Johnson0XX100.007064846264555751645047594545455450530281800,000$
9Lukas Rousek (R)0XX100.007363967063403849504746604444445350510231700,000$
10Simon Benoit0X100.009770877274647556254747732550506150640231750,000$
11Calle Rosen0X100.006141927069656963256251692557576250620282762,500$
12Jordan Harris (R)0X100.007543776764694160253950702544445850580211700,000$
13Cavan Fitzgerald0X100.007771916571586147253641643954545350570251750,000$
14Dean Stewart (R)0X100.008075937075403852254941643944445450560241700,000$
15Linus Hogberg (R)0X100.007466916566657046253739603744445250560231750,000$
16Oskari Laaksonen (R)0X100.007065826365646753255041593944445450560221925,000$
17Jakub Galvas (R)0X100.006960916460586050254640583844445250540231700,000$
Rayé
1Mitchell Stephens0X100.007143907269595155796755772553536450600251750,000$
2Adam Helewka0X100.0080768968765454585056566653444461505802600$
3Doyle Somerby0X100.0082857662855659472538396637525252505802700$
4Ian McCoshen0X100.0078807260805457462537396337505050505602600$
MOYENNE D’ÉQUIPE100.00776388677058595439494965404747585057
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 SPÂgeContratSalaire
1Nico Daws (R)100.00634747836956696365627846466250610211700,000$
2Kyle Keyser (R)100.00544151695855535857563044445450540231733,333$
Rayé
1Devin Cooley (R)100.00474050834947505349493044444850510251785,000$
2Michael McNiven100.004445567642465051484830444447505002400$
MOYENNE D’ÉQUIPE100.0052435178555156565554424545535054
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Nolan Pratt63767865706579CAN47170,000$


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’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
1C.J. SuessChicago Wolves (QUE)LW61010208009841152924.39%213322.27213313000141022.274151022.9900000301
2Marco RossiChicago Wolves (QUE)C6910198758745152120.00%513121.97123212000031021.97163114002.8811001130
3Valtteri PuustinenChicago Wolves (QUE)LW/RW831316500975417285.56%114217.76033212000020017.7613143002.2500000011
4Hudson FaschingChicago Wolves (QUE)RW896155008743122520.93%613516.89123511000001216.89755012.2200000200
5Jackson CatesChicago Wolves (QUE)C/LW8459100192191319.05%39111.4700001000020011.4710990001.9600000001
6Calle RosenChicago Wolves (QUE)D61562557713947.69%914123.5401101700003000.00%046000.8500100000
7Simon BenoitChicago Wolves (QUE)D624631010138199710.53%1516227.0710111600003000.00%035000.7400011000
8Cavan FitzgeraldChicago Wolves (QUE)D10066-200211151070.00%1316116.150110800003000.00%038000.7400000000
9Cole SmithChicago Wolves (QUE)LW103361001162591412.00%311311.4000022000010111.401352001.0500000010
10William LockwoodChicago Wolves (QUE)RW8246110101251621012.50%38210.2600000000000010.26752001.4600110010
11Jordan HarrisChicago Wolves (QUE)D8235-2201313136815.38%1214718.431011800003100.00%0113000.6800000000
12Adam JohnsonChicago Wolves (QUE)C/LW8112-100351041110.00%3668.260000000000008.262221000.6100000001
13Lukas RousekChicago Wolves (QUE)LW/RW81120002396711.11%2648.020000000000108.02271000.6200000000
14Dean StewartChicago Wolves (QUE)D8022955548530.00%210413.070000000001000.00%003000.3800001000
15Linus HogbergChicago Wolves (QUE)D8022620534350.00%410312.930000100001000.00%020000.3900000000
16Mitchell StephensChicago Wolves (QUE)C1000020213000.00%177.070000000000007.071100000.00%00000000
17Oskari LaaksonenChicago Wolves (QUE)D8000200401000.00%2394.980000000000000.00%000000.00%00000000
Statistiques d’équipe totales ou en moyenne125477512246433511410434013119213.82%86182814.6261016161070001325357.26%3518654031.3311223664
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
1Nico DawsChicago Wolves (QUE)87100.8834.344840035299180011.000380001
Statistiques d’équipe totales ou en moyenne87100.8834.34484003529918001380001


