STOCKTON Flames

GP: 72 | W: 44 | L: 22 | OTL: 6 | P: 94
GF: 363 | GA: 198 | PP%: 19.07% | PK%: 86.14%
DG: Francis Pilote | Morale : 99 | Moyenne d'Équipe : 62
Prochain matchs #912 vs MANITOBA Moose
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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
1Filip Chytil0X100.006035756882828867686766606753518480690
2Robert Thomas (R)0X100.005735757172818370717465616853518480690
3Tobias Rieder0XX100.006735756570808064546760696265555780680
4Joel Eriksson Ek (R)0X100.007535726479788063766363686356528280680
5Denis Malgin0X100.006535756865806367686766656756526280660
6Lias Andersson0X100.006341696675649166706059596152518780650
7Jakob Forsbacka Karlsson0X100.005635756874646468706361586451507380630
8Dylan Sikura0X100.005235736966616668506763576552504880620
9Alexander Nylander0XX100.005135716976565669546363546451508780610
10Curtis McKenzie0X100.005689477081505070506363576354514180610
11Janne Kuokkanen0X100.005135706876545368506262536250507486600
12Victor Ejdsell0X100.006489676892505068505858505850504397600
13Filip Hronek (R)0X100.006335737168719070307069617052567180690
14Gustav Forsling0X100.006435756372776163306060706755515881640
15Joakim Ryan0X100.006741756469735764306355686554514780630
16Oliver Kylington0X100.005535756771656967306159596852506880620
17Tyler Wotherspoon0X100.005789666482495064304742505251506680550
Rayé
1Carter Camper0X100.005089677065505070706262506250503438580
2Max Gortz (R)0X100.004935796877474357305450515360507131560
3Grayson Downing0XX100.005089695673475056705252505250503727540
4Trevor Murphy0X100.005089566866505068305045515550504327540
MOYENNE D'ÉQUIPE100.00585170677463646651625958625351637262
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
1Nick Ellis100.00656277736774686666666350584380600
2Joni Ortio100.00576271696767636465625562626380580
Rayé
MOYENNE D'ÉQUIPE100.0061627471677166656664595660538059
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Willie Desjardins75767679818148CAN623150,000$


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
1Filip ChytilSTOCKTON Flames (CGY)C63455610191180671093488722912.93%13137721.873692514800071472164.20%137700021.4704000555
2Dylan SikuraSTOCKTON Flames (CGY)RW642858869412038512257022012.44%9128320.06371014136000005259.76%8200001.3400000272
3Filip HronekSTOCKTON Flames (CGY)D6315678278280615616845878.93%52150523.9051015561490002119200.00%000001.0900000163
4Tobias RiederSTOCKTON Flames (CGY)LW/RW5331498090455107742876521910.80%16139126.25336201160008844156.20%12100011.1503010667
5Robert ThomasSTOCKTON Flames (CGY)C4933467970140581112787820011.87%10118024.10268201010005834165.99%108200041.34120001113
6Curtis McKenzieSTOCKTON Flames (CGY)LW642644707245594492245617711.61%8111117.3632515830001522149.33%7500001.2600001421
7Joel Eriksson EkSTOCKTON Flames (CGY)C6440307065300122872826917714.18%12103216.1324613590002298073.00%71100021.3612000525
8Joakim RyanSTOCKTON Flames (CGY)D64174562675759430121377814.05%41131320.526511341340001106300.00%000000.9400001141
9Oliver KylingtonSTOCKTON Flames (CGY)D64754618624044408522748.24%32119718.701342372000083200.00%000001.0200000003
