Checkers
GP: 80 | W: 45 | L: 31 | OTL: 4 | P: 94
GF: 336 | GA: 317 | PP%: 22.65% | PK%: 74.32%
DG: Jean-Francois Chouinard | Morale : 50 | Moyenne d'Équipe : 63
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Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du Joueur C L R D CON CK FG DI SK ST EN DU PH FO PA SC DF PS EX LD PO MO OV TA SPÂgeContratSalaire
1Michael Latta (R)X100.007138687980678075697674676654484170710242900,000$
2Jonathan Huberdeau (R) (A)X100.007325757474757577748873566649455566710224990,000$
3Aleksander Barkov (R) (C)X100.007550767873737475717873607145426452710204850,000$
4Tobias Rieder (R)X100.0073458072717176777573736569524559647002211,000,000$
5Quinton Howden (R)X100.007136757568687175667466646846454770680232500,000$
6Jerry D'Amigo (R)X100.006534787267776867667067656846463860660243700,000$
7Kerby Rychel (R)X100.008149687374607874636567606645445757660213700,000$
8Jake Virtanen (R)X100.007239696679567768636770515141416670640191500,000$
9Mitchell Heard (R)X100.007232646975566559586968655547473727630233500,000$
10Matt Puempel (R)X100.006438766865636566606167476844445660620224500,000$
11Roberts Lipsbergs (R)X100.006930705871676461726163516444455059600212400,000$
12Michael McCarron (R)X100.007444616277537959616460436142425670590202500,000$
13Aaron Ekblad (R)X100.007446847470767176517466735947418067710191500,000$
14Michal Jordan (R)X100.006624827274776970577370706365593661700252600,000$
15William ColbertX100.007237807066667765547165745878641870700301800,000$
16John Draeger (R)X100.006622757070666756397058805447464558670222500,000$
17Markus Nutivaara (R)X100.005735727360526785328756694744436827660212500,000$
18Niklas Hansson (R)X100.006616777261727057407146825148425368660202400,000$
Rayé
1Kyle Platzer (R)X100.004034676541645172566360567742424919590202400,000$
2Juuso Ikonen (R)X100.005028716558535167575860566042425319580202400,000$
3Anton Zlobin (R)X100.005721636356585661526167405545463919570221400,000$
4Connor Honey (R)X100.006457595267597640554247465642425120520202400,000$
5Lukas Vejdemo (R)X100.004229756152605248595254494842425820520192500,000$
6Dmytro Timashov (R)X100.004724654647455559556440425242425820490192500,000$
7Viktor Baldayev (R)X100.006848676273626864395746684643425419630202400,000$
8Keaton Thompson (R)X100.005636666956556860436854685243425720610202400,000$
9Nelson Nogier (R)X100.006337705863645953336154674141416020600191500,000$
10Jake Walman (R)X100.005832786667665852335738703641416618600191500,000$
MOYENNE D'ÉQUIPE100.00653572676664676555676161584745534563
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
1Garret Sparks100.0072718759647279556380714644487068X0
2Igor Bobkov100.00736366716970756767628048463470680
Rayé
1Marek Langhamer100.00614658626953555856497043435120570
MOYENNE D'ÉQUIPE100.0069607064676570606264744644445364
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Glen Gulutzan54607666334563CAN421350,000$


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
1Michael LattaCheckers (Flo)C804359102247201721902679817216.10%50160720.09817253323511272877348.66%18334430021.27010001055
2Tobias RiederCheckers (Flo)RW7942529419595121952868515814.69%46179622.7417203755278101112753153.41%1763630021.0515001556
3Aleksander BarkovCheckers (Flo)C55334982163588851995012316.58%21107019.4714223634205000034151.15%16153917011.5326001755
4Jonathan HuberdeauCheckers (Flo)LW482839679280103601795014615.64%23101521.1551217191640113702258.89%903613001.3213000343
5Aaron EkbladCheckers (Flo)D78105363722010016216374746.13%131221728.4331316263020225321300.00%04662000.5701000222
6Jerry D'AmigoCheckers (Flo)RW803025551424010168149408420.13%26108513.5730336521381135057.58%333021101.0111000252
7Quinton HowdenCheckers (Flo)C801635513400126106176751099.09%29113114.1422475912391801145.59%5902513000.9000000242
8Kerby RychelCheckers (Flo)LW78272350249511563163488916.56%20100612.91336111260001401245.71%352714110.9923000512
9Michal JordanCheckers (Flo)D7611374841808610911540569.57%98169622.3345921270011034300.00%03465000.5700000116
10Markus NutivaaraCheckers (Flo)D7743842-238957510814155682.84%94161520.9827916215000139100.00%02643000.5201000000
11Jake VirtanenCheckers (Flo)RW80222042-660010363138388415.94%19112414.0625711172101102250.67%75226000.7502000112
12William ColbertCheckers (Flo)D807182518260941228539378.24%89162920.3734782030220200110.00%02242000.3100000001
13Matt PuempelCheckers (Flo)LW75915240180794173265212.33%788211.76123358000011034.78%2378000.5400000002
14John DraegerCheckers (Flo)D7821719916061814716254.26%61113014.490000340001212000.00%01432000.3400000010
15Mitchell HeardCheckers (Flo)C4651116-332054557220466.94%64219.17000000001111043.75%1601510000.7600000000
16Roberts LipsbergsCheckers (Flo)LW791141512200623259153218.64%106758.55000070000220147.06%1769000.4400000121
17Niklas HanssonCheckers (Flo)D791141516435631055230291.92%91126516.02000080002313000.00%01037000.2400000010
18Stefan RuzickaPanthersRW1278153100162046133215.22%524020.021235371014391157.89%76111011.2500000200
19Michael McCarronCheckers (Flo)RW8068147480852046133013.04%56337.9100004000000245.45%1154000.4400000011
20Kyle PlatzerCheckers (Flo)C22731048051935142520.00%42039.24000110000172040.26%7773000.9800000001
21Keaton ThompsonCheckers (Flo)D21010202422150.00%54221.351011500001000.00%012000.4700000000
22Anton ZlobinCheckers (Flo)RW110110000100100.00%066.480000000000000.00%000003.0800000000
23Viktor BaldayevCheckers (Flo)D1300011151384130.00%615511.930000100004000.00%006000.0000001000
24Juuso IkonenCheckers (Flo)LW6000-200635310.00%0559.270000000006000.00%011000.0000000000
25Jake WalmanCheckers (Flo)D3000-100010000.00%062.310000000001000.00%000000.0000000000
Stats d'équipe Total ou en Moyenne138732352885111975830173016202503845147612.90%8462271616.3869114183254246071017542201381749.32%4811464469270.75723003413841
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
1Igor BobkovCheckers (Flo)64371620.8833.7134011002101800905220.714146020210
2Garret SparksCheckers (Flo)3181520.8654.28143120102756385300.75082060111
Stats d'équipe Total ou en Moyenne95453140.8783.87483312031225561290520.727228080321


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
Aaron EkbladCheckers (Flo)D191996-01-01Yes180 Lbs6 ft0NoNoNo1Pro & Farm500,000$0$0$No
Aleksander BarkovCheckers (Flo)C201995-01-01Yes185 Lbs6 ft4NoNoNo4Pro & Farm850,000$0$0$No1,750,000$3,000,000$4,250,000$
Anton ZlobinCheckers (Flo)RW221993-01-01Yes180 Lbs6 ft0NoNoNo1Pro & Farm400,000$0$0$No
Connor HoneyCheckers (Flo)RW201995-01-01Yes185 Lbs6 ft1NoNoNo2Pro & Farm400,000$0$0$No500,000$
Dmytro TimashovCheckers (Flo)LW191996-01-01Yes192 Lbs5 ft10NoNoNo2Pro & Farm500,000$0$0$No500,000$
Garret SparksCheckers (Flo)G221993-01-01No207 Lbs6 ft2NoYesNo2Pro & Farm999,999$0$0$No999,999$
Igor BobkovCheckers (Flo)G241991-01-01No235 Lbs6 ft5NoNoNo2Pro & Farm600,000$0$0$No600,000$
Jake VirtanenCheckers (Flo)RW191996-01-01Yes226 Lbs6 ft1NoNoNo1Pro & Farm500,000$0$0$No
Jake WalmanCheckers (Flo)D191996-01-01Yes180 Lbs6 ft0NoNoNo1Pro & Farm500,000$0$0$No
Jerry D'AmigoCheckers (Flo)RW241991-01-01Yes208 Lbs5 ft11NoNoNo3Pro & Farm700,000$0$0$No800,000$850,000$
John DraegerCheckers (Flo)D221993-01-01Yes186 Lbs6 ft1NoNoNo2Pro & Farm500,000$0$0$No500,000$
Jonathan HuberdeauCheckers (Flo)LW221993-01-01Yes188 Lbs6 ft1NoNoNo4Pro & Farm990,000$0$0$No3,000,000$3,000,000$3,500,000$
Juuso IkonenCheckers (Flo)LW201995-01-01Yes185 Lbs5 ft9NoNoNo2Pro & Farm400,000$0$0$No500,000$
