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Connexion

Chill
GP: 82 | W: 32 | L: 44 | OTL: 6 | P: 70
GF: 290 | GA: 339 | PP%: 17.00% | PK%: 76.06%
DG: Maxime Pigeon-Gosselin | Morale : 50 | Moyenne d’équipe : 54
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Centre de jeu
Chill
32-44-6, 70pts
4
FINAL
7 Heat
35-40-7, 77pts
Team Stats
W1StreakL1
21-19-1Home Record19-17-5
11-25-5Away Record16-23-2
4-4-2Last 10 Games5-4-1
3.54Buts par match 3.50
4.13Buts contre par match 3.76
17.00%Pourcentage en avantage numérique23.53%
76.06%Pourcentage en désavantage numérique78.33%
Minnesota
34-41-7, 75pts
5
FINAL
8 Chill
32-44-6, 70pts
Team Stats
L4StreakW1
22-17-2Home Record21-19-1
12-24-5Away Record11-25-5
3-6-1Last 10 Games4-4-2
3.01Buts par match 3.54
3.38Buts contre par match 4.13
20.23%Pourcentage en avantage numérique17.00%
79.69%Pourcentage en désavantage numérique76.06%
Meneurs d'équipe
Buts
Rafael Harvey-Pinard
38
Passes
Scott Reedy
56
Points
Scott Reedy
90
Plus/Moins
Jakub Lauko
4
Victoires
Keith Petruzzelli
15
Pourcentage d’arrêts
Rasmus Korhonen
0.935

Statistiques d’équipe
Buts pour
290
3.54 GFG
Tirs pour
3517
42.89 Avg
Pourcentage en avantage numérique
17.0%
42 GF
Début de zone offensive
42.5%
Buts contre
339
4.13 GAA
Tirs contre
3320
40.49 Avg
Pourcentage en désavantage numérique
76.1%%
51 GA
Début de la zone défensive
38.2%
Informations de l'équipe

Directeur généralMaxime Pigeon-Gosselin
DivisionAtlantique
ConférenceEst
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance2,896
Billets de saison300