10Gustav ForslingSTOCKTON Flames (CGY)D641641576225576571424310911.27%61143222.384812501420002116200.00%000000.8000100114
11Alexander NylanderSTOCKTON Flames (CGY)LW/RW642032525310031441926115110.42%2119218.63134191340000181060.56%7100010.8700000112
12Denis MalginSTOCKTON Flames (CGY)C64232649411956592259761908.88%11100115.6502212260002542065.31%64000020.9800010101
13Lias AnderssonSTOCKTON Flames (CGY)C6420204040953226136309514.71%36129.560112310000122173.77%12200011.3100010020
14Jakob Forsbacka KarlssonSTOCKTON Flames (CGY)C647132022001087121479.86%03084.8212339000001077.27%2200001.3000000000
15Tyler WotherspoonSTOCKTON Flames (CGY)D4111314464715295196115.26%2166716.29000215011038000.00%000000.4200102000
16Victor EjdsellSTOCKTON Flames (CGY)C8707-2401983262621.87%159411.8000000000000071.57%10200011.4800000000
17Janne KuokkanenSTOCKTON Flames (CGY)C35336-1140111330112910.00%251634.68011050001190058.27%13900000.7300000002
Stats d'équipe Total ou en Moyenne952339597936964391459588602899783211911.69%3311686517.7234639730813660113196440765.87%4544000141.11211234383739
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
1Nick EllisSTOCKTON Flames (CGY)64441460.9061.69386961410911590220.66712640110
2Pavel FrancouzCALGARY Flames51381210.9101.673055213859430010.93315510131
Stats d'équipe Total ou en Moyenne115822670.9081.68692582719421020230.815271150241


Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
Nom du Joueur Nom de l'ÉquipePOS Âge Date de Naissance Nouveau Joueur Poids Taille Non-Échange Disponible pour Échange Ballotage Forcé Contrat StatusType Salaire Actuel Cap Salariale Cap Salariale Restant Exclus du Cap Salarial Link
Alexander NylanderSTOCKTON Flames (CGY)LW/RW211998-03-02No87 Kg185 CMNoNoNo6Avec RestrictionPro & Farm750,000$0$0$NoLien
Carter CamperSTOCKTON Flames (CGY)C311988-07-06No80 Kg175 CMNoNoNo6Sans RestrictionPro & Farm750,000$0$0$NoLien
Curtis McKenzieSTOCKTON Flames (CGY)LW281991-02-22No93 Kg188 CMNoNoNo6Sans RestrictionPro & Farm750,000$0$0$NoLien
Denis MalginSTOCKTON Flames (CGY)C221997-01-18No80 Kg175 CMNoNoNo6Avec RestrictionPro & Farm1,200,000$0$0$NoLien
Dylan SikuraSTOCKTON Flames (CGY)RW241995-06-01No75 Kg180 CMNoNoNo2Avec RestrictionPro & Farm750,000$0$0$NoLien
Filip ChytilSTOCKTON Flames (CGY)C191999-09-05No95 Kg188 CMNoNoNo2Avec RestrictionPro & Farm750,000$0$0$NoLien
Filip HronekSTOCKTON Flames (CGY)D211997-11-02Yes77 Kg183 CMNoNoNo3Avec RestrictionPro & Farm750,000$0$0$NoLien
Grayson DowningSTOCKTON Flames (CGY)C/RW271992-04-18No89 Kg183 CMNoNoNo2Avec RestrictionPro & Farm750,000$0$0$NoLien
Gustav ForslingSTOCKTON Flames (CGY)D231996-06-12No85 Kg183 CMNoNoNo6Avec RestrictionPro & Farm1,500,000$0$0$NoLien
Jakob Forsbacka KarlssonSTOCKTON Flames (CGY)C221996-10-31No84 Kg185 CMNoNoNo6Avec RestrictionPro & Farm750,000$0$0$NoLien
Janne KuokkanenSTOCKTON Flames (CGY)C211998-05-25No88 Kg185 CMNoNoNo2Avec RestrictionPro & Farm750,000$0$0$NoLien
Joakim RyanSTOCKTON Flames (CGY)D261993-06-17No84 Kg180 CMNoNoNo4Avec RestrictionPro & Farm750,000$0$0$NoLien
Joel Eriksson EkSTOCKTON Flames (CGY)C221997-01-29Yes95 Kg185 CMNoNoNo3Avec RestrictionPro & Farm750,000$0$0$NoLien
Joni OrtioSTOCKTON Flames (CGY)G281991-04-16No86 Kg185 CMNoNoNo6Sans RestrictionPro & Farm750,000$0$0$No
Lias AnderssonSTOCKTON Flames (CGY)C201998-10-13No86 Kg185 CMNoNoNo6Avec RestrictionPro & Farm900,000$0$0$NoLien
Max GortzSTOCKTON Flames (CGY)RW261993-01-28Yes95 Kg188 CMNoNoNo4Avec RestrictionPro & Farm750,000$0$0$No
Nick EllisSTOCKTON Flames (CGY)G251994-01-18No82 Kg185 CMNoNoNo6Avec RestrictionPro & Farm750,000$0$0$NoLien
Oliver KylingtonSTOCKTON Flames (CGY)D221997-05-19No83 Kg183 CMNoNoNo6Avec RestrictionPro & Farm750,000$0$0$NoLien
Robert ThomasSTOCKTON Flames (CGY)C201999-07-02Yes85 Kg183 CMNoNoNo3Avec RestrictionPro & Farm750,000$0$0$NoLien
Tobias RiederSTOCKTON Flames (CGY)LW/RW261993-01-10No85 Kg180 CMNoNoNo4Avec RestrictionPro & Farm900,000$0$0$NoLien
Trevor MurphySTOCKTON Flames (CGY)D241995-07-17No82 Kg178 CMNoNoNo6Avec RestrictionPro & Farm750,000$0$0$NoLien
Tyler WotherspoonSTOCKTON Flames (CGY)D261993-03-12No94 Kg188 CMNoNoNo1Avec RestrictionPro & Farm800,000$0$0$NoLien
Victor EjdsellSTOCKTON Flames (CGY)C241995-06-06No97 Kg196 CMNoNoNo2Avec RestrictionPro & Farm750,000$0$0$NoLien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2323.8386 Kg183 CM4.26817,391$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Tobias RiederFilip ChytilDylan Sikura31122
2Curtis McKenzieRobert ThomasAlexander Nylander26122
3Tobias RiederJoel Eriksson EkDylan Sikura23122
4Tobias RiederDenis MalginDylan Sikura20122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Filip HronekGustav Forsling31122
2Joakim RyanOliver Kylington26122
3Tyler WotherspoonFilip Hronek23122
4Gustav ForslingJoakim Ryan20122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Tobias RiederFilip ChytilDylan Sikura55122
2Curtis McKenzieRobert ThomasAlexander Nylander45122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Filip HronekGustav Forsling55122
2Joakim RyanOliver Kylington45122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Filip ChytilTobias Rieder55122
2Robert ThomasCurtis McKenzie45122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Filip HronekGustav Forsling55122
2Joakim RyanOliver Kylington45122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Filip Chytil55122Filip HronekGustav Forsling55122
2Robert Thomas45122Joakim RyanOliver Kylington45122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Filip ChytilTobias Rieder55122
2Robert ThomasCurtis McKenzie45122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Filip HronekGustav Forsling55122
2Joakim RyanOliver Kylington45122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Tobias RiederFilip ChytilDylan SikuraFilip HronekGustav Forsling
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Tobias RiederFilip ChytilDylan SikuraFilip HronekGustav Forsling
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Denis Malgin, Lias Andersson, Jakob Forsbacka KarlssonDenis Malgin, Lias AnderssonDenis Malgin
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Joakim Ryan, Oliver Kylington, Tyler WotherspoonJoakim RyanJoakim Ryan, Oliver Kylington
Tirs de Pénalité
Filip Chytil, Robert Thomas, Tobias Rieder, Joel Eriksson Ek, Denis Malgin
Gardien
#1 : Nick Ellis, #2 : Joni Ortio
Lignes d'Attaque Perso. en Prol.