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 Plafond salarial Plafond salarial restant Exclus du plafond salarial Salaire annuel 2Salaire annuel 3Salaire annuel 4Salaire annuel 5Salaire annuel 6Salaire annuel 7Salaire annuel 8Salaire annuel 9Salaire annuel 10Link
Adam HelewkaChicago Wolves (QUE)LW261995-07-21No205 Lbs6 ft2NoNoNo0Pro & Farm0$0$NoLien / Lien NHL
Adam JohnsonChicago Wolves (QUE)C/LW281994-06-22No174 Lbs6 ft0NoNoNo1Pro & Farm800,000$0$0$NoLien / Lien NHL
C.J. SuessChicago Wolves (QUE)LW281994-03-16No190 Lbs5 ft11NoNoNo1Pro & Farm775,000$0$0$NoLien
Calle RosenChicago Wolves (QUE)D281994-02-01No186 Lbs6 ft1NoNoNo2Pro & Farm762,500$0$0$No762,500$Lien / Lien NHL
Cavan FitzgeraldChicago Wolves (QUE)D251996-08-23No190 Lbs6 ft1NoNoNo1Pro & Farm750,000$0$0$NoLien / Lien NHL
Cole SmithChicago Wolves (QUE)LW261995-10-28Yes195 Lbs6 ft3NoNoNo1Pro & Farm750,000$0$0$NoLien / Lien NHL
Dean StewartChicago Wolves (QUE)D241998-06-12Yes201 Lbs6 ft2NoNoNo1Pro & Farm700,000$0$0$No
Devin CooleyChicago Wolves (QUE)G251997-05-24Yes192 Lbs6 ft5NoNoNo1Pro & Farm785,000$0$0$NoLien / Lien NHL
Doyle SomerbyChicago Wolves (QUE)D271994-07-04No223 Lbs6 ft6NoNoNo0Pro & Farm0$0$NoLien / Lien NHL
Hudson FaschingChicago Wolves (QUE)RW261995-07-28No204 Lbs6 ft1NoNoNo1Pro & Farm750,000$0$0$NoLien / Lien NHL
Ian McCoshenChicago Wolves (QUE)D261995-08-05No218 Lbs6 ft3NoNoNo0Pro & Farm0$0$NoLien / Lien NHL
Jackson CatesChicago Wolves (QUE)C/LW241997-09-26Yes190 Lbs6 ft0NoNoNo1Pro & Farm700,000$0$0$NoLien
Jakub GalvasChicago Wolves (QUE)D231999-06-15Yes161 Lbs5 ft11NoNoNo1Pro & Farm700,000$0$0$No
Jordan HarrisChicago Wolves (QUE)D212000-07-07Yes179 Lbs5 ft11NoNoNo1Pro & Farm700,000$0$0$No
Kyle KeyserChicago Wolves (QUE)G231999-03-08Yes178 Lbs6 ft2NoNoNo1Pro & Farm733,333$0$0$NoLien / Lien NHL
Linus HogbergChicago Wolves (QUE)D231998-09-04Yes176 Lbs6 ft1NoNoNo1Pro & Farm750,000$0$0$NoLien / Lien NHL
Lukas RousekChicago Wolves (QUE)LW/RW231999-04-20Yes172 Lbs5 ft11NoNoNo1Pro & Farm700,000$0$0$No
Marco RossiChicago Wolves (QUE)C202001-09-23Yes183 Lbs5 ft9NoNoNo1Pro & Farm700,000$0$0$No
Michael McNivenChicago Wolves (QUE)G241997-07-08No203 Lbs6 ft1NoNoNo0Pro & Farm0$0$NoLien / Lien NHL
Mitchell StephensChicago Wolves (QUE)C251997-02-05No190 Lbs5 ft11NoNoNo1Pro & Farm750,000$0$0$NoLien / Lien NHL
Nico DawsChicago Wolves (QUE)G212000-12-22Yes203 Lbs6 ft4NoNoNo1Pro & Farm700,000$0$0$No
Oskari LaaksonenChicago Wolves (QUE)D221999-07-02Yes172 Lbs6 ft1NoNoNo1Pro & Farm925,000$0$0$NoLien / Lien NHL
Simon BenoitChicago Wolves (QUE)D231998-09-19No191 Lbs6 ft3NoNoNo1Pro & Farm750,000$0$0$NoLien / Lien NHL
Valtteri PuustinenChicago Wolves (QUE)LW/RW231999-06-04Yes183 Lbs5 ft9NoNoNo1Pro & Farm700,000$0$0$No
William LockwoodChicago Wolves (QUE)RW241998-06-20Yes172 Lbs5 ft11NoNoNo1Pro & Farm750,000$0$0$NoLien / Lien NHL
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2524.32189 Lbs6 ft10.88625,233$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
140122
2Valtteri PuustinenHudson Fasching30122
3Cole SmithJackson CatesWilliam Lockwood20122
4Lukas RousekAdam Johnson10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
140122
2Jordan HarrisCavan Fitzgerald30122
3Dean StewartLinus Hogberg20122
4Oskari Laaksonen10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
160122
2Valtteri PuustinenHudson Fasching40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
160122
2Jordan HarrisCavan Fitzgerald40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
160122
2Valtteri Puustinen40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
160122
2Jordan HarrisCavan Fitzgerald40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
16012260122
240122Jordan HarrisCavan Fitzgerald40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
160122
2Valtteri Puustinen40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
160122
2Jordan HarrisCavan Fitzgerald40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Valtteri Puustinen, Cole Smith, Hudson FaschingValtteri Puustinen, Cole SmithValtteri Puustinen
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Dean Stewart, Linus Hogberg, Oskari LaaksonenDean StewartDean Stewart, Linus Hogberg
Tirs de pénalité
, , , , Valtteri Puustinen
Gardien
#1 : , #2 : Kyle Keyser


