Stars

GP: 82 | W: 36 | L: 40 | OTL: 6 | P: 78
GF: 284 | GA: 322 | PP%: 23.14% | PK%: 76.37%
GM : Julien Desrosiers | Morale : 50 | Team Overall : 47
Your browser screen resolution is too small for this page. Some information are hidden to keep the page readable.

Filter Tips
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
# Player Name C L R D CON CK FG DI SK ST EN DU PH FO PA SC DF PS EX LD PO MO OV TA SPAgeContractSalary Average
1Alexander VolkovXX100.00767182647180865950595767555555050610223864,167$
2Taylor RaddyshXX100.00838089638078836075536268594444050610212742,500$
3Michael McCarronXX100.00798855658861625671526066594949050590242620,000$
4Liam Hawel (R)X100.00565274697175946165595153545454050590204525,000$
5Andrew PoturalskiX100.00746886596968635468575166485555050570251792,000$
6Hudson ElynuikX100.00747571637561655063474761454444050540212700,000$
7Lucas LessioX100.00473584637343294035364362484036050470261600,000$
8Jesse Gabrielle (R)X100.00364040407135353640363640383230050380222742,500$
9Matt Schmalz (R)XX100.00323737377731313237323237343230050360231525,000$
10Andrew MacDonaldX100.005243846367676547355243764761540505903322,500,000$
11Martin Fehervary (R)X100.00757283727266714725384160394444050570194805,835$
12Louie BelpedioX100.00707065646972834825404060394444050570232925,000$
13Justin FalkX100.00605076597660433835354169475751050540302800,000$
14Connor Hall (R)X100.00394343436337373943393943413230050410212700,000$
15Kenney Morrison (R)X100.00394545456636363945393945423230050410271825,000$
16Sam Ruopp (R)X100.00323737376431313237323237343230050360231525,000$
17Stephen Desrocher (R)X100.00323737376931313237323237343230050360231525,000$
Scratches
1Chris Leblanc (R)X100.00313737376829293137313137333230050350261560,000$
2Henrik SedinX100.001920202020191919201919202020200502103915,347,152$
TEAM AVERAGE100.0053536053695252434441425343424005048
Filter Tips
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
# Goalie Name CON SK DU EN SZ AG RB SC HS RT PH PS EX LD PO MO OV TA SP
1Scott Wedgewood100.0053678176515551585352305454050570
2Mark Visentin100.0044454272403537353333333532050410
Scratches
1Evan Smith (R)100.0033373568333232323232313230050370
TEAM AVERAGE100.004350537241414042393931403905045
Coaches Name PH DF OF PD EX LD PO CNT Age Contract Salary


Filter Tips
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
# Player Name Team NamePOSGP 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 McCarronStars (Dal)C/RW824040801479531816536212124411.05%30144717.656612481290001386356.17%16200001.11120104610
2Liam HawelStars (Dal)C822652781710023237270721999.63%15145717.7731013221221015522254.10%197400011.0703000355
3Taylor RaddyshStars (Dal)C/RW56373976936101351103237923111.46%28119521.3491221501330005825159.38%25600101.2715101573
4Owen TippettDallasLW/RW4538377518280961282726117813.97%15105523.466101637102000111254347.71%41500021.42050001023
5Greg McKeggDallasC/LW511653691318044162225641587.11%28114022.37410142711400071284050.43%138000111.2126000432
6Alexander VolkovStars (Dal)LW/RW4526356128240122892287419611.40%1494721.067111857127000014349.30%7100001.2902000673
7Gustav ForslingDallasD60845531742018583127341076.30%135137322.9041216471540003142020.00%000100.7700000125
8Andrew MacDonaldStars (Dal)D69113445-61004097108377010.19%114122717.7857123998011289210.00%000000.7300000021
9Andrew PoturalskiStars (Dal)C82202343-1539571183226721378.85%25114613.981018230000191054.40%141000000.7500000120
10Hudson ElynuikStars (Dal)C82201939-315820160154262621907.63%33125915.3600000000001052.24%33500000.6200112220
11Martin FehervaryStars (Dal)D8262733-5560224559835566.12%78146117.83055271150000119100.00%000000.4500000013
12Jake BeanDallasD23524291116055235210269.62%4352923.043472760000358200.00%000101.0900000042
13Lucas LessioStars (Dal)LW8282028-1001549840738.16%11122514.9513412930000381028.10%12100000.4600000020
14Louie BelpedioStars (Dal)D8232023-19460193536921504.35%61104912.80022431000142000.00%000000.4400000002
15Justin FalkStars (Dal)D8231821-1638084546026585.00%8095411.6301113000031010.00%000000.4400000001
16Kenney MorrisonStars (Dal)D82369716072121741017.65%375396.5800012000024000.00%000000.3300000000
17Connor HallStars (Dal)D820882180581310490.00%405636.8700000000024000.00%000000.2800000000
18Jesse GabrielleStars (Dal)LW69011-13201367220.00%387912.74000040000240030.30%6600000.0200000000
Team Total or Average1238270501771305364018941678281481819949.59%7901945415.7149931424071319112381043331652.28%619000440.79423223364540
Filter Tips
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
# Goalie Name Team NameGP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA ST BG S1 S2 S3
1Scott WedgewoodStars (Dal)82363850.9113.7546046028832220100.63219820812
2Mark VisentinStars (Dal)80210.9064.9934920293090000.0002082000
Team Total or Average90364060.9103.8449548031735310100.571218282812


