Little Stars
GP: 80 | W: 41 | L: 33 | OTL: 6 | P: 88
GF: 380 | GA: 367 | PP%: 25.96% | PK%: 75.92%
GM : François Cloutier | Morale : 42 | Team Overall : 63
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
1Evgeny Kuznetsov (R)X100.006736827272777474676586667254484942710231975,000$
2Dana TyrellX100.007132807271817772737574696260533444710261825,000$
3Jesse JoensuuX100.007333737274707973657568646967582365690281800,000$
4Ilya Mikheyev (R)X100.007349796667747273746663586645465163660212500,000$
5Scott Kosmachuck (R)X100.007134747271607670557669635947454753660212550,000$
6Joakim Nygard (R)X100.005340797366595579706859598246495352650222500,000$
7Adam Tambellini (R)X100.005929766680726465667180456144434663650214600,000$
8Daniel O'regan (R)X100.006228766660737068707669535544434762640212400,000$
9Michael Mersch (R)X100.006535726972656569635574506954544247640232500,000$
10Sebastian Wannstrom (R)X100.006229686869676464707070485953533362630241350,000$
11Roman Horak (R)X100.005939756859676570726960475146462841620243300,000$
12Zach Budish (R)X100.006932756266626360647069536148463462620241500,000$
13Tyler Wotherspoon (R)X100.007026867473737269507258796253445159710222900,000$
14Patrick Wiercioch (R)X100.006733747465676969486959705253483462670251350,000$
15Eric Knodel (R)X100.007334686966776366426856685156533228660252500,000$
16Anton Cederholm (R)X100.006427826371666654447257784345425762660204750,000$
17Reece Willcox (R)X100.005929737262626963466552735944435062630212375,000$
18Tucker Poolman (R)X100.006633687364595663576548605646454762610224600,000$
Scratches
1Emile Poirier (R)X100.005128786771626460606177486945434920620213550,000$
2Daniil Tarasov (R)X100.006230676167615865696565545954543119610241300,000$
3Jason Dickinson (R)X100.006332726561606668706265507042426443610204500,000$
4Shane Gersich (R)X100.005935766752637272757462375141417320610191500,000$
5Justin Auger (R)X100.005626725462676256596969396645445020580213500,000$
6Radel Fazleev (R)X100.004631696248636160717362435041415620580191500,000$
7Rudolfs Balcers (R)X100.005633655248605249565162455640406920520182500,000$
8Jean-Christophe Beaudin (R)X100.004821595045515860586554364840407720520182500,000$
9Julien Nantel (R)X100.004740625152605551555560394741415220520191500,000$
10Yakov Trenin (R)X100.006030615359564959475149385440405920510182500,000$
11Ville Pokka (R)X100.006236686058626065336461565343435115590211350,000$
12Lawrence Pilut (R)X100.005934675257566261396156525045426420560202500,000$
TEAM AVERAGE100.00623273656465656560676455594746484262
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
1Dustin Tokarski100.00716781686577766967736764563362700
2Connor Knapp100.00725967747568636373667252523062680
Scratches
1Peter Delmas100.00636773687467667264636748483320670
TEAM AVERAGE100.0069647470717168686867695552324868
Coaches Name PH DF OF PD EX LD PO CNT Age Contract Salary
Claude Julien82837474596155CAN5121,000,000$


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
1Jesse JoensuuLittle Stars (Dal)LW775781138157151649834412020816.57%49170922.202230526630931481645245.00%1807729131.61261007115
2Scott KosmachuckLittle Stars (Dal)RW79547112518835135852687214920.15%45157919.99192948552990005775348.23%1415523001.5833000668