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
TotalDomicileVisiteur
# 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
1Binghampton Senators1010000027-5000000000001010000027-500.0002460016301211914915912324291082150.00%5180.00%011122150.23%8720243.07%9721345.54%2201382158916980
2Bridgeport Sound Tigers220000001156110000006151100000054141.000111627001630121871491591232732819314125.00%2150.00%011122150.23%8720243.07%9721345.54%2201382158916980
3Chicoutimi Sagueneens21100000171611100000012751010000059-420.500173047001630121891491591232732421358225.00%8450.00%011122150.23%8720243.07%9721345.54%2201382158916980
4Grand Rapids Griffins2100001016124100000107611100000096341.000162743001630121103149159123279247488450.00%110.00%011122150.23%8720243.07%9721345.54%2201382158916980
5London Knights11000000422110000004220000000000021.00048120016301212814915912323511618200.00%3166.67%011122150.23%8720243.07%9721345.54%2201382158916980
6Philadelphia Phantoms21100000910-1110000005411010000046-220.500917261016301211051491591232762614314125.00%20100.00%011122150.23%8720243.07%9721345.54%2201382158916980
Total1063000105952754000010342014523000002532-7140.7005910216110163012143114915912323781227717128932.14%21861.90%011122150.23%8720243.07%9721345.54%2201382158916980
_Since Last GM Reset1063000105952754000010342014523000002532-7140.7005910216110163012143114915912323781227717128932.14%21861.90%011122150.23%8720243.07%9721345.54%2201382158916980
_Vs Conference8520001053431043000010301812422000002325-2120.750539014310163012138414915912323011026114524833.33%13653.85%011122150.23%8720243.07%9721345.54%2201382158916980

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
1014W2591021614313781227717110
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
106300105952
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
54000103420
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
52300002532
Derniers 10 matchs
WLOTWOTL SOWSOL
630010
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
28932.14%21861.90%0
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
14915912321630121
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
11122150.23%8720243.07%9721345.54%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
2201382158916980