Keaton ThompsonCheckers (Flo)D201995-01-01Yes185 Lbs6 ft0NoNoNo2Pro & Farm400,000$0$0$No500,000$
Kerby RychelCheckers (Flo)LW211994-01-01Yes185 Lbs6 ft1NoNoNo3Pro & Farm700,000$0$0$No800,000$900,000$
Kyle PlatzerCheckers (Flo)C201995-01-01Yes185 Lbs5 ft11NoNoNo2Pro & Farm400,000$0$0$No500,000$
Lukas VejdemoCheckers (Flo)C191996-01-01Yes194 Lbs6 ft4NoNoNo2Pro & Farm500,000$0$0$No500,000$
Marek LanghamerCheckers (Flo)G211994-01-01No181 Lbs6 ft1NoNoNo1Pro & Farm300,000$0$0$No
Markus NutivaaraCheckers (Flo)D211994-01-01Yes187 Lbs6 ft1NoNoNo2Pro & Farm500,000$0$0$No500,000$
Matt PuempelCheckers (Flo)LW221993-01-01Yes190 Lbs6 ft0NoNoNo4Pro & Farm500,000$0$0$No550,000$600,000$600,000$
Michael LattaCheckers (Flo)C241991-01-01Yes209 Lbs6 ft0NoNoNo2Pro & Farm900,000$0$0$No1,000,000$
Michael McCarronCheckers (Flo)RW201995-01-01Yes185 Lbs6 ft5NoNoNo2Pro & Farm500,000$0$0$No500,000$
Michal JordanCheckers (Flo)D251990-01-01Yes195 Lbs6 ft1NoNoNo2Pro & Farm600,000$0$0$No600,000$
Mitchell HeardCheckers (Flo)C231992-01-01Yes188 Lbs6 ft0NoNoNo3Pro & Farm500,000$0$0$No500,000$500,000$
Nelson NogierCheckers (Flo)D191996-01-01Yes191 Lbs6 ft2NoNoNo1Pro & Farm500,000$0$0$No
Niklas HanssonCheckers (Flo)D201995-01-01Yes185 Lbs6 ft1NoNoNo2Pro & Farm400,000$0$0$No500,000$
Quinton HowdenCheckers (Flo)C231992-01-01Yes189 Lbs6 ft2NoNoNo2Pro & Farm500,000$0$0$No600,000$
Roberts LipsbergsCheckers (Flo)LW211994-01-01Yes185 Lbs5 ft11NoNoNo2Pro & Farm400,000$0$0$No500,000$
Tobias RiederCheckers (Flo)RW221993-01-01Yes185 Lbs5 ft11NoNoNo1Pro & Farm1,000,000$0$0$No
Viktor BaldayevCheckers (Flo)D201995-01-01Yes185 Lbs6 ft3NoNoNo2Pro & Farm400,000$0$0$No500,000$
William ColbertCheckers (Flo)D301985-01-01No210 Lbs6 ft2NoNoNo1Pro & Farm800,000$0$0$No
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
3121.39192 Lbs6 ft12.03569,032$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Jonathan HuberdeauAleksander BarkovTobias Rieder40023
2Kerby RychelMichael LattaJerry D'Amigo30023
3Matt PuempelQuinton HowdenJake Virtanen20032
4Roberts LipsbergsMitchell HeardMichael McCarron10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Aaron EkbladMarkus Nutivaara40023
2Michal JordanWilliam Colbert30023
3John DraegerNiklas Hansson20122
4Aaron EkbladMarkus Nutivaara10023
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Jonathan HuberdeauAleksander BarkovTobias Rieder60014
2Kerby RychelMichael LattaJerry D'Amigo40014
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Aaron EkbladMarkus Nutivaara60023
2Michal JordanWilliam Colbert40023
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Michael LattaJerry D'Amigo60131
2Quinton HowdenTobias Rieder40131
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1John DraegerNiklas Hansson60140
2William ColbertAaron Ekblad40140
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Michael Latta60131John DraegerNiklas Hansson60140
2Mitchell Heard40131William ColbertAaron Ekblad40140
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Aleksander BarkovJonathan Huberdeau60023
2Michael LattaTobias Rieder40023
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Aaron EkbladMarkus Nutivaara60023
2William ColbertMichal Jordan40023
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Jonathan HuberdeauAleksander BarkovTobias RiederAaron EkbladMarkus Nutivaara
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Kerby RychelMichael LattaTobias RiederJohn DraegerNiklas Hansson
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Jake Virtanen, Jonathan Huberdeau, Aleksander BarkovJake Virtanen, Jonathan HuberdeauMichael Latta
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Niklas Hansson, Markus Nutivaara, Aaron EkbladWilliam ColbertAaron Ekblad, Niklas Hansson
Tirs de Pénalité
Aleksander Barkov, Tobias Rieder, Quinton Howden, Michael Latta, Jonathan Huberdeau
Gardien
#1 : Igor Bobkov, #2 : Garret Sparks


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
1Admirals220000001147110000005231100000062441.000112031008611812686885586384736522122437342.86%11372.73%0887179849.33%904182649.51%638133247.90%173695916397551466736
2Barracuda20200000712-51010000025-31010000057-200.000712190086118126875855863847366514183710110.00%9455.56%0887179849.33%904182649.51%638133247.90%173695916397551466736
3Bears3210000014104220000009451010000056-140.667142539008611812689185586384736913024808112.50%12375.00%0887179849.33%904182649.51%638133247.90%173695916397551466736
4Comets3110100012111100010006512110000066040.667122133008611812681028558638473610925166412433.33%8275.00%0887179849.33%904182649.51%638133247.90%173695916397551466736
5Condors220000001055110000003211100000073441.0001018280086118126865855863847365515264111218.18%13284.62%0887179849.33%904182649.51%638133247.90%173695916397551466736
6Crunch310010101293100010003212100001097261.000122032008611812689385586384736924718761317.69%9188.89%1887179849.33%904182649.51%638133247.90%173695916397551466736
7Devils43000010141043200001011831100000032181.000142034008611812681328558638473611647389514321.43%19478.95%0887179849.33%904182649.51%638133247.90%173695916397551466736
8Eagles614000102435-11312000001216-4302000101219-740.3332441651086118126819785586384736192788512134720.59%391366.67%1887179849.33%904182649.51%638133247.90%173695916397551466736
9Griffins20200000913-41010000045-11010000058-300.000915240086118126865855863847366117144911218.18%7271.43%0887179849.33%904182649.51%638133247.90%173695916397551466736
10Heat7430000026242321000001192422000001515080.5712639650086118126820985586384736216655615940717.50%28678.57%2887179849.33%904182649.51%638133247.90%173695916397551466736
11IceHogs21000100660110000004311000010023-130.7506101600861181268798558638473664221642300.00%8450.00%0887179849.33%904182649.51%638133247.90%173695916397551466736
12Influenza20200000510-51010000037-41010000023-100.000581300861181268578558638473665111642500.00%8362.50%0887179849.33%904182649.51%638133247.90%173695916397551466736
13Little Stars4220000016160312000001012-21100000064240.500162642008611812681338558638473612547327718316.67%16381.25%0887179849.33%904182649.51%638133247.90%173695916397551466736
14Monsters32000001981110000004312100000155050.833916250086118126890855863847361033924721417.14%12191.67%0887179849.33%904182649.51%638133247.90%173695916397551466736
15Moose2110000068-21010000026-41100000042220.5006101600861181268558558638473665252452200.00%12375.00%0887179849.33%904182649.51%638133247.90%173695916397551466736
16Penguins63200001332763210000018126311000011515070.58333528500861181268186855863847362105662135231043.48%26773.08%0887179849.33%904182649.51%638133247.90%173695916397551466736
17Phantoms21100000121111010000067-11100000064220.500122032008611812686585586384736651914449444.44%7528.57%0887179849.33%904182649.51%638133247.90%173695916397551466736
18Punishers3110001012102110000005322010001077040.667121830008611812681048558638473610334288411436.36%14378.57%0887179849.33%904182649.51%638133247.90%173695916397551466736
19Rampage413000001825-7211000001212020200000613-720.250182846008611812681388558638473613148429424833.33%221054.55%1887179849.33%904182649.51%638133247.90%173695916397551466736
20Reign220000001046110000005321100000051441.000101929008611812686985586384736571917407114.29%70100.00%0887179849.33%904182649.51%638133247.90%173695916397551466736
21Rocket2020000038-51010000023-11010000015-400.00034700861181268598558638473660191847800.00%9188.89%1887179849.33%904182649.51%638133247.90%173695916397551466736