Filip Chytil, Robert Thomas, Tobias Rieder, Joel Eriksson Ek, Denis Malgin, Lias Andersson, Lias Andersson, Jakob Forsbacka Karlsson, Dylan Sikura, Alexander Nylander, Curtis McKenzie
Lignes de Défense Perso. en Prol.
Filip Hronek, Gustav Forsling, Joakim Ryan, Oliver Kylington, Tyler Wotherspoon


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
1BELLEVILLE Senators431000001578220000009272110000065160.7501528430017810973423610041022106528571718726116.67%9366.67%01469225865.06%891162954.70%748117963.44%222317561355389773427
2BRIDGEPORT Sound Tigers3110010047-31000010012-12110000035-230.5004812001781097349110041022106528901618511400.00%60100.00%01469225865.06%891162954.70%748117963.44%222317561355389773427
3BROOKLYN Wolfpack220000002011911000000918110000001101141.0002038580117810973414210041022106528121629000.00%30100.00%01469225865.06%891162954.70%748117963.44%222317561355389773427
4CHICAGO Wolves220000001921711000000130131100000062441.00019355401178109734127100410221065281962254125.00%10100.00%01469225865.06%891162954.70%748117963.44%222317561355389773427
5CLEVELAND Monsters22000000241231100000013112110000001101141.00024467001178109734150100410221065281852242150.00%10100.00%01469225865.06%891162954.70%748117963.44%222317561355389773427
6COLORADO Eagles2110000067-11010000035-21100000032120.500611171017810973458100410221065284917394116212.50%9188.89%01469225865.06%891162954.70%748117963.44%222317561355389773427
7CORNWALL Aces44000000391382200000016115220000002302381.00039751140317810973430110041022106528145447100.00%20100.00%01469225865.06%891162954.70%748117963.44%222317561355389773427
8HERSEY Bears21000100550110000002111000010034-130.750591400178109734441004102210652844128326233.33%4175.00%01469225865.06%891162954.70%748117963.44%222317561355389773427
9HOLLYWOOD Oscar33000000363331100000013112220000002322161.0003669105001781097342151004102210652815664811100.00%30100.00%01469225865.06%891162954.70%748117963.44%222317561355389773427
10IOWA Wild411000111117-621100000612-62000001155050.62511162700178109734152100410221065281735133749111.11%13284.62%01469225865.06%891162954.70%748117963.44%222317561355389773427
11LAVAL Rockets2010100034-1100010001011010000024-220.500358011781097344910041022106528632322308112.50%11281.82%01469225865.06%891162954.70%748117963.44%222317561355389773427
12LEHIGH VALLEY Phantoms430000012181321000001532220000001651170.87521406100178109734109100410221065287830207017317.65%9188.89%01469225865.06%891162954.70%748117963.44%222317561355389773427
13MANITOBA Moose42200000923-1421100000510-521100000413-940.5009162500178109734641004102210652818859144214428.57%7185.71%01469225865.06%891162954.70%748117963.44%222317561355389773427
14MILWAUKEE Admirals211000006421010000012-11100000052320.50061016001781097344310041022106528531322253133.33%10190.00%01469225865.06%891162954.70%748117963.44%222317561355389773427
15MONT-LAURIER Sommet31200000752211000006331010000012-120.3337132001178109734117100410221065284519144513323.08%7185.71%01469225865.06%891162954.70%748117963.44%222317561355389773427
16PROVIDENCE Bruins2020000047-31010000023-11010000024-200.0004711101781097345510041022106528632060511119.09%11281.82%01469225865.06%891162954.70%748117963.44%222317561355389773427