Informations de la formation

Équipe Pro21
Équipe Mineure23
Limite contact 44 / 50
Espoirs27


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
1Scott ReedyX100.00634290697659716953567263254747050610223800,000$
2Rafael Harvey-PinardXX100.00726490706463636379626163584444050600221825,000$
3James HamblinXX100.006962866762666859745063606044440505702221,000,000$
4Evan BarrattX100.00696870646861635670505860554444050560222870,000$
5Lauri Pajuniemi (R)X100.00746791656751505950536163584444050560223883,750$
6Gage Goncalves (R)X100.00726783636757575771506061574444050560204820,000$
7Yaroslav Likhachyok (R)X100.00443799716272915857515545585454050560204560,000$
8Luke Toporowski (R)X100.00453999696569895455445544585454050540204560,000$
9Jakub Lauko (R)XX100.00666471676457595164524657444444050530213764,167$
10Josh Lopina (R)X100.00767286617238355164514662444444050520204878,333$
11Jacob Bernard-Docker (R)X100.00654285757065625825504765254545050590213925,000$
12John Ludvig (R)X100.00707571627554555425474661464444050550212853,333$
13Samuel Sjolund (R)X100.00453999656465953925393243345454050520204560,000$
14Josh Maniscalco (R)X100.00757684597644463925263660364444050510223853,333$
Rayé
1Raphael Lavoie (R)XX100.00807591687557585771515965564444050580212870,000$
2Declan McDonnell (R)XXX100.00706887626855584659434159414444050510193700,000$
3Jay O'Brien (R)X100.00484584676748524954394847535454050500213895,000$
4Vladislav Firstov (R)X100.00474199666756724552374443465454050490204925,000$
5Patrick Moynihan (R)X100.00474299656858784253383842405454050480204560,000$
6Grant HuttonX100.00734491657764695925394868254545050590262800,000$
MOYENNE D’ÉQUIPE100.0064568866695865535346515746474705055
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 moyen
Rayé
1Rasmus Korhonen (R)100.0044405085454445494545454444050490184650,000$
MOYENNE D’ÉQUIPE100.004440508545444549454545444405049
Nom de l’entraîneur 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
1Scott ReedyChill (Nas)C81345690-12100662064181033128.13%40164320.29781568186011111882147.08%192000021.1024000453
2Rasmus KupariNashvilleC/RW79314677-182201563063861072868.03%28182923.16311145920000051672249.60%249400000.8404000664
3Lauri PajuniemiChill (Nas)RW81284876-12380118109291801989.62%32141817.515101556182000015334.41%9300001.0711000423
4Rafael Harvey-PinardChill (Nas)C/LW81383674-18801051764161453299.13%38169020.8787156720901111975162.02%25800120.8814000334
5Gage GoncalvesChill (Nas)C81273663-42551341232466219110.98%30138417.1000002000004054.60%31500010.9100100422
6Evan BarrattChill (Nas)C81203656-154410138215281851747.12%30139217.190000110113864055.84%158300000.8000010421
7James HamblinChill (Nas)C/LW81232952-20155118126293972247.85%36148018.2854942186000073158.06%9300000.7011010322
8Jacob Bernard-DockerChill (Nas)D73123951-13400123110149581098.05%130174023.84268591901122150200.00%000000.5900000132
9Ben GleasonNashvilleD75132942-22521013269112416611.61%118151920.265914481670002134130.00%000000.5500101121
10Raphael LavoieChill (Nas)C/RW73122840-21622011989286731654.20%25147520.223710431831017760056.19%10500000.5401211011
11Yaroslav LikhachyokChill (Nas)LW81142539-20551109221641266.33%4128015.8100002000000053.41%8800000.6100001002
12John LudvigChill (Nas)D8182634-2112135160549725618.25%125156119.28145341650000118000.00%000000.4400007011
13Luke ToporowskiChill (Nas)LW8181927-2240893361304913.11%83127615.7700000000000087.50%800000.4200000001
14Pierre-Olivier JosephNashvilleD4771724-13495130449028737.78%76111023.6311233133000183100.00%000000.4300100121
15Samuel SjolundChill (Nas)D8121012-932070131571613.33%74130816.15000229000067010.00%000000.1800000010
16Jakub LaukoChill (Nas)C/LW8128104401220299186.90%112643.270003420003530150.43%11500000.7600000000
17Josh LopinaChill (Nas)C8102210011812280.00%71071.33000220000070036.36%1100000.3700000000
18Declan McDonnellChill (Nas)C/LW/RW5000100000110.00%071.500000100003000.00%200000.00%00000000
Statistiques d’équipe totales ou en moyenne1324279490769-21455195168218103403101724068.20%8872249316.9940671075161917246451245291351.07%708500150.685155310313228
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 PetruzzelliNashville36151620.8934.3119782014213280020.8758354020
2Lukas ParikNashville3292020.8914.1517076111810840200.3333317311
3Rasmus KorhonenChill (Nas)103500.9352.6549820223380220.00%0627100
Statistiques d’équipe totales ou en moyenne78274140.8974.0441841012822750044117238431