Derniers matchs 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
1 - 2022-09-258Chicago Wolves5Chicoutimi Sagueneens9ALSommaire du match
2 - 2022-09-2614Chicago Wolves2Binghampton Senators7ALSommaire du match
3 - 2022-09-2732Bridgeport Sound Tigers1Chicago Wolves6BWSommaire du match
5 - 2022-09-2950Philadelphia Phantoms4Chicago Wolves5BWSommaire du match
7 - 2022-10-0170London Knights2Chicago Wolves4BWSommaire du match
8 - 2022-10-0286Chicago Wolves9Grand Rapids Griffins6AWSommaire du match
9 - 2022-10-03100Chicago Wolves4Philadelphia Phantoms6ALSommaire du match
12 - 2022-10-06121Grand Rapids Griffins6Chicago Wolves7BWXXSommaire du match
13 - 2022-10-07137Chicoutimi Sagueneens7Chicago Wolves12BWSommaire du match
14 - 2022-10-08140Chicago Wolves5Bridgeport Sound Tigers4AWSommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets2510
Assistance00
Assistance PCT0.00%0.00%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
0 0 - 0.00% 0$0$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
0$ 1,563,083$ 1,556,833$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 0$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 0 0$ 0$




Chicago Wolves Leaders statistiques (saison régulière)

# Nom du joueur GP G A P +/- PIM HIT HTT SHT SHT% SB MP AMG PPG PPA PPP PPS PKG PKA PKP PKS GW GT FO% HT P/20 PSG PSS
1Adam Johnson338245346591-84470496704168514.54%311809623.95531381911594042223056.42151.46524
2Morgan Klimchuk32820024044032292512440116817.12%208611618.6560681281440008241241.4381.4400
3Patrick Brown304144240384-9228850856088816.22%228609620.05406010096808812849.5281.26812
4Vitali Kravtsov3281881923803618842446898419.11%160573717.495624801280000281639.3481.3200
5C.J. Smith200135204339-13420329257384715.94%225498624.933457918700094842.9741.36416

Chicago Wolves Leaders des statistiques des gardiens (saison régulière)

# Nom du gardien GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA
1Pat Nagle2129680240.8924.2012339008648004440420160.25016
2Kyle Keyser1494473220.8725.047958160669523832101100.54951
3Michael McNiven35101430.8685.031812401521155676310.5008
4David Ayres120800.8476.795300060392264000.00%0

Chicago Wolves Statistiques de l'Équipe de Carrière

TotalDomicileVisiteur
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
Saison régulière
202082303902614388393-541171900203211203841132002411177190-1376388614100250901581376270375510189113532561118107914442149242.99%2057563.41%5776155649.87%889182948.61%739154047.99%155779017977761605821
202082303902614388393-541171900203211203841132002411177190-1376388614100250901581376270375510189113532561118107914442149242.99%2057563.41%5776155649.87%889182948.61%739154047.99%155779017977761605821
202178155003415335467-1323952601313155239-8439102402102180228-484733554487920691311316287077510131057412930991156315511888243.62%2449162.70%3798165748.16%700149346.89%748153848.63%154482216687491510734
Total Saison régulière24275128071631311111253-142121396401719577645-68121366406924534608-74199111117722883120249447405188276228530492879111944232273721443961626643.18%65424163.15%132350476949.28%2478515148.11%2226461848.20%465824025264230247222377
Séries éliminatoires
Total Séries éliminatoires0000000000000000000000000000000000000000000000000000000.00%000.00%0000.00%000.00%000.00%000000

Chicago Wolves Leaders statistiques (séries éliminatoires)

# Nom du joueur GP G A P +/- PIM HIT HTT SHT SHT% SB MP AMG PPG PPA PPP PPS PKG PKA PKP PKS GW GT FO% HT P/20 PSG PSS

Chicago Wolves Leaders des statistiques des gardiens (séries éliminatoires)

# Nom du gardien GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA