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OTHL - IceHogs 

IceHogs

GP: 82 | W: 71 | L: 9 | OTL: 2 | P: 144
GF: 513 | GA: 161 | PP%: 20.24% | PK%: 87.69%
DG: Mark | Morale : 50 | Moyenne d'Équipe : 60
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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
1Adam ErneXX100.008966827278578262416560707556566650650
2Joseph BlandisiXX100.006466587366717366806362635956566450630
3Austin CzarnikXXX100.005940948058598168446760622562626550630
4Logan Brown (R)X100.008585866285626264806560705744446550630
5Kiefer Sherwood (R)XX100.008144947266597959386162652548486650620
6Peter CehlarikXX100.006142906775637369266072522546466750610
7Valentin ZykovXX100.007344977180557169326058522546466250600
8Max Veronneau (R)X100.005540996467634963256370562545456550590
9Griffen MolinoXX100.007263926463576047594245614351515250530
10Cameron SchillingX100.007469856669788554254941643955555650620
11Matt TennysonX100.007576747076697454254942654057575650620
12Matt BartkowskiX100.007472796972596250253941663964655450600
13Justin HollX100.007142936366605757254947542546465650560
Rayé
MOYENNE D'ÉQUIPE100.00725886697162706040565562395252615061
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
1Al Montoya100.00464759784445505246473061614850520
Rayé
MOYENNE D'ÉQUIPE100.0046475978444550524647306161485052
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Mike Van Ryn50685966454656CAN3921,340,000$


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
1Max VeronneauIceHogs (CHI)RW827884162115175289045612434417.11%26137716.80336164700013017160.49%8100042.350000113145
2Logan BrownIceHogs (CHI)C75571011581091243015615732910826317.33%31148319.787192624161000511913178.16%141000032.13012131039
3Kiefer SherwoodIceHogs (CHI)LW/RW767580155111601012311539610527618.94%26140518.5081523411711011397160.81%7400062.21001001478
4Valentin ZykovIceHogs (CHI)LW/RW8260851451151801101303579824216.81%25141017.2014512780115846164.00%12500032.060000011611
5Peter CehlarikIceHogs (CHI)LW/RW825886144103240259542813529113.55%20148318.0991322511840001294061.45%8300021.9400000476
6Griffen MolinoIceHogs (CHI)C/LW8231901211124751441252456615212.65%38144217.59314105310151373270.13%120200001.6800010058
7Austin CzarnikIceHogs (CHI)C/LW/RW69387411292100151082687217914.18%24141420.5039122316900081301164.97%17700011.5800000386
8Joseph BlandisiIceHogs (CHI)C/LW685061111976151481343439023914.58%16149321.9636920165000121557076.70%127900041.4900001764
9Matt BartkowskiIceHogs (CHI)D781239517966101533593334612.90%40149219.1337102417701131751042.86%700000.6800011202
10Justin HollIceHogs (CHI)D8184250704751112577176510.39%47148718.3653838189011319420100.00%400000.6700000032
11Matt TennysonIceHogs (CHI)D6743741768620150375725407.02%46136720.410441816700001570080.00%500000.6000211012
12Adam ErneIceHogs (CHI)LW/RW30528333223572477417526.76%763721.260333690001821059.57%23500001.0300000102
13Cameron SchillingIceHogs (CHI)D31411153835531122541416.00%1664720.892139760000861050.00%200000.4600001010
Stats d'équipe Total ou en Moyenne90348081812981149618100126611103148894220315.25%3621714318.984788135289171323545142263772.97%4684000231.5101548656165
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
1Al MontoyaIceHogs (CHI)8271920.8911.834767101514513260300.5002820012
Stats d'équipe Total ou en Moyenne8271920.8911.834767101514513260300.5002820012


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
Adam ErneIceHogs (CHI)LW/RW251995-04-20No214 Lbs6 ft1NoNoNo1Pro & Farm874,167$0$0$NoLien
Al MontoyaIceHogs (CHI)G351985-02-12No201 Lbs6 ft2YesNoNo1Pro & Farm675,000$0$0$NoLien
Austin CzarnikIceHogs (CHI)C/LW/RW271992-12-12No160 Lbs5 ft9NoNoNo1Pro & Farm975,000$0$0$NoLien
Cameron SchillingIceHogs (CHI)D311988-10-07No182 Lbs6 ft2YesNoNo2Pro & Farm700,000$0$0$No700,000$Lien
Griffen MolinoIceHogs (CHI)C/LW261994-01-21No171 Lbs5 ft11NoNoNo1Pro & Farm1,000,000$0$0$NoLien
Joseph BlandisiIceHogs (CHI)C/LW251994-07-18No182 Lbs5 ft11NoNoNo3Pro & Farm650,000$0$0$No650,000$650,000$Lien
Justin HollIceHogs (CHI)D281992-01-30No170 Lbs6 ft2NoNoNo2Pro & Farm925,000$0$0$No925,000$Lien
Kiefer SherwoodIceHogs (CHI)LW/RW251995-03-31Yes180 Lbs5 ft11NoNoNo2Pro & Farm925,000$0$0$No925,000$Lien
Logan BrownIceHogs (CHI)C221998-03-04Yes220 Lbs6 ft6NoNoNo3Pro & Farm1,573,333$0$0$No1,573,333$1,573,333$Lien
Matt BartkowskiIceHogs (CHI)D311988-06-04No196 Lbs6 ft1YesNoNo2Pro & Farm675,000$0$0$No675,000$Lien
Matt TennysonIceHogs (CHI)D291990-04-23No205 Lbs6 ft2YesNoNo2Pro & Farm750,000$0$0$No750,000$Lien
Max VeronneauIceHogs (CHI)RW241995-12-11Yes181 Lbs6 ft0NoNoNo2Pro & Farm925,000$0$0$No925,000$Lien
Peter CehlarikIceHogs (CHI)LW/RW241995-05-12No202 Lbs6 ft2NoNoNo2Pro & Farm925,000$0$0$No925,000$Lien
Valentin ZykovIceHogs (CHI)LW/RW241995-05-14No224 Lbs6 ft1NoNoNo1Pro & Farm894,167$0$0$NoLien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
1426.86192 Lbs6 ft11.79890,476$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Adam ErneJoseph BlandisiAustin Czarnik40122
2Kiefer SherwoodLogan BrownPeter Cehlarik30122
3Valentin ZykovGriffen MolinoMax Veronneau20122
4Joseph BlandisiAdam ErneLogan Brown10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Matt TennysonCameron Schilling40122
2Matt BartkowskiJustin Holl30122
320122
4Matt TennysonCameron Schilling10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Adam ErneJoseph BlandisiAustin Czarnik60122
2Kiefer SherwoodLogan BrownPeter Cehlarik40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Matt TennysonCameron Schilling60122
2Matt BartkowskiJustin Holl40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Adam ErneJoseph Blandisi60122
2Logan BrownAustin Czarnik40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Matt TennysonCameron Schilling60122
2Matt BartkowskiJustin Holl40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Adam Erne60122Matt TennysonCameron Schilling60122
2Joseph Blandisi40122Matt BartkowskiJustin Holl40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Adam ErneJoseph Blandisi60122
2Logan BrownAustin Czarnik40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Matt TennysonCameron Schilling60122
2Matt BartkowskiJustin Holl40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Adam ErneJoseph BlandisiAustin CzarnikMatt TennysonCameron Schilling
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Adam ErneJoseph BlandisiAustin CzarnikMatt TennysonCameron Schilling
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Valentin Zykov, Max Veronneau, Griffen MolinoValentin Zykov, Max VeronneauGriffen Molino
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Matt Bartkowski, Justin Holl, Matt TennysonMatt BartkowskiJustin Holl, Matt Tennyson
Tirs de Pénalité
Adam Erne, Joseph Blandisi, Logan Brown, Austin Czarnik, Kiefer Sherwood
Gardien
#1 : Al Montoya, #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
1 Americans2110000056-1110000003121010000025-320.5005101500235161116145115111351135438182233800.00%10190.00%01775251070.72%971151664.05%976136071.76%279422501284398850501
2Admirals550000004554033000000293262200000016214101.0004578123022351611161269115111351135476152110615426.67%80100.00%01775251070.72%971151664.05%976136071.76%279422501284398850501
3Barracudas330000001851322000000154111100000031261.0001831490023516111611211151113511354481424678337.50%11281.82%11775251070.72%971151664.05%976136071.76%279422501284398850501
4Bears2200000014311110000009091100000053241.00014253901235161116195115111351135431181036400.00%5260.00%01775251070.72%971151664.05%976136071.76%279422501284398850501
5Bruins220000001239110000008351100000040441.00012223401235161116174115111351135425821319222.22%8275.00%01775251070.72%971151664.05%976136071.76%279422501284398850501
6Checkers2020000038-51010000023-11010000015-400.0003580023516111612711511135113544314103310110.00%5260.00%01775251070.72%971151664.05%976136071.76%279422501284398850501
7Comets32001000743110000003212100100042261.00071219002351611161651151113511354681821301616.25%70100.00%01775251070.72%971151664.05%976136071.76%279422501284398850501
8Condors3210000014772110000011561100000032140.6671426400023516111617811511135113545919765218633.33%21195.24%01775251070.72%971151664.05%976136071.76%279422501284398850501
9Crunch22000000826110000006151100000021141.0008162400235161116183115111351135426827269111.11%6183.33%01775251070.72%971151664.05%976136071.76%279422501284398850501
10Devils22000000182161100000081711000000101941.0001830480023516111611201151113511354301011412150.00%3166.67%01775251070.72%971151664.05%976136071.76%279422501284398850501
11Eagles44000000414372200000019316220000002212181.000417311401235161116123811511135113544619167111327.27%60100.00%01775251070.72%971151664.05%976136071.76%279422501284398850501
12Griffins220000001248110000008261100000042241.00012223400235161116180115111351135435612366233.33%6266.67%01775251070.72%971151664.05%976136071.76%279422501284398850501
13Gulls311001008802010010024-21100000064230.50081220002351611161701151113511354692247497114.29%15193.33%01775251070.72%971151664.05%976136071.76%279422501284398850501
14Heat31200000720-131010000019-821100000611-520.333711180023516111615811511135113541182227458112.50%10370.00%01775251070.72%971151664.05%976136071.76%279422501284398850501
15Marlies220000001275110000006421100000063341.0001219310023516111617611511135113543698318225.00%4175.00%01775251070.72%971151664.05%976136071.76%279422501284398850501
16Monsters2110000079-2110000005231010000027-520.50071017002351611161541151113511354421313276233.33%4250.00%01775251070.72%971151664.05%976136071.76%279422501284398850501
17Moose55000000277202200000011473300000016313101.00027487501235161116121211511135113548024559912216.67%20290.00%01775251070.72%971151664.05%976136071.76%279422501284398850501
18Penguins22000000936110000006151100000032141.000918270023516111617711511135113542058281000.00%30100.00%01775251070.72%971151664.05%976136071.76%279422501284398850501
19Phantoms22000000184141100000011381100000071641.00018325000235161116194115111351135427111443100.00%70100.00%01775251070.72%971151664.05%976136071.76%279422501284398850501
20Rampage 44000000383352200000024123220000001421281.000386910701235161116121411511135113544018307115426.67%70100.00%01775251070.72%971151664.05%976136071.76%279422501284398850501
21Reign3300000031130220000002102111000000101961.0003153840223516111611731151113511354331224554375.00%120100.00%01775251070.72%971151664.05%976136071.76%279422501284398850501
22Roadrunners33000000295241100000013211220000001631361.0002944730023516111611671151113511354421016653133.33%80100.00%11775251070.72%971151664.05%976136071.76%279422501284398850501
23Rocket20100001612-61010000027-51000000145-110.2506111700235161116140115111351135470191828800.00%9277.78%01775251070.72%971151664.05%976136071.76%279422501284398850501
24Senators22000000936110000005051100000043141.0009152401235161116178115111351135445116298337.50%30100.00%01775251070.72%971151664.05%976136071.76%279422501284398850501
25Sound Tigers22000000173141100000010281100000071641.000172744002351611161106115111351135440102247100.00%110100.00%01775251070.72%971151664.05%976136071.76%279422501284398850501
26Stars440000002652122000000172152200000093681.0002646720123516111612181151113511354491420991119.09%10280.00%01775251070.72%971151664.05%976136071.76%279422501284398850501
27Thunderbirds220000001587110000006511100000093641.0001527420023516111615911511135113545013432812325.00%13376.92%01775251070.72%971151664.05%976136071.76%279422501284398850501
Total82709011015131613524135500100291792124135401001222821401440.8785138971410015235161116134221151113511354141941069214902525120.24%2603287.69%21775251070.72%971151664.05%976136071.76%279422501284398850501
29Wild44000000323292200000018018220000001431181.0003259910223516111612091151113511354661128938225.00%130100.00%01775251070.72%971151664.05%976136071.76%279422501284398850501
30Wolf Pack2200000017314110000009361100000080841.00017324901235161116111311511135113541241335200.00%4175.00%01775251070.72%971151664.05%976136071.76%279422501284398850501
31Wolves33000000844110000003212200000052361.0008142201235161116110911511135113545515295612216.67%11190.91%01775251070.72%971151664.05%976136071.76%279422501284398850501
_Since Last GM Reset82709011015131613524135500100291792124135401001222821401440.8785138971410015235161116134221151113511354141941069214902525120.24%2603287.69%21775251070.72%971151664.05%976136071.76%279422501284398850501
_Vs Conference49435001003298324625213001001874014724222000001424399870.8883295749030112351611161218111511135113548192334359611403323.57%1621391.98%21775251070.72%971151664.05%976136071.76%279422501284398850501
_Vs Division2626100000209271821313000000118131051313100000911477521.00020937358208235161116113601151113511354357101170539721622.22%64493.75%01775251070.72%971151664.05%976136071.76%279422501284398850501

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
82144W25138971410342214194106921490015
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
827091101513161
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
41355010029179
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
41354100122282
Derniers 10 Matchs
WLOTWOTL SOWSOL
820000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
2525120.24%2603287.69%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
11511135113542351611161
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
1775251070.72%971151664.05%976136071.76%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
279422501284398850501


Derniers Match Joués
Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
JourMatch Équipe Visiteuse Score Équipe Locale Score ST OT SO RI Lien
3 - 2019-10-0616IceHogs7Phantoms1WSommaire du Match
9 - 2019-10-1248Barracudas2IceHogs7WSommaire du Match
11 - 2019-10-1463Moose3IceHogs7WSommaire du Match
13 - 2019-10-1680Condors2IceHogs9WSommaire du Match
17 - 2019-10-20108Monsters2IceHogs5WSommaire du Match
19 - 2019-10-22125Bears0IceHogs9WSommaire du Match
21 - 2019-10-24136Wolves2IceHogs3WSommaire du Match
23 - 2019-10-26147Phantoms3IceHogs11WSommaire du Match
25 - 2019-10-28162IceHogs1Checkers5LSommaire du Match
26 - 2019-10-29170Reign0IceHogs13WSommaire du Match
28 - 2019-10-31184IceHogs13Admirals0WSommaire du Match
32 - 2019-11-04211IceHogs10Reign1WSommaire du Match
33 - 2019-11-05218IceHogs6Gulls4WSommaire du Match
35 - 2019-11-07231IceHogs3Barracudas1WSommaire du Match
37 - 2019-11-09240Comets2IceHogs3WSommaire du Match
39 - 2019-11-11258IceHogs3Penguins2WSommaire du Match
40 - 2019-11-12265Marlies4IceHogs6WSommaire du Match
43 - 2019-11-15285IceHogs3Wolves2WSommaire du Match
46 - 2019-11-18307IceHogs3Admirals2WSommaire du Match
47 - 2019-11-19314 Americans1IceHogs3WSommaire du Match
49 - 2019-11-21321Checkers3IceHogs2LSommaire du Match
51 - 2019-11-23337Crunch1IceHogs6WSommaire du Match
53 - 2019-11-25351IceHogs3Stars2WSommaire du Match
56 - 2019-11-28374Stars0IceHogs8WSommaire du Match
59 - 2019-12-01396Eagles2IceHogs10WSommaire du Match
60 - 2019-12-02405IceHogs11Eagles1WSommaire du Match
62 - 2019-12-04421Rampage 0IceHogs11WSommaire du Match
65 - 2019-12-07438IceHogs4Bruins0WSommaire du Match
66 - 2019-12-08449IceHogs10Devils1WSommaire du Match
68 - 2019-12-10463Roadrunners2IceHogs13WSommaire du Match