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 moyen restantPlafond 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
Declan McDonnellChill (Nas)C/LW/RW192002-02-25Yes190 Lbs5 ft10YesNoNo3Pro & Farm700,000$0$0$No700,000$700,000$Lien
Evan BarrattChill (Nas)C221999-02-18No188 Lbs6 ft0NoNoNo2Pro & Farm870,000$0$0$No870,000$Lien
Gage GoncalvesChill (Nas)C202001-01-16Yes181 Lbs6 ft0NoNoNo4Pro & Farm820,000$0$0$No820,000$820,000$820,000$Lien
Grant Hutton (contrat à 1 volet)Chill (Nas)D261995-07-25No205 Lbs6 ft3YesNoYes2Pro & Farm800,000$0$0$No800,000$Lien
Jacob Bernard-DockerChill (Nas)D212000-06-30Yes190 Lbs6 ft0NoNoNo3Pro & Farm925,000$0$0$No925,000$925,000$Lien
Jakub LaukoChill (Nas)C/LW212000-03-28Yes170 Lbs6 ft0NoNoNo3Pro & Farm764,167$0$0$No764,167$764,167$Lien
James HamblinChill (Nas)C/LW221999-04-27No176 Lbs5 ft9YesNoNo2Pro & Farm1,000,000$0$0$No1,000,000$Lien
Jay O'BrienChill (Nas)C211999-11-04Yes185 Lbs6 ft0NoNoNo3Pro & Farm895,000$0$0$No895,000$895,000$Lien
John LudvigChill (Nas)D212000-08-02Yes205 Lbs6 ft1NoNoNo2Pro & Farm853,333$0$0$No853,333$Lien
Josh LopinaChill (Nas)C202001-02-16Yes194 Lbs6 ft2NoNoNo4Pro & Farm878,333$0$0$No878,333$878,333$878,333$Lien
Josh ManiscalcoChill (Nas)D221999-02-17Yes205 Lbs6 ft2NoNoNo3Pro & Farm853,333$0$0$No853,333$853,333$Lien
Lauri PajuniemiChill (Nas)RW221999-09-12Yes183 Lbs6 ft0NoNoNo3Pro & Farm883,750$0$0$No883,750$883,750$Lien
Luke ToporowskiChill (Nas)LW202001-04-12Yes181 Lbs5 ft11NoNoNo4Pro & Farm560,000$0$0$No560,000$560,000$560,000$Lien
Patrick MoynihanChill (Nas)C202001-01-23Yes190 Lbs5 ft11NoNoNo4Pro & Farm560,000$0$0$No560,000$560,000$560,000$Lien
Rafael Harvey-PinardChill (Nas)C/LW221999-01-06No183 Lbs5 ft9NoNoNo1Pro & Farm825,000$0$0$NoLien
Raphael LavoieChill (Nas)C/RW212000-09-25Yes196 Lbs6 ft4NoNoNo2Pro & Farm870,000$0$0$No870,000$Lien
Rasmus KorhonenChill (Nas)G182002-10-22Yes201 Lbs6 ft5NoNoNo4Pro & Farm650,000$0$0$No650,000$650,000$650,000$Lien
Samuel SjolundChill (Nas)D202001-05-19Yes174 Lbs6 ft1NoNoNo4Pro & Farm560,000$0$0$No560,000$560,000$560,000$Lien
Scott ReedyChill (Nas)C221999-04-04No209 Lbs6 ft2NoNoNo3Pro & Farm800,000$0$0$No800,000$800,000$Lien
Vladislav FirstovChill (Nas)LW202001-06-19Yes181 Lbs6 ft1NoNoNo4Pro & Farm925,000$0$0$No925,000$925,000$925,000$Lien
Yaroslav LikhachyokChill (Nas)LW202001-09-02Yes178 Lbs5 ft10NoNoNo4Pro & Farm560,000$0$0$No560,000$560,000$560,000$Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2120.95189 Lbs6 ft03.05788,234$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Rafael Harvey-Pinard40122
2Gage GoncalvesScott ReedyLauri Pajuniemi30122
3Yaroslav LikhachyokEvan BarrattJames Hamblin20122
4Luke ToporowskiGage Goncalves10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
140122
2John Ludvig30122
3Samuel SjolundLuke Toporowski20122
410122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Rafael Harvey-Pinard60122
2James HamblinScott ReedyLauri Pajuniemi40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
160122
2John Ludvig40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Scott Reedy60122
2Rafael Harvey-Pinard40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
160122
2John Ludvig40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
16012260122
2Scott Reedy40122John Ludvig40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Scott Reedy60122
2Rafael Harvey-Pinard40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