3Dana TyrellLittle Stars (Dal)C61357410912601081352236713315.70%34134922.12730373221413451993154.46%19303127121.6236000755
4Evgeny KuznetsovLittle Stars (Dal)C60374279-5140931182157113517.21%45126821.141418323520701121622248.08%15393428011.2525000641
5Ilya MikheyevLittle Stars (Dal)RW80323567-2729515273172539918.60%28134116.77151227442480002462051.92%523222001.0013001234
6Daniel O'reganLittle Stars (Dal)C80234063-122407897171539813.45%16114414.313811111351122645048.77%6932319001.1002000120
7Adam TambelliniLittle Stars (Dal)LW80253459-2045586611804610213.89%21126715.854111521242000032256.92%654515000.9300001123
8Tyler WotherspoonLittle Stars (Dal)D79134659-121409616816563707.88%143224528.4361521333490223257100.00%04679000.5302000012
9Joakim NygardLittle Stars (Dal)LW80272451-78043601995810113.57%2699812.481233364048723154.00%502613011.0201000604
10Patrick WierciochLittle Stars (Dal)D8083947-12106013715512154566.61%132223027.8861117203530000220110.00%03473000.4200000004
11Anton CederholmLittle Stars (Dal)D8052732-18180711308143296.17%83164520.5704452190110171000.00%0559100.3900000000
12Eric KnodelLittle Stars (Dal)D6052530-10340104855419289.26%62120520.0831481590110117200.00%01732100.5000000100
13Zach BudishLittle Stars (Dal)RW801513280606151103254214.56%176428.0300008000002050.00%141010000.8700000201
14Sebastian WannstromLittle Stars (Dal)RW8071623-13300895111332666.19%1886810.86011000004290143.18%442310000.5300000011
15Michael MerschLittle Stars (Dal)LW70111122-51605237110317210.00%86198.840110110111171055.56%273510000.7100000100
16Reece WillcoxLittle Stars (Dal)D8041822034044776227226.45%81112714.10101462000059200.00%0831000.3900000000
17Roman HorakLittle Stars (Dal)C629918-7155573984264810.71%1262210.03000010110330050.37%2701612000.5800000110
18Jason DickinsonLittle Stars (Dal)C5731518-28027337321404.11%34547.9800000000010048.88%17894000.7901000000
19Tucker PoolmanLittle Stars (Dal)D801781128070453415182.94%5599212.4100004000043000.00%0520000.1600000000
20Emile PoirierLittle Stars (Dal)LW13527620322381021.74%31058.1501102000011075.00%434001.3200000000
21Ville PokkaLittle Stars (Dal)D21033640131319320.00%1024411.6500000000011000.00%0514000.2500000000
22Daniil TarasovLittle Stars (Dal)RW1011000100120.00%12121.5001105000000033.33%311000.9300000000
Team Total or Average14403766331009-9361525168416132814908153013.36%8922368516.45101175276337287391221401756371350.81%5190540535470.851129102413638
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
1Connor KnappLittle Stars (Dal)48211540.8644.502401001801320686420.643143842010
2Dustin TokarskiLittle Stars (Dal)46201820.8624.492434401821319626300.667124238201
Team Total or Average94413360.8634.4948354036226391312720.654268080211


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
Adam TambelliniLittle Stars (Dal)LW211994-01-01Yes185 Lbs6 ft4NoNoNo4Pro & Farm600,000$0$0$No600,000$600,000$600,000$
Anton CederholmLittle Stars (Dal)D201995-01-01Yes185 Lbs6 ft2NoNoNo4Pro & Farm750,000$0$0$No750,000$750,000$750,000$
Connor KnappLittle Stars (Dal)G251990-01-01No206 Lbs6 ft6NoNoNo1Pro & Farm300,000$0$0$No
Dana TyrellLittle Stars (Dal)C261989-01-01No185 Lbs5 ft10NoNoNo1Pro & Farm825,000$0$0$No