22Senators33000000191091100000053222000000147761.00019325100861181268103855863847361103935548337.50%17664.71%0887179849.33%904182649.51%638133247.90%173695916397551466736
23Sound Tigers211000008711010000035-21100000052320.50081523108611812686085586384736572820407114.29%10280.00%0887179849.33%904182649.51%638133247.90%173695916397551466736
24Thunderbirds311000011091210000016331010000046-230.50010182800861181268978558638473698461664500.00%80100.00%0887179849.33%904182649.51%638133247.90%173695916397551466736
25Wolfpack64200000302553300000020911312000001016-680.66730558500861181268188855863847361966078125361130.56%39782.05%0887179849.33%904182649.51%638133247.90%173695916397551466736
Total8039310214333631719402214020111711492240171700132165168-3940.58833656289820861181268258085586384736255887175917773407722.65%3709574.32%6887179849.33%904182649.51%638133247.90%173695916397551466736
_Since Last GM Reset8039310214333631719402214020111711492240171700132165168-3940.58833656289820861181268258085586384736255887175917773407722.65%3709574.32%6887179849.33%904182649.51%638133247.90%173695916397551466736
_Vs Conference52251902042226211152615702011119942526101200031107117-10640.61522637059610861181268168285586384736169859250611482386125.63%2456274.69%5887179849.33%904182649.51%638133247.90%173695916397551466736
_Vs Division2512110001111311121284000006146151347000115265-13270.54011318730010861181268780855863847368142592815401333526.32%1323375.00%3887179849.33%904182649.51%638133247.90%173695916397551466736

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
8094W233656289825802558871759177720
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
8039312143336317
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4022142011171149
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
4017170132165168
Derniers 10 Matchs
WLOTWOTL SOWSOL
250021
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
3407722.65%3709574.32%6
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
85586384736861181268
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
887179849.33%904182649.51%638133247.90%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
173695916397551466736


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
1 - 2020-10-091Checkers1Heat5LR1Sommaire du Match
3 - 2020-10-1114Checkers4Penguins5LSommaire du Match
4 - 2020-10-1224Penguins3Checkers8WSommaire du Match
9 - 2020-10-1746Devils3Checkers4WSommaire du Match
11 - 2020-10-1958Wolfpack4Checkers7WR1Sommaire du Match
12 - 2020-10-2065Checkers6Eagles7LSommaire du Match
16 - 2020-10-2486Heat2Checkers5WR1Sommaire du Match
18 - 2020-10-2698Checkers3Heat5LSommaire du Match
20 - 2020-10-28112Heat3Checkers4WR1Sommaire du Match
23 - 2020-10-31129Eagles5Checkers3LSommaire du Match
24 - 2020-11-01130Checkers1Wolfpack6LR1Sommaire du Match
30 - 2020-11-07162Little Stars3Checkers6WSommaire du Match
32 - 2020-11-09176Checkers5Heat3WR1Sommaire du Match
34 - 2020-11-11182Checkers3Wolfpack7LSommaire du Match
35 - 2020-11-12193Eagles8Checkers4LR2Sommaire du Match
39 - 2020-11-16211IceHogs3Checkers4WSommaire du Match
42 - 2020-11-19228Checkers5Senators3WSommaire du Match
44 - 2020-11-21237Devils2Checkers3WSommaire du Match
46 - 2020-11-23252Checkers9Senators4WSommaire du Match
49 - 2020-11-26265Phantoms7Checkers6LSommaire du Match
52 - 2020-11-29280Checkers6Phantoms4WSommaire du Match
54 - 2020-12-01290Punishers3Checkers5WSommaire du Match
57 - 2020-12-04305Checkers7Condors3WSommaire du Match
59 - 2020-12-06317Checkers4Moose2WSommaire du Match
61 - 2020-12-08325Condors2Checkers3WSommaire du Match
64 - 2020-12-11345Reign3Checkers5WSommaire du Match
66 - 2020-12-13354Checkers3Devils2WSommaire du Match
68 - 2020-12-15365Checkers2IceHogs3LXSommaire du Match