160122
2John Ludvig40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Rafael Harvey-Pinard
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Rafael Harvey-Pinard
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Jakub Lauko, Josh Lopina, Evan BarrattJakub Lauko, Josh LopinaEvan Barratt
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Samuel Sjolund, , John LudvigSamuel Sjolund, John Ludvig
Tirs de pénalité
, Scott Reedy, Rafael Harvey-Pinard, , James Hamblin
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
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
1Admirals3210000011110110000003212110000089-140.667112031001169176101331184112311755012440207310330.00%9188.89%01636310352.72%1383278549.66%687140948.76%1909131820076011055524
2Baby Hawks30200010710-31010000013-22010001067-120.33371017001169176101081184112311755093362059500.00%8275.00%01636310352.72%1383278549.66%687140948.76%1909131820076011055524
3Bears20200000711-41010000036-31010000045-100.00071219001169176107811841123117550872410437228.57%5260.00%01636310352.72%1383278549.66%687140948.76%1909131820076011055524
4Bruins2010010059-41010000014-31000010045-110.250581300116917610671184112311755083254941500.00%5180.00%01636310352.72%1383278549.66%687140948.76%1909131820076011055524
5Cabaret Lady Mary Ann220000001358110000006331100000072541.000132437001169176101651184112311755082284423133.33%20100.00%01636310352.72%1383278549.66%687140948.76%1909131820076011055524
6Caroline21100000711-4110000006511010000016-520.500712190011691761096118411231175508022437800.00%2150.00%01636310352.72%1383278549.66%687140948.76%1909131820076011055524
7Chiefs402010011216-42010100056-120100001710-330.37512203210116917610174118411231175501383067615426.67%2150.00%01636310352.72%1383278549.66%687140948.76%1909131820076011055524
8Comets31200000713-6110000005412020000029-720.3337142100116917610129118411231175501353514671218.33%6350.00%11636310352.72%1383278549.66%687140948.76%1909131820076011055524
9Cougars20200000812-41010000057-21010000035-200.000814221011691761082118411231175501012523415240.00%8187.50%01636310352.72%1383278549.66%687140948.76%1909131820076011055524
10Crunch20101000910-1100010004311010000057-220.50091827101169176107211841123117550882619469222.22%7271.43%01636310352.72%1383278549.66%687140948.76%1909131820076011055524
11Heat312000001114-31100000052320200000612-620.3331119300011691761013111841123117550109334556600.00%13653.85%01636310352.72%1383278549.66%687140948.76%1909131820076011055524
12Jayhawks412001001215-3211000007702010010058-330.375121931001169176101551184112311755017045181011000.00%9366.67%01636310352.72%1383278549.66%687140948.76%1909131820076011055524
13Las Vegas33000000171162200000012931100000052361.00017294600116917610128118411231175501223216637457.14%8362.50%01636310352.72%1383278549.66%687140948.76%1909131820076011055524
14Manchots20000101810-21000010056-11000000134-120.50081523001169176108411841123117550722816406233.33%70100.00%01636310352.72%1383278549.66%687140948.76%1909131820076011055524
15Marlies2010100056-11010000013-21000100043120.5005712001169176108711841123117550833512379222.22%6183.33%01636310352.72%1383278549.66%687140948.76%1909131820076011055524
16Minnesota32100000171432200000012841010000056-140.66717324900116917610136118411231175501134616866350.00%8275.00%01636310352.72%1383278549.66%687140948.76%1909131820076011055524