Filter Tips
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
Player Name Team NamePOS Age Birthday Rookie Weight Height No Trade Available For Trade Force Waivers Contract Type Current Salary Salary RemainingSalary Cap Salary Cap Remaining Exclude from Salary Cap Salary Year 2Salary Year 3Salary Year 4Salary Year 5Salary Year 6Salary Year 7Salary Year 8Salary Year 9Salary Year 10Link
Alexander VolkovStars (Dal)LW/RW221997-08-02No191 Lbs6 ft1NoNoNo3Pro & Farm864,167$86,417$0$No864,167$864,167$Link
Andrew MacDonaldStars (Dal)D331986-09-07No204 Lbs6 ft1NoNoNo2Pro & Farm2,500,000$250,000$0$No2,500,000$Link
Andrew PoturalskiStars (Dal)C251994-01-14No190 Lbs5 ft11NoNoNo1Pro & Farm792,000$79,200$0$NoLink
Chris LeblancStars (Dal)RW261993-09-12Yes195 Lbs6 ft3NoNoNo1Pro & Farm560,000$56,000$0$NoLink
Connor HallStars (Dal)D211998-02-21Yes192 Lbs6 ft4NoNoNo2Pro & Farm700,000$70,000$0$No700,000$Link
Evan SmithStars (Dal)G221997-02-27Yes181 Lbs6 ft6NoNoNo1Pro & Farm525,000$52,500$0$NoLink
Henrik Sedin (1 Way Contract)Stars (Dal)C391980-09-26No183 Lbs6 ft2NoNoNo1Pro & Farm3,000,000$5,347,152$0$NoLink
Hudson ElynuikStars (Dal)C211997-10-12No194 Lbs6 ft5NoNoNo2Pro & Farm700,000$70,000$0$No700,000$Link
Jesse GabrielleStars (Dal)LW221997-06-17Yes205 Lbs6 ft0NoNoNo2Pro & Farm742,500$74,250$0$No742,500$Link
Justin FalkStars (Dal)D301988-10-11No223 Lbs6 ft5NoNoNo2Pro & Farm800,000$80,000$0$No800,000$Link
Kenney MorrisonStars (Dal)D271992-02-13Yes200 Lbs6 ft2NoNoNo1Pro & Farm825,000$82,500$0$NoLink
Liam HawelStars (Dal)C201999-04-18Yes183 Lbs6 ft5NoNoNo4Pro & Farm525,000$52,500$0$No525,000$525,000$525,000$Link
Louie BelpedioStars (Dal)D231996-05-14No193 Lbs5 ft11NoNoNo2Pro & Farm925,000$92,500$0$No925,000$Link
Lucas LessioStars (Dal)LW261993-01-23No212 Lbs6 ft1NoNoNo1Pro & Farm600,000$60,000$0$NoLink
Mark VisentinStars (Dal)G271992-08-07No195 Lbs6 ft2NoNoNo1Pro & Farm675,000$67,500$0$NoLink
Martin FehervaryStars (Dal)D191999-10-06Yes194 Lbs6 ft2NoNoNo4Pro & Farm805,835$80,584$0$No805,835$805,835$805,835$Link
Matt SchmalzStars (Dal)C/RW231996-03-21Yes217 Lbs6 ft6NoNoNo1Pro & Farm525,000$52,500$0$NoLink
Michael McCarronStars (Dal)C/RW241995-03-06No231 Lbs6 ft6NoNoNo2Pro & Farm620,000$62,000$0$No620,000$Link
Sam RuoppStars (Dal)D231996-06-03Yes195 Lbs6 ft4NoNoNo1Pro & Farm525,000$52,500$0$NoLink
Scott WedgewoodStars (Dal)G271992-08-14No195 Lbs6 ft2NoNoNo4Pro & Farm700,000$70,000$0$No700,000$700,000$700,000$Link
Stephen DesrocherStars (Dal)D231996-01-26Yes206 Lbs6 ft4NoNoNo1Pro & Farm525,000$52,500$0$NoLink
Taylor RaddyshStars (Dal)C/RW211998-02-18No216 Lbs6 ft3NoNoNo2Pro & Farm742,500$74,250$0$No742,500$Link
Total PlayersAverage AgeAverage WeightAverage HeightAverage ContractAverage Year 1 Salary
2224.73200 Lbs6 ft31.86871,682$