70 - 2020-12-17375Bears3Checkers6WSommaire du Match
72 - 2020-12-19382Checkers2Monsters3LXXSommaire du Match
75 - 2020-12-22398Heat4Checkers2LR1Sommaire du Match
78 - 2020-12-25412Checkers5Punishers4WXXSommaire du Match
80 - 2020-12-27425Senators3Checkers5WSommaire du Match
82 - 2020-12-29435Checkers3Rampage6LR1Sommaire du Match
84 - 2020-12-31448Checkers6Little Stars4WSommaire du Match
86 - 2021-01-02457Checkers5Reign1WSommaire du Match
88 - 2021-01-04463Admirals2Checkers5WSommaire du Match
92 - 2021-01-08484Influenza7Checkers3LSommaire du Match
94 - 2021-01-10502Checkers5Griffins8LSommaire du Match
96 - 2021-01-12509Comets5Checkers6WXSommaire du Match
98 - 2021-01-14516Checkers5Bears6LSommaire du Match
102 - 2021-01-18535Moose6Checkers2LSommaire du Match
106 - 2021-01-22551Checkers6Heat2WR1Sommaire du Match
108 - 2021-01-24558Checkers8Penguins6WSommaire du Match
109 - 2021-01-25565Barracuda5Checkers2LSommaire du Match
112 - 2021-01-28586Sound Tigers5Checkers3LSommaire du Match
115 - 2021-01-31603Checkers2Influenza3LSommaire du Match
117 - 2021-02-02614Wolfpack1Checkers5WR1Sommaire du Match
119 - 2021-02-04621Checkers5Barracuda7LSommaire du Match
122 - 2021-02-07638Crunch2Checkers3WXSommaire du Match
125 - 2021-02-10657Checkers1Rocket5LSommaire du Match
127 - 2021-02-12664Eagles3Checkers5WR2Sommaire du Match
130 - 2021-02-15679Checkers4Thunderbirds6LSommaire du Match
132 - 2021-02-17691Rampage6Checkers7WR1Sommaire du Match
135 - 2021-02-20708Checkers2Punishers3LSommaire du Match
137 - 2021-02-22716Bears1Checkers3WSommaire du Match
139 - 2021-02-24725Checkers3Rampage7LR1Sommaire du Match
142 - 2021-02-27743Rocket3Checkers2LSommaire du Match
144 - 2021-03-01753Checkers5Sound Tigers2WSommaire du Match
148 - 2021-03-05769Rampage6Checkers5LR1Sommaire du Match
151 - 2021-03-08788Checkers6Wolfpack3WR1Sommaire du Match
153 - 2021-03-10796Little Stars4Checkers3LSommaire du Match
158 - 2021-03-15817Wolfpack4Checkers8WR1Sommaire du Match
160 - 2021-03-17829Checkers6Admirals2WSommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
162 - 2021-03-19841Monsters3Checkers4WSommaire du Match
164 - 2021-03-21848Checkers5Comets2WSommaire du Match
167 - 2021-03-24861Checkers5Crunch4WXXSommaire du Match
169 - 2021-03-26872Thunderbirds1Checkers5WSommaire du Match
171 - 2021-03-28886Checkers4Crunch3WSommaire du Match
173 - 2021-03-30891Checkers3Penguins4LXXSommaire du Match
174 - 2021-03-31897Checkers2Eagles9LR2Sommaire du Match
176 - 2021-04-02909Griffins5Checkers4LSommaire du Match
178 - 2021-04-04922Checkers4Eagles3WXXR2Sommaire du Match
181 - 2021-04-07933Little Stars5Checkers1LSommaire du Match
186 - 2021-04-12953Devils3Checkers4WXXSommaire du Match
190 - 2021-04-16973Penguins8Checkers6LSommaire du Match
191 - 2021-04-17980Checkers1Comets4LSommaire du Match
196 - 2021-04-221007Thunderbirds2Checkers1LXXSommaire du Match
199 - 2021-04-251021Penguins1Checkers4WSommaire du Match
201 - 2021-04-271030Checkers3Monsters2WSommaire du Match



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des Billets3020
Assistance76,35127,247
Assistance PCT95.44%68.12%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacitéPopularité de l'Équipe
0 2590 - 86.33% 74,431$2,977,242$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
2,736,503$ 2,655,000$ 2,580,000$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
12,951$ 2,370,345$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 0 14,659$ 0$




LigueDomicileVisiteur
Année GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff P G A TP SO EG GP1 GP2 GP3 GP4 SHF SH1 SP2 SP3 SP4 SHA SHB Pim Hit PPA PPG PP% PKA PK GA PK% PK GF W OF FO T OF FO OF FO% W DF FO T DF FO DF FO% W NT FO T NT FO NT FO% PZ DF PZ OF PZ NT PC DF PC OF PC NT