70 - 2019-12-12482IceHogs2Wolves0WSommaire du Match
72 - 2019-12-14488IceHogs9Roadrunners2WSommaire du Match
74 - 2019-12-16513IceHogs5Rampage 1WSommaire du Match
75 - 2019-12-17515Wild0IceHogs11WSommaire du Match
78 - 2019-12-20535Eagles1IceHogs9WSommaire du Match
79 - 2019-12-21547IceHogs8Moose1WSommaire du Match
81 - 2019-12-23556IceHogs11Eagles0WSommaire du Match
83 - 2019-12-25570Devils1IceHogs8WSommaire du Match
87 - 2019-12-29584Sound Tigers2IceHogs10WSommaire du Match
89 - 2019-12-31605IceHogs2Monsters7LSommaire du Match
91 - 2020-01-02617IceHogs1Heat7LSommaire du Match
93 - 2020-01-04636IceHogs2Comets1WSommaire du Match
96 - 2020-01-07655Griffins2IceHogs8WSommaire du Match
98 - 2020-01-09665Heat9IceHogs1LSommaire du Match
100 - 2020-01-11681Admirals2IceHogs6WSommaire du Match
102 - 2020-01-13695Gulls1IceHogs0LSommaire du Match
105 - 2020-01-16720IceHogs4Senators3WSommaire du Match
106 - 2020-01-17725IceHogs4Rocket5LXXSommaire du Match
109 - 2020-01-20753IceHogs6Marlies3WSommaire du Match
110 - 2020-01-21756Moose1IceHogs4WSommaire du Match
112 - 2020-01-23763Thunderbirds5IceHogs6WSommaire du Match
123 - 2020-02-03792IceHogs7Roadrunners1WSommaire du Match
126 - 2020-02-06817IceHogs7Wild1WSommaire du Match
127 - 2020-02-07825Bruins3IceHogs8WSommaire du Match
131 - 2020-02-11859IceHogs5Moose0WSommaire du Match
133 - 2020-02-13870IceHogs3Condors2WSommaire du Match
134 - 2020-02-14879IceHogs2Comets1WXSommaire du Match
137 - 2020-02-17897IceHogs5Heat4WSommaire du Match
138 - 2020-02-18914IceHogs3Moose2WSommaire du Match
141 - 2020-02-21928Wolf Pack3IceHogs9WSommaire du Match
143 - 2020-02-23944Admirals0IceHogs11WSommaire du Match
145 - 2020-02-25961IceHogs6Stars1WSommaire du Match
147 - 2020-02-27978IceHogs9Rampage 1WSommaire du Match
149 - 2020-02-29992IceHogs2Crunch1WSommaire du Match
151 - 2020-03-021001IceHogs9Thunderbirds3WSommaire du Match
154 - 2020-03-051019Gulls3IceHogs2LXSommaire du Match
156 - 2020-03-071034Condors3IceHogs2LSommaire du Match
157 - 2020-03-081045IceHogs4Griffins2WSommaire du Match
159 - 2020-03-101061Rampage 1IceHogs13WSommaire du Match
162 - 2020-03-131079Barracudas2IceHogs8WSommaire du Match
164 - 2020-03-151094Senators0IceHogs5WSommaire du Match
165 - 2020-03-161108IceHogs5Bears3WSommaire du Match
168 - 2020-03-191126IceHogs7Wild2WSommaire du Match
170 - 2020-03-211139Wild0IceHogs7WSommaire du Match
172 - 2020-03-231153IceHogs2 Americans5LSommaire du Match
173 - 2020-03-241165Admirals1IceHogs12WSommaire du Match
176 - 2020-03-271186Penguins1IceHogs6WSommaire du Match
178 - 2020-03-291199Stars2IceHogs9WSommaire du Match
180 - 2020-03-311216Reign0IceHogs8WSommaire du Match
182 - 2020-04-021230Rocket7IceHogs2LSommaire du Match
184 - 2020-04-041248IceHogs7Sound Tigers1WSommaire du Match
186 - 2020-04-061267IceHogs8Wolf Pack0WSommaire du Match



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité de l'Aréna20001000
Prix des Billets350
Assistance72,75835,023
Assistance PCT88.73%85.42%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
0 2629 - 87.63% 62,110$2,546,530$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
2,524,708$ 1,246,667$ 1,246,667$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
6,703$ 1,184,747$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 0 13,907$ 0$





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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
201982709011015131613524135500100291792124135401001222821401445138971410015235161116134221151113511354141941069214902525120.24%2603287.69%21775251070.72%971151664.05%976136071.76%279422501284398850501
Total Saison Régulière82709011015131613524135500100291792124135401001222821401445138971410015235161116134221151113511354141941069214902525120.24%2603287.69%21775251070.72%971151664.05%976136071.76%279422501284398850501