Daniel O'reganLittle Stars (Dal)C211994-01-01Yes169 Lbs5 ft9NoNoNo2Pro & Farm400,000$0$0$No400,000$
Daniil TarasovLittle Stars (Dal)RW241991-01-01Yes185 Lbs6 ft0NoNoNo1Pro & Farm300,000$0$0$No
Dustin TokarskiLittle Stars (Dal)G261989-01-01No198 Lbs5 ft11NoNoNo1Pro & Farm800,000$0$0$No
Emile PoirierLittle Stars (Dal)LW211994-01-01Yes185 Lbs6 ft1NoNoNo3Pro & Farm550,000$0$0$No550,000$550,000$
Eric KnodelLittle Stars (Dal)D251990-01-01Yes216 Lbs6 ft6NoNoNo2Pro & Farm500,000$0$0$No500,000$
Evgeny KuznetsovLittle Stars (Dal)C231992-01-01Yes172 Lbs6 ft0NoNoNo1Pro & Farm975,000$0$0$No
Ilya MikheyevLittle Stars (Dal)RW211994-01-01Yes195 Lbs6 ft3NoNoNo2Pro & Farm500,000$0$0$No500,000$
Jason DickinsonLittle Stars (Dal)C201995-01-01Yes185 Lbs6 ft2NoNoNo4Pro & Farm500,000$0$0$No500,000$500,000$500,000$
Jean-Christophe BeaudinLittle Stars (Dal)C181997-01-01Yes196 Lbs6 ft1NoNoNo2Pro & Farm500,000$0$0$No500,000$
Jesse JoensuuLittle Stars (Dal)LW281987-01-01No209 Lbs6 ft4NoNoNo1Pro & Farm800,000$0$0$No
Joakim NygardLittle Stars (Dal)LW221993-01-01Yes179 Lbs6 ft0NoNoNo2Pro & Farm500,000$0$0$No500,000$
Julien NantelLittle Stars (Dal)LW191996-01-01Yes195 Lbs6 ft0NoNoNo1Pro & Farm500,000$0$0$No
Justin AugerLittle Stars (Dal)RW211994-01-01Yes185 Lbs6 ft7NoNoNo3Pro & Farm500,000$0$0$No500,000$500,000$
Lawrence PilutLittle Stars (Dal)D201995-01-01Yes194 Lbs5 ft11NoNoNo2Pro & Farm500,000$0$0$No500,000$
Michael MerschLittle Stars (Dal)LW231992-01-01Yes218 Lbs6 ft2NoNoNo2Pro & Farm500,000$0$0$No500,000$
Patrick WierciochLittle Stars (Dal)D251990-01-01Yes192 Lbs6 ft4NoNoNo1Pro & Farm350,000$0$0$No
Peter DelmasLittle Stars (Dal)G251990-01-01No169 Lbs6 ft2NoNoNo1Pro & Farm575,000$0$0$No
Radel FazleevLittle Stars (Dal)C191996-01-01Yes192 Lbs5 ft11NoNoNo1Pro & Farm500,000$0$0$No
Reece WillcoxLittle Stars (Dal)D211994-01-01Yes184 Lbs6 ft3NoNoNo2Pro & Farm375,000$0$0$No375,000$
Roman HorakLittle Stars (Dal)C241991-01-01Yes170 Lbs6 ft0NoNoNo3Pro & Farm300,000$0$0$No300,000$300,000$
Rudolfs BalcersLittle Stars (Dal)LW181997-01-01Yes180 Lbs5 ft11NoNoNo2Pro & Farm500,000$0$0$No500,000$
Scott KosmachuckLittle Stars (Dal)RW211994-01-01Yes185 Lbs5 ft11NoNoNo2Pro & Farm550,000$0$0$No550,000$
Sebastian WannstromLittle Stars (Dal)RW241991-01-01Yes180 Lbs6 ft1NoNoNo1Pro & Farm350,000$0$0$No
Shane GersichLittle Stars (Dal)LW191996-01-01Yes175 Lbs5 ft11NoNoNo1Pro & Farm500,000$0$0$No
Tucker PoolmanLittle Stars (Dal)D221993-01-01Yes185 Lbs6 ft2NoNoNo4Pro & Farm600,000$0$0$No600,000$600,000$600,000$
Tyler WotherspoonLittle Stars (Dal)D221993-01-01Yes210 Lbs6 ft2NoNoNo2Pro & Farm900,000$0$0$No975,000$
Ville PokkaLittle Stars (Dal)D211994-01-01Yes205 Lbs5 ft11NoNoNo1Pro & Farm350,000$0$0$No
Yakov TreninLittle Stars (Dal)C181997-01-01Yes201 Lbs6 ft2NoNoNo2Pro & Farm500,000$0$0$No500,000$
Zach BudishLittle Stars (Dal)RW241991-01-01Yes223 Lbs6 ft3NoNoNo1Pro & Farm500,000$0$0$No
Total PlayersAverage AgeAverage WeightAverage HeightAverage ContractAverage Year 1 Salary
3322.03191 Lbs6 ft11.91534,848$



5 vs 5 Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Jesse JoensuuDana TyrellScott Kosmachuck40122
2Adam TambelliniEvgeny KuznetsovIlya Mikheyev30122
3Joakim NygardDaniel O'reganSebastian Wannstrom20122