17Monarchs3210000015141211000009901100000065140.66715284300116917610205118411231175501193018679111.11%9188.89%01636310352.72%1383278549.66%687140948.76%1909131820076011055524
18Monsters2020000048-41010000025-31010000023-100.0004610001169176106311841123117550863419438112.50%7185.71%01636310352.72%1383278549.66%687140948.76%1909131820076011055524
19Monsters413000001116-52110000067-12020000059-420.250112132001169176101391184112311755015248349517317.65%12283.33%01636310352.72%1383278549.66%687140948.76%1909131820076011055524
20Oceanics4220000013121220000008442020000058-340.500132235001169176101341184112311755015544376918316.67%90100.00%01636310352.72%1383278549.66%687140948.76%1909131820076011055524
21Oil Kings30300000415-1120200000411-71010000004-400.000461000116917610124118411231175501253924536116.67%10370.00%01636310352.72%1383278549.66%687140948.76%1909131820076011055524
22Phantoms22000000963110000005321100000043141.00091726001169176109211841123117550681363812325.00%3166.67%01636310352.72%1383278549.66%687140948.76%1909131820076011055524
23Rocket210000101358110000007071000001065141.000132134011169176101001184112311755079201245300.00%5260.00%01636310352.72%1383278549.66%687140948.76%1909131820076011055524
24Seattle30300000714-720200000610-41010000014-300.0007142100116917610101118411231175501183024571119.09%11372.73%11636310352.72%1383278549.66%687140948.76%1909131820076011055524
25Senators2020000047-31010000034-11010000013-200.000481200116917610701184112311755067271445600.00%6183.33%01636310352.72%1383278549.66%687140948.76%1909131820076011055524
26Sharks310020001915410001000651210010001310361.00019375600116917610187118411231175501924014765240.00%7271.43%01636310352.72%1383278549.66%687140948.76%1909131820076011055524
27Sound Tigers20200000510-51010000024-21010000036-300.000581300116917610801184112311755068181247600.00%6266.67%01636310352.72%1383278549.66%687140948.76%1909131820076011055524
28Spiders20200000510-51010000034-11010000026-400.0005101500116917610871184112311755091171728500.00%6183.33%01636310352.72%1383278549.66%687140948.76%1909131820076011055524
29Stars42200000121112110000045-12110000086240.5001220321011691761014511841123117550146362983800.00%7185.71%01636310352.72%1383278549.66%687140948.76%1909131820076011055524
30Thunder21000100761110000003121000010045-130.75071118001169176108111841123117550692415695120.00%5180.00%01636310352.72%1383278549.66%687140948.76%1909131820076011055524
31Wolf Pack20200000612-61010000036-31010000036-300.00061218001169176108411841123117550105241042500.00%5180.00%01636310352.72%1383278549.66%687140948.76%1909131820076011055524
Total82254405422290339-4941181903100152156-44172502322138183-45700.42729051480441116917610351711841123117550332095457717652474217.00%2135176.06%21636310352.72%1383278549.66%687140948.76%1909131820076011055524
_Since Last GM Reset82254405422290339-4941181903100152156-44172502322138183-45700.42729051480441116917610351711841123117550332095457717652474217.00%2135176.06%21636310352.72%1383278549.66%687140948.76%1909131820076011055524
_Vs Conference35101803301123147-241769011005766-91849022016681-15300.4291232213440011691761015321184112311755014694232697581162017.24%951683.16%01636310352.72%1383278549.66%687140948.76%1909131820076011055524
_Vs Division165503100646048330100030255822021003435-1170.53164111175211169176107241184112311755065221014836645817.78%44979.55%01636310352.72%1383278549.66%687140948.76%1909131820076011055524