5 vs 5 Forward
Line #Left WingCenterRight WingTime %PHYDFOF
140122
2Lucas LessioLiam HawelMichael McCarron30122
3Jesse GabrielleAndrew PoturalskiHudson Elynuik20122
4Hudson Elynuik10122
5 vs 5 Defense
Line #DefenseDefenseTime %PHYDFOF
140122
2Andrew MacDonaldMartin Fehervary30122
3Louie BelpedioJustin Falk20122
4Kenney MorrisonConnor Hall10122
Power Play Forward
Line #Left WingCenterRight WingTime %PHYDFOF
160122
2Lucas LessioLiam HawelMichael McCarron40122
Power Play Defense
Line #DefenseDefenseTime %PHYDFOF
160122
2Andrew MacDonaldMartin Fehervary40122
Penalty Kill 4 Players Forward
Line #CenterWingTime %PHYDFOF
160122
2Liam Hawel40122
Penalty Kill 4 Players Defense
Line #DefenseDefenseTime %PHYDFOF
160122
2Andrew MacDonaldMartin Fehervary40122
Penalty Kill 3 Players
Line #WingTime %PHYDFOFDefenseDefenseTime %PHYDFOF
16012260122
240122Andrew MacDonaldMartin Fehervary40122
4 vs 4 Forward
Line #CenterWingTime %PHYDFOF
160122
2Liam Hawel40122
4 vs 4 Defense
Line #DefenseDefenseTime %PHYDFOF
160122
2Andrew MacDonaldMartin Fehervary40122
Last Minutes Offensive
Left WingCenterRight WingDefenseDefense
Last Minutes Defensive
Left WingCenterRight WingDefenseDefense
Extra Forwards
Normal PowerPlayPenalty Kill
Andrew Poturalski, Jesse Gabrielle, Michael McCarronAndrew Poturalski, Jesse GabrielleMichael McCarron
Extra Defensemen
Normal PowerPlayPenalty Kill
Louie Belpedio, Justin Falk, Kenney MorrisonLouie BelpedioJustin Falk, Kenney Morrison
Penalty Shots
, , , Liam Hawel, Michael McCarron
Goalie
#1 : Scott Wedgewood, #2 : Mark Visentin