17PV Sharapovas31200000628-2210100000211-921100000417-1320.33369150017810973436100410221065282045982315320.00%4175.00%01469225865.06%891162954.70%748117963.44%222317561355389773427
18ROCKFORD IceHogs2110000057-2110000003211010000025-320.5005712001781097345710041022106528592028327114.29%12283.33%01469225865.06%891162954.70%748117963.44%222317561355389773427
19SAN DIEGO Gulls42200000171432110000013762110000047-340.500173148021781097342421004102210652816531682000.00%30100.00%01469225865.06%891162954.70%748117963.44%222317561355389773427
20SYRACUSE Crunch42100100207132010010057-2220000001501550.6252037570217810973417610041022106528782410599111.11%50100.00%01469225865.06%891162954.70%748117963.44%222317561355389773427
21TORONTO Marlies4210000124195210000011551021100000914-550.625244569001781097341801004102210652814732185910440.00%9188.89%01469225865.06%891162954.70%748117963.44%222317561355389773427
22TUSCON Roadrunners21001000752100010003211100000043141.00071421001781097345010041022106528521114356116.67%6183.33%01469225865.06%891162954.70%748117963.44%222317561355389773427
Total724122023133631981653418100220217386873823120011119011278940.6533636731036214178109734310610041022106528181651242511331943719.07%1662386.14%01469225865.06%891162954.70%748117963.44%222317561355389773427
24UTICA Comets2020000039-61010000024-21010000015-400.00036900178109734551004102210652853191229700.00%6266.67%01469225865.06%891162954.70%748117963.44%222317561355389773427
25VICTORIAVILLE Tigres21100000853000000000002110000085320.500813210017810973445100410221065284510374411327.27%13192.31%01469225865.06%891162954.70%748117963.44%222317561355389773427
26WILKIES-BARRIE Penguins44000000442422200000025124220000001911881.000448512902178109734312100410221065283264644250.00%20100.00%01469225865.06%891162954.70%748117963.44%222317561355389773427
_Since Last GM Reset724122023133631981653418100220217386873823120011119011278940.6533636731036214178109734310610041022106528181651242511331943719.07%1662386.14%01469225865.06%891162954.70%748117963.44%222317561355389773427
_Vs Conference432711001132401251152012500102107565123156000111336964600.6982404466860817810973419431004102210652810763181866471102623.64%831186.75%01469225865.06%891162954.70%748117963.44%222317561355389773427
_Vs Division23116000121117338115300001502921126300011614417260.56511120631716178109734103310041022106528626180140341601118.33%51982.35%01469225865.06%891162954.70%748117963.44%222317561355389773427

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
7294W23636731036310618165124251133214
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
7241222313363198
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
341810220217386
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
3823120111190112
Derniers 10 Matchs
WLOTWOTL SOWSOL
630001
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
1943719.07%1662386.14%0
Tirs en 1e PériodeTirs en 2e PériodeTirs en 3e PériodeTirs en 4e PériodeButs en 1e PériodeButs en 2e PériodeButs en 3e PériodeButs en 4e Période
10041022106528178109734
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
1469225865.06%891162954.70%748117963.44%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