4Michael MerschRoman HorakZach Budish10122
5 vs 5 Defense
Line #DefenseDefenseTime %PHYDFOF
1Tyler WotherspoonPatrick Wiercioch40122
2Anton CederholmEric Knodel30122
3Tucker PoolmanReece Willcox20122
4Tyler WotherspoonPatrick Wiercioch10122
Power Play Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Jesse JoensuuDana TyrellScott Kosmachuck60023
2Adam TambelliniEvgeny KuznetsovIlya Mikheyev40023
Power Play Defense
Line #DefenseDefenseTime %PHYDFOF
1Tyler WotherspoonPatrick Wiercioch60023
2Anton CederholmEric Knodel40023
Penalty Kill 4 Players Forward
Line #CenterWingTime %PHYDFOF
1Dana TyrellJesse Joensuu60032
2Evgeny KuznetsovScott Kosmachuck40032
Penalty Kill 4 Players Defense
Line #DefenseDefenseTime %PHYDFOF
1Tyler WotherspoonPatrick Wiercioch60032
2Anton CederholmEric Knodel40032
Penalty Kill 3 Players
Line #WingTime %PHYDFOFDefenseDefenseTime %PHYDFOF
1Dana Tyrell60032Tyler WotherspoonPatrick Wiercioch60032
2Evgeny Kuznetsov40032Anton CederholmEric Knodel40032
4 vs 4 Forward
Line #CenterWingTime %PHYDFOF
1Dana TyrellJesse Joensuu60023
2Evgeny KuznetsovScott Kosmachuck40023
4 vs 4 Defense
Line #DefenseDefenseTime %PHYDFOF
1Tyler WotherspoonPatrick Wiercioch60023
2Anton CederholmEric Knodel40023
Last Minutes Offensive
Left WingCenterRight WingDefenseDefense
Jesse JoensuuDana TyrellScott KosmachuckTyler WotherspoonPatrick Wiercioch
Last Minutes Defensive
Left WingCenterRight WingDefenseDefense
Jesse JoensuuDana TyrellScott KosmachuckTyler WotherspoonPatrick Wiercioch
Extra Forwards
Normal PowerPlayPenalty Kill
Evgeny Kuznetsov, Adam Tambellini, Daniel O'reganJoakim Nygard, Michael MerschDaniel O'regan
Extra Defensemen
Normal PowerPlayPenalty Kill
Tucker Poolman, Anton Cederholm, Eric KnodelTucker PoolmanAnton Cederholm, Eric Knodel
Penalty Shots
Dana Tyrell, Evgeny Kuznetsov, Jesse Joensuu, Scott Kosmachuck, Adam Tambellini
Goalie
#1 : Connor Knapp, #2 : Dustin Tokarski


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
1Admirals30300000617-111010000026-420200000411-700.000691500118132123131078819909244511428235611218.18%11372.73%0975192350.70%922182050.66%740144751.14%171695616767481450725
2Barracuda211000001114-31010000038-51100000086220.50011193000118132123137188199092445711821398450.00%8450.00%0975192350.70%922182050.66%740144751.14%171695616767481450725
3Bears21100000131121010000058-31100000083520.500132235001181321231373881990924456224124813646.15%6266.67%0975192350.70%922182050.66%740144751.14%171695616767481450725
4Checkers42200000161601010000046-2321000001210240.50016264200118132123131258819909244513342349316318.75%18383.33%1975192350.70%922182050.66%740144751.14%171695616767481450725
5Comets612002102525030100200912-3311000101613360.5002539641011813212313209881990924451866844143361027.78%22768.18%0975192350.70%922182050.66%740144751.14%171695616767481450725
6Condors202000001114-31010000068-21010000056-100.00011162710118132123137188199092445651516395120.00%8450.00%1975192350.70%922182050.66%740144751.14%171695616767481450725
7Crunch32100000191452200000017981010000025-340.66719304900118132123131058819909244510845167316531.25%8187.50%1975192350.70%922182050.66%740144751.14%171695616767481450725