Filter Tips
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
OverallHomeVisitor
# VS Team 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
1Admirals31200000911-2110000004312020000058-320.33391827001009982694100310441009531372720731119.09%7271.43%01435290249.45%1507323146.64%727144950.17%1855127120476041056514
2Baby Hawks412000011620-420100001710-321100000910-130.37516304600100998261401003104410095318056289416425.00%14471.43%01435290249.45%1507323146.64%727144950.17%1855127120476041056514
3Bears22000000963110000004311100000053241.0009172600100998266810031044100953782332646350.00%11463.64%01435290249.45%1507323146.64%727144950.17%1855127120476041056514
4Bruins21100000651110000003121010000034-120.5006111700100998267210031044100953551410588225.00%5260.00%01435290249.45%1507323146.64%727144950.17%1855127120476041056514
5Cabaret Lady Mary Ann220000001367110000005411100000082641.00013253800100998261311003104410095379240483133.33%000.00%01435290249.45%1507323146.64%727144950.17%1855127120476041056514
6Caroline21100000862110000006331010000023-120.5008152300100998269610031044100953812215515120.00%4250.00%01435290249.45%1507323146.64%727144950.17%1855127120476041056514
7Chiefs522001001316-32110000066031100100710-350.500132437001009982615510031044100953228753512511218.18%11281.82%01435290249.45%1507323146.64%727144950.17%1855127120476041056514
8Chill413000001122-1120200000412-821100000710-320.250112132001009982614110031044100953225512710514321.43%10370.00%01435290249.45%1507323146.64%727144950.17%1855127120476041056514
9Comets321000001112-12110000079-21100000043140.6671120310010099826107100310441009531174316556116.67%8187.50%01435290249.45%1507323146.64%727144950.17%1855127120476041056514
10Cougars2010000179-21000000145-11010000034-110.25071421001009982664100310441009539428195810220.00%7271.43%01435290249.45%1507323146.64%727144950.17%1855127120476041056514
11Crunch21100000810-21010000036-31100000054120.500813210010099826981003104410095394191475500.00%6266.67%01435290249.45%1507323146.64%727144950.17%1855127120476041056514
12Heat330000001486220000008531100000063361.0001426400010099826171100310441009531073324835120.00%12191.67%01435290249.45%1507323146.64%727144950.17%1855127120476041056514
13Jayhawks3120000089-11010000023-12110000066020.333816240010099826106100310441009531383518765120.00%7185.71%01435290249.45%1507323146.64%727144950.17%1855127120476041056514
14Las Vegas311000011112-1210000017701010000045-130.5001120310010099826128100310441009539531149310330.00%6350.00%01435290249.45%1507323146.64%727144950.17%1855127120476041056514
15Manchots210000017701000000134-11100000043130.7507132000100998267410031044100953842620654250.00%10280.00%01435290249.45%1507323146.64%727144950.17%1855127120476041056514
16Marlies2020000037-41010000023-11010000014-300.0003470010099826541003104410095371218493133.33%40100.00%01435290249.45%1507323146.64%727144950.17%1855127120476041056514
17Minnesota43100000241212220000001441021100000108260.7502443670010099826263100310441009531682622997228.57%11190.91%01435290249.45%1507323146.64%727144950.17%1855127120476041056514
18Monarchs30300000820-121010000029-720200000611-500.00081321001009982689100310441009531845417792150.00%6266.67%11435290249.45%1507323146.64%727144950.17%1855127120476041056514
19Monsters211000009811010000046-21100000052320.5009182700100998266510031044100953922225575240.00%10280.00%01435290249.45%1507323146.64%727144950.17%1855127120476041056514
20Monsters41201000151502010100089-12110000076140.50015243900100998261381003104410095317649389014642.86%18666.67%01435290249.45%1507323146.64%727144950.17%1855127120476041056514
21Oceanics513000101626-1030300000821-132100001085340.400162642001009982613610031044100953233643510817211.76%12191.67%01435290249.45%1507323146.64%727144950.17%1855127120476041056514
22Oil Kings3210000012102211000007701100000053240.66712223400100998261131003104410095313141187411218.18%80100.00%01435290249.45%1507323146.64%727144950.17%1855127120476041056514
23Phantoms20100001610-41010000014-31000000156-110.250612180010099826721003104410095395271266600.00%60100.00%01435290249.45%1507323146.64%727144950.17%1855127120476041056514
24Rocket2110000056-11010000024-21100000032120.5005101500100998265910031044100953832912555240.00%6183.33%01435290249.45%1507323146.64%727144950.17%1855127120476041056514
25Senators2010100079-2100010004311010000036-320.5007142100100998267210031044100953992010544125.00%5180.00%01435290249.45%1507323146.64%727144950.17%1855127120476041056514
26Sharks30300000517-121010000024-220200000313-1000.0005914001009982696100310441009531144316501119.09%8362.50%01435290249.45%1507323146.64%727144950.17%1855127120476041056514
27Sound Tigers211000008711010000024-21100000063320.5008142200100998266610031044100953892020484125.00%10370.00%01435290249.45%1507323146.64%727144950.17%1855127120476041056514
28Spiders21100000440110000002111010000023-120.500471100100998266510031044100953601664013323.08%30100.00%01435290249.45%1507323146.64%727144950.17%1855127120476041056514
29Thunder2020000027-51010000013-21010000014-300.0002350010099826741003104410095357231443300.00%6266.67%01435290249.45%1507323146.64%727144950.17%1855127120476041056514
Total82334002115284322-3841152002004136165-2941182000111148157-9780.4762845188020010099826308810031044100953353198856220722295323.14%2375676.37%11435290249.45%1507323146.64%727144950.17%1855127120476041056514
30Wolf Pack22000000954110000004221100000053241.0009162500100998268110031044100953872617375240.00%6350.00%01435290249.45%1507323146.64%727144950.17%1855127120476041056514
_Since Last GM Reset82334002115284322-3841152002004136165-2941182000111148157-9780.4762845188020010099826308810031044100953353198856220722295323.14%2375676.37%11435290249.45%1507323146.64%727144950.17%1855127120476041056514
_Vs Conference42211601103165151142210801003868242011800100796910480.5711653024670010099826176910031044100953177151127310761132824.78%1182677.97%01435290249.45%1507323146.64%727144950.17%1855127120476041056514
_Vs Division26550100095111-161314010004762-151341000004849-1120.231951682630010099826973100310441009531210321185621791924.05%761777.63%01435290249.45%1507323146.64%727144950.17%1855127120476041056514