222317561355389773427


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 - 2019-07-304MANITOBA Moose8STOCKTON Flames1LSommaire du Match
2 - 2019-07-3125IOWA Wild11STOCKTON Flames3LSommaire du Match
3 - 2019-08-0135STOCKTON Flames0PV Sharapovas15LSommaire du Match
4 - 2019-08-0251PV Sharapovas11STOCKTON Flames2LSommaire du Match
6 - 2019-08-0461STOCKTON Flames1SAN DIEGO Gulls7LSommaire du Match
8 - 2019-08-0678STOCKTON Flames0MANITOBA Moose12LSommaire du Match
9 - 2019-08-0784SAN DIEGO Gulls7STOCKTON Flames2LSommaire du Match
10 - 2019-08-08103STOCKTON Flames6TORONTO Marlies13LSommaire du Match
11 - 2019-08-09114LEHIGH VALLEY Phantoms2STOCKTON Flames1LXXSommaire du Match
12 - 2019-08-10124STOCKTON Flames11SYRACUSE Crunch0WSommaire du Match
14 - 2019-08-12134TORONTO Marlies1STOCKTON Flames12WSommaire du Match
16 - 2019-08-14153STOCKTON Flames6LEHIGH VALLEY Phantoms1WSommaire du Match
17 - 2019-08-15164STOCKTON Flames1MONT-LAURIER Sommet2LSommaire du Match
18 - 2019-08-16176CORNWALL Aces0STOCKTON Flames9WSommaire du Match
20 - 2019-08-18189STOCKTON Flames11HOLLYWOOD Oscar1WSommaire du Match
21 - 2019-08-19199BELLEVILLE Senators1STOCKTON Flames4WSommaire du Match
23 - 2019-08-21218MONT-LAURIER Sommet0STOCKTON Flames4WSommaire du Match
24 - 2019-08-22230STOCKTON Flames3SAN DIEGO Gulls0WSommaire du Match
25 - 2019-08-23242STOCKTON Flames1BELLEVILLE Senators3LSommaire du Match
26 - 2019-08-24248STOCKTON Flames12WILKIES-BARRIE Penguins0WSommaire du Match
27 - 2019-08-25262BRIDGEPORT Sound Tigers2STOCKTON Flames1LXSommaire du Match
28 - 2019-08-26278STOCKTON Flames4MANITOBA Moose1WSommaire du Match
29 - 2019-08-27287CHICAGO Wolves0STOCKTON Flames13WSommaire du Match
30 - 2019-08-28306BROOKLYN Wolfpack1STOCKTON Flames9WSommaire du Match
31 - 2019-08-29317STOCKTON Flames5MILWAUKEE Admirals2WSommaire du Match
32 - 2019-08-30330COLORADO Eagles5STOCKTON Flames3LSommaire du Match
34 - 2019-09-01341STOCKTON Flames2LAVAL Rockets4LSommaire du Match
35 - 2019-09-02355STOCKTON Flames10LEHIGH VALLEY Phantoms4WSommaire du Match
36 - 2019-09-03364TORONTO Marlies4STOCKTON Flames3LXXSommaire du Match
37 - 2019-09-04385LEHIGH VALLEY Phantoms1STOCKTON Flames4WSommaire du Match
39 - 2019-09-06400STOCKTON Flames3BRIDGEPORT Sound Tigers2WSommaire du Match
40 - 2019-09-07405MONT-LAURIER Sommet3STOCKTON Flames2LSommaire du Match
42 - 2019-09-09422STOCKTON Flames3COLORADO Eagles2WSommaire du Match
43 - 2019-09-10437CORNWALL Aces1STOCKTON Flames7WSommaire du Match
44 - 2019-09-11444STOCKTON Flames6VICTORIAVILLE Tigres2WR3Sommaire du Match
46 - 2019-09-13463IOWA Wild1STOCKTON Flames3WSommaire du Match
47 - 2019-09-14473STOCKTON Flames1UTICA Comets5LSommaire du Match
48 - 2019-09-15489LAVAL Rockets0STOCKTON Flames1WXSommaire du Match
49 - 2019-09-16498STOCKTON Flames11BROOKLYN Wolfpack0WSommaire du Match
50 - 2019-09-17515BELLEVILLE Senators1STOCKTON Flames5WSommaire du Match
51 - 2019-09-18526MANITOBA Moose2STOCKTON Flames4WSommaire du Match
53 - 2019-09-20541STOCKTON Flames0BRIDGEPORT Sound Tigers3LSommaire du Match
54 - 2019-09-21553MILWAUKEE Admirals2STOCKTON Flames1LSommaire du Match
56 - 2019-09-23567STOCKTON Flames2PROVIDENCE Bruins4LSommaire du Match