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
8270W129051480435173320954577176541
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
8225445422290339
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4118193100152156
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
417252322138183
Derniers 10 matchs
WLOTWOTL SOWSOL
440101
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
2474217.00%2135176.06%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
11841123117550116917610
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
1636310352.72%1383278549.66%687140948.76%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
1909131820076011055524


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
4 - 2022-10-101Sharks5Chill6BWXSommaire du match
5 - 2022-10-112Chill5Sharks4AWXSommaire du match
7 - 2022-10-1316Stars3Chill1BLSommaire du match
9 - 2022-10-1535Chill1Stars2ALSommaire du match
12 - 2022-10-1852Monarchs4Chill5BWSommaire du match
14 - 2022-10-2063Chill2Monsters3ALSommaire du match
16 - 2022-10-2283Phantoms3Chill5BWSommaire du match
21 - 2022-10-27115Chiefs2Chill3BWXSommaire du match
23 - 2022-10-29136Bears6Chill3BLSommaire du match
26 - 2022-11-01154Chill0Oil Kings4ALSommaire du match
28 - 2022-11-03169Chill2Heat5ALSommaire du match
30 - 2022-11-05186Chill0Comets4ALSommaire du match
33 - 2022-11-08205Chill1Seattle4ALSommaire du match
35 - 2022-11-10219Chill3Monsters4ALSommaire du match
37 - 2022-11-12232Wolf Pack6Chill3BLSommaire du match
40 - 2022-11-15254Minnesota3Chill4BWSommaire du match
42 - 2022-11-17267Sound Tigers4Chill2BLSommaire du match
44 - 2022-11-19285Thunder1Chill3BWSommaire du match
46 - 2022-11-21297Jayhawks4Chill3BLSommaire du match
48 - 2022-11-23311Chill3Cougars5ALSommaire du match
50 - 2022-11-25319Monsters4Chill2BLSommaire du match
51 - 2022-11-26338Monsters5Chill2BLSommaire du match
54 - 2022-11-29356Admirals2Chill3BWSommaire du match
56 - 2022-12-01366Chill2Spiders6ALSommaire du match
57 - 2022-12-02377Chill3Sound Tigers6ALSommaire du match
63 - 2022-12-08421Chill4Thunder5ALXSommaire du match
65 - 2022-12-10434Senators4Chill3BLSommaire du match
67 - 2022-12-12453Chill4Chiefs5ALXXSommaire du match
68 - 2022-12-13461Oil Kings4Chill1BLSommaire du match
70 - 2022-12-15477Chill3Oceanics4ALSommaire du match
72 - 2022-12-17493Chill2Monsters5ALSommaire du match
74 - 2022-12-19505Oil Kings7Chill3BLSommaire du match
76 - 2022-12-21521Chill2Baby Hawks4ALSommaire du match
78 - 2022-12-23539Monsters3Chill4BWSommaire du match
82 - 2022-12-27551Stars2Chill3BWSommaire du match
85 - 2022-12-30574Chill6Admirals5AWSommaire du match
86 - 2022-12-31579Chill5Las Vegas2AWSommaire du match
89 - 2023-01-03604Rocket0Chill7BWSommaire du match
91 - 2023-01-05614Chill1Caroline6ALSommaire du match
92 - 2023-01-06622Chill4Bears5ALSommaire du match
95 - 2023-01-09645Chill1Senators3ALSommaire du match
97 - 2023-01-11658Chill4Marlies3AWXSommaire du match
98 - 2023-01-12664Chill6Rocket5AWXXSommaire du match
100 - 2023-01-14686Crunch3Chill4BWXSommaire du match
102 - 2023-01-16703Heat2Chill5BWSommaire du match
105 - 2023-01-19724Chill3Chiefs5ALSommaire du match
107 - 2023-01-21742Monarchs5Chill4BLSommaire du match
110 - 2023-01-24762Oceanics2Chill3BWSommaire du match
112 - 2023-01-26775Spiders4Chill3BLSommaire du match
124 - 2023-02-07817Las Vegas6Chill7BWSommaire du match
128 - 2023-02-11836Chill4Phantoms3AWSommaire du match
130 - 2023-02-13851Jayhawks3Chill4BWSommaire du match
133 - 2023-02-16873Bruins4Chill1BLSommaire du match
135 - 2023-02-18884Cabaret Lady Mary Ann3Chill6BWSommaire du match
136 - 2023-02-19896Chill5Minnesota6ALSommaire du match
138 - 2023-02-21914Comets4Chill5BWSommaire du match
140 - 2023-02-23929Chill8Sharks6AWSommaire du match
143 - 2023-02-26953Chill3Jayhawks4ALXSommaire du match
145 - 2023-02-28963Manchots6Chill5BLXSommaire du match
147 - 2023-03-02975Chill7Cabaret Lady Mary Ann2AWSommaire du match
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
149 - 2023-03-04998Chill4Baby Hawks3AWXXSommaire du match
151 - 2023-03-061010Chill2Comets5ALSommaire du match
154 - 2023-03-091034Chill2Jayhawks4ALSommaire du match
156 - 2023-03-111052Chill6Monarchs5AWSommaire du match
157 - 2023-03-121060Chill2Admirals4ALSommaire du match
159 - 2023-03-141069Cougars7Chill5BLSommaire du match
161 - 2023-03-161085Baby Hawks3Chill1BLSommaire du match
163 - 2023-03-181097Oceanics2Chill5BWSommaire du match
164 - 2023-03-191112Chill3Wolf Pack6ALSommaire du match
166 - 2023-03-211124Chill5Crunch7ALSommaire du match
168 - 2023-03-231142Seattle7Chill4BLSommaire du match
170 - 2023-03-251152Seattle3Chill2BLSommaire du match
171 - 2023-03-261167Marlies3Chill1BLSommaire du match
173 - 2023-03-281178Chill4Bruins5ALXSommaire du match
175 - 2023-03-301192Chill3Manchots4ALXXSommaire du match
177 - 2023-04-011204Chiefs4Chill2BLSommaire du match
179 - 2023-04-031227Chill7Stars4AWSommaire du match
180 - 2023-04-041235Las Vegas3Chill5BWSommaire du match
182 - 2023-04-061250Caroline5Chill6BWSommaire du match
184 - 2023-04-081261Chill2Oceanics4ALSommaire du match
186 - 2023-04-101282Chill4Heat7ALSommaire du match
189 - 2023-04-131305Minnesota5Chill8BWSommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3515
Assistance79,62239,110
Assistance PCT97.10%95.39%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
0 2896 - 96.53% 82,279$3,373,420$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
1,926,644$ 2,375,291$ 2,375,291$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
12,502$ 1,926,644$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 0 12,502$ 0$




Chill 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

Chill 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

Chill 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

Chill 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

Chill 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