Total For Players
Games PlayedPointsStreakGoalsAssistsPointsShots ForShots AgainstShots BlockedPenalty MinutesHitsEmpty Net GoalsShutouts
8278L1028451880230883531988562207200
All Games
GPWLOTWOTL SOWSOLGFGA
8233402115284322
Home Games
GPWLOTWOTL SOWSOLGFGA
4115202004136165
Visitor Games
GPWLOTWOTL SOWSOLGFGA
4118200111148157
Last 10 Games
WLOTWOTL SOWSOL
0100000
Power Play AttempsPower Play GoalsPower Play %Penalty Kill AttempsPenalty Kill Goals AgainstPenalty Kill %Penalty Kill Goals For
2295323.14%2375676.37%1
Shots 1 PeriodShots 2 PeriodShots 3 PeriodShots 4+ PeriodGoals 1 PeriodGoals 2 PeriodGoals 3 PeriodGoals 4+ Period
1003104410095310099826
Face Offs
Won Offensive ZoneTotal OffensiveWon Offensive %Won Defensif ZoneTotal DefensiveWon Defensive %Won Neutral ZoneTotal NeutralWon Neutral %
1435290249.45%1507323146.64%727144950.17%
Puck Time
In Offensive ZoneControl In Offensive ZoneIn Defensive ZoneControl In Defensive ZoneIn Neutral ZoneControl In Neutral Zone
1855127120476041056514