58 - 2019-09-25582SAN DIEGO Gulls0STOCKTON Flames11WSommaire du Match
59 - 2019-09-26592STOCKTON Flames12HOLLYWOOD Oscar1WSommaire du Match
60 - 2019-09-27601STOCKTON Flames6CHICAGO Wolves2WSommaire du Match
61 - 2019-09-28609STOCKTON Flames3TORONTO Marlies1WSommaire du Match
64 - 2019-10-01621HOLLYWOOD Oscar1STOCKTON Flames13WSommaire du Match
65 - 2019-10-02634STOCKTON Flames3HERSEY Bears4LXSommaire du Match
67 - 2019-10-04650UTICA Comets4STOCKTON Flames2LSommaire du Match
69 - 2019-10-06670WILKIES-BARRIE Penguins0STOCKTON Flames14WSommaire du Match
70 - 2019-10-07678STOCKTON Flames4SYRACUSE Crunch0WSommaire du Match
71 - 2019-10-08690STOCKTON Flames4TUSCON Roadrunners3WSommaire du Match
73 - 2019-10-10700CLEVELAND Monsters1STOCKTON Flames13WSommaire du Match
74 - 2019-10-11716STOCKTON Flames11CLEVELAND Monsters0WSommaire du Match
75 - 2019-10-12726SYRACUSE Crunch5STOCKTON Flames4LXSommaire du Match
77 - 2019-10-14746ROCKFORD IceHogs2STOCKTON Flames3WSommaire du Match
78 - 2019-10-15758STOCKTON Flames2ROCKFORD IceHogs5LSommaire du Match
79 - 2019-10-16768STOCKTON Flames7WILKIES-BARRIE Penguins1WSommaire du Match
80 - 2019-10-17778HERSEY Bears1STOCKTON Flames2WSommaire du Match
82 - 2019-10-19794WILKIES-BARRIE Penguins1STOCKTON Flames11WSommaire du Match
83 - 2019-10-20810STOCKTON Flames4PV Sharapovas2WSommaire du Match
84 - 2019-10-21819STOCKTON Flames3IOWA Wild4LXXSommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
85 - 2019-10-22829TUSCON Roadrunners2STOCKTON Flames3WXSommaire du Match
86 - 2019-10-23846PROVIDENCE Bruins3STOCKTON Flames2LSommaire du Match
87 - 2019-10-24851STOCKTON Flames2IOWA Wild1WXXSommaire du Match
89 - 2019-10-26869STOCKTON Flames13CORNWALL Aces0WSommaire du Match
90 - 2019-10-27880SYRACUSE Crunch2STOCKTON Flames1LSommaire du Match
91 - 2019-10-28889STOCKTON Flames2VICTORIAVILLE Tigres3LR3Sommaire du Match
92 - 2019-10-29894STOCKTON Flames10CORNWALL Aces0WSommaire du Match
93 - 2019-10-30905STOCKTON Flames5BELLEVILLE Senators2WSommaire du Match
94 - 2019-10-31912MANITOBA Moose-STOCKTON Flames-
96 - 2019-11-02936HOLLYWOOD Oscar-STOCKTON Flames-
98 - 2019-11-04946STOCKTON Flames-MONT-LAURIER Sommet-
100 - 2019-11-06961PV Sharapovas-STOCKTON Flames-
103 - 2019-11-09987VICTORIAVILLE Tigres-STOCKTON Flames-
106 - 2019-11-121013VICTORIAVILLE Tigres-STOCKTON Flames-



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité de l'Aréna20001000
Prix des Billets3515
Assistance00
Assistance PCT0.00%0.00%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
5 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
1,874,113$ 1,880,000$ 1,880,000$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 1,743,730$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 14 18,972$ 265,608$




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
32724122023133631981653418100220217386873823120011119011278943636731036214178109734310610041022106528181651242511331943719.07%1662386.14%01469225865.06%891162954.70%748117963.44%222317561355389773427
Total Saison Régulière724122023133631981653418100220217386873823120011119011278943636731036214178109734310610041022106528181651242511331943719.07%1662386.14%01469225865.06%891162954.70%748117963.44%222317561355389773427