Last Played Games
Filter Tips
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
DayGame Visitor Team Score Home Team Score ST OT SO RI Link
2 - 2020-10-2310Bruins1Stars3WBoxScore
4 - 2020-10-2524Stars4Chiefs2WBoxScore
5 - 2020-10-2632Stars3Cougars4LBoxScore
7 - 2020-10-2839Stars5Bears3WBoxScore
9 - 2020-10-3055Heat3Stars4WBoxScore
11 - 2020-11-0170Bears3Stars4WBoxScore
13 - 2020-11-0382Stars5Crunch4WBoxScore
15 - 2020-11-0594Stars5Monsters2WBoxScore
17 - 2020-11-07108Stars4Manchots3WBoxScore
18 - 2020-11-08118Stars5Phantoms6LXXBoxScore
20 - 2020-11-10132Senators3Stars4WXBoxScore
23 - 2020-11-13152Admirals3Stars4WBoxScore
25 - 2020-11-15166Manchots4Stars3LXXBoxScore
28 - 2020-11-18186Minnesota2Stars7WBoxScore
31 - 2020-11-21201Stars3Monsters4LBoxScore
32 - 2020-11-22206Rocket4Stars2LBoxScore
35 - 2020-11-25230Monsters4Stars5WXBoxScore
40 - 2020-11-30264Stars4Oceanics3WXXBoxScore
43 - 2020-12-03284Stars6Heat3WBoxScore
44 - 2020-12-04291Stars4Comets3WBoxScore
46 - 2020-12-06300Stars5Oil Kings3WBoxScore
49 - 2020-12-09327Comets4Stars6WBoxScore
51 - 2020-12-11342Oceanics5Stars1LBoxScore
53 - 2020-12-13359Baby Hawks5Stars4LXXBoxScore
55 - 2020-12-15371Las Vegas5Stars4LXXBoxScore
56 - 2020-12-16376Stars5Baby Hawks2WBoxScore
59 - 2020-12-19402Chiefs2Stars4WBoxScore
61 - 2020-12-21416Stars3Minnesota4LBoxScore
63 - 2020-12-23431Stars4Oceanics2WBoxScore
65 - 2020-12-25445Oceanics9Stars4LBoxScore
67 - 2020-12-27461Sound Tigers4Stars2LBoxScore
70 - 2020-12-30478Spiders1Stars2WBoxScore
73 - 2021-01-02499Las Vegas2Stars3WBoxScore
74 - 2021-01-03505Stars5Chill4WBoxScore
76 - 2021-01-05523Oil Kings2Stars4WBoxScore
79 - 2021-01-08539Stars1Thunder4LBoxScore
80 - 2021-01-09548Stars8Cabaret Lady Mary Ann2WBoxScore
82 - 2021-01-11566Heat2Stars4WBoxScore
88 - 2021-01-17593Monsters5Stars3LBoxScore
89 - 2021-01-18609Stars2Jayhawks3LBoxScore
92 - 2021-01-21626Chill4Stars2LBoxScore
94 - 2021-01-23640Cougars5Stars4LXXBoxScore
99 - 2021-01-28677Stars3Monarchs7LBoxScore
100 - 2021-01-29687Stars2Admirals3LBoxScore
102 - 2021-01-31702Stars3Sharks9LBoxScore
105 - 2021-02-03722Stars4Monsters2WBoxScore
107 - 2021-02-05737Crunch6Stars3LBoxScore
109 - 2021-02-07753Stars7Minnesota4WBoxScore
118 - 2021-02-16771Thunder3Stars1LBoxScore
120 - 2021-02-18776Marlies3Stars2LBoxScore
123 - 2021-02-21798Stars2Spiders3LBoxScore
125 - 2021-02-23810Stars5Wolf Pack3WBoxScore
126 - 2021-02-24816Stars6Sound Tigers3WBoxScore
129 - 2021-02-27842Minnesota2Stars7WBoxScore
130 - 2021-02-28852Stars2Chiefs3LXBoxScore
133 - 2021-03-03873Caroline3Stars6WBoxScore
135 - 2021-03-05881Stars1Marlies4LBoxScore
137 - 2021-03-07900Stars3Rocket2WBoxScore
138 - 2021-03-08911Stars3Senators6LBoxScore
141 - 2021-03-11929Jayhawks3Stars2LBoxScore
143 - 2021-03-13944Chiefs4Stars2LBoxScore
145 - 2021-03-15960Baby Hawks5Stars3LBoxScore
Trade Deadline --- Trades can’t be done after this day is simulated!
147 - 2021-03-17974Stars2Caroline3LBoxScore
149 - 2021-03-19984Stars3Bruins4LBoxScore
151 - 2021-03-211007Stars1Chiefs5LBoxScore
154 - 2021-03-241026Oil Kings5Stars3LBoxScore
156 - 2021-03-261039Stars2Chill6LBoxScore
158 - 2021-03-281051Chill8Stars2LBoxScore
161 - 2021-03-311076Wolf Pack2Stars4WBoxScore
163 - 2021-04-021090Cabaret Lady Mary Ann4Stars5WBoxScore
165 - 2021-04-041106Sharks4Stars2LBoxScore
167 - 2021-04-061122Stars4Jayhawks3WBoxScore
168 - 2021-04-071130Stars4Las Vegas5LBoxScore
171 - 2021-04-101149Phantoms4Stars1LBoxScore
173 - 2021-04-121168Oceanics7Stars3LBoxScore
175 - 2021-04-141184Monarchs9Stars2LBoxScore
178 - 2021-04-171202Stars4Baby Hawks8LBoxScore
179 - 2021-04-181212Monsters6Stars4LBoxScore
181 - 2021-04-201227Comets5Stars1LBoxScore
183 - 2021-04-221241Stars3Admirals5LBoxScore
184 - 2021-04-231254Stars0Sharks4LBoxScore
186 - 2021-04-251270Stars3Monarchs4LBoxScore



Arena Capacity - Ticket Price Attendance - %
Level 1Level 2
Arena Capacity20001000
Ticket Price205
Attendance80,89640,103
Attendance PCT98.65%97.81%

Income
Home Games LeftAverage Attendance - %Average Income per GameYear to Date RevenueArena CapacityTeam Popularity
0 2951 - 98.37% 48,545$1,990,364$3000100

Expenses
Year To Date ExpensesPlayers Total SalariesPlayers Total Average SalariesCoaches Salaries
1,924,250$ 1,617,700$ 1,617,700$ 0$
Salary Cap Per DaysSalary Cap To DatePlayers In Salary CapPlayers Out of Salary Cap
8,697$ 1,924,250$ 22 0

Estimate
Estimated Season RevenueRemaining Season DaysExpenses Per DaysEstimated Season Expenses
0$ 0 8,697$ 0$




OverallHomeVisitor
Year 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