8Devils32100000171431100000075221100000109140.6671730470011813212313968819909244593351755201050.00%6183.33%0975192350.70%922182050.66%740144751.14%171695616767481450725
9Eagles420001012017331000101141401100000063360.750202949001181321231314488199092445139442611522627.27%13192.31%0975192350.70%922182050.66%740144751.14%171695616767481450725
10Griffins311000101091210000108531010000024-240.6671015250011813212313119881990924459828146218316.67%7185.71%0975192350.70%922182050.66%740144751.14%171695616767481450725
11Heat311010001815311000000743201010001111040.66718304800118132123131158819909244511139206114535.71%10280.00%1975192350.70%922182050.66%740144751.14%171695616767481450725
12IceHogs3200000113103210000019811100000042250.83313213400118132123131168819909244510841286116531.25%14378.57%1975192350.70%922182050.66%740144751.14%171695616767481450725
13Influenza2110000079-21010000028-61100000051420.5007121900118132123137288199092445692514389111.11%70100.00%1975192350.70%922182050.66%740144751.14%171695616767481450725
14Monsters2010001056-11010000024-21000001032120.5005611001181321231368881990924456821652900.00%30100.00%1975192350.70%922182050.66%740144751.14%171695616767481450725
15Moose21100000871110000006241010000025-320.50081321001181321231374881990924456717635400.00%3166.67%0975192350.70%922182050.66%740144751.14%171695616767481450725
16Penguins32100000121202200000010731010000025-340.667121830001181321231396881990924459641236120630.00%9277.78%0975192350.70%922182050.66%740144751.14%171695616767481450725
17Phantoms20200000711-41010000045-11010000036-300.0007142100118132123136088199092445712214308112.50%7185.71%0975192350.70%922182050.66%740144751.14%171695616767481450725
18Punishers935000014655-94210000123194514000002336-1370.389468112700118132123133258819909244528811489183501224.00%401562.50%1975192350.70%922182050.66%740144751.14%171695616767481450725
19Rampage3210000016115110000009272110000079-240.667162844001181321231394881990924459924405615213.33%20670.00%1975192350.70%922182050.66%740144751.14%171695616767481450725
20Reign211000001091110000008531010000024-220.50010152500118132123137488199092445592020401218.33%10280.00%0975192350.70%922182050.66%740144751.14%171695616767481450725
21Rocket210010001064110000007431000100032141.00010162600118132123137088199092445602414606116.67%70100.00%0975192350.70%922182050.66%740144751.14%171695616767481450725
22Senators3210000016972200000013581010000034-140.667162945001181321231310888199092445903426511119.09%14378.57%0975192350.70%922182050.66%740144751.14%171695616767481450725
23Sound Tigers211000001091110000005321010000056-120.5001019290011813212313768819909244562228359333.33%40100.00%0975192350.70%922182050.66%740144751.14%171695616767481450725
24Thunderbirds62201010292813110100019145311000101014-480.6672948770011813212313190881990924451915668120331236.36%34973.53%0975192350.70%922182050.66%740144751.14%171695616767481450725
25Wolfpack4310000025196211000001211122000000138560.7502548730011813212313156881990924451334520788112.50%10190.00%0975192350.70%922182050.66%740144751.14%171695616767481450725
Total8034330334338036713402012013132111822940142102030169185-16880.550380633101320118132123132814881990924452641892619168438910125.96%2997275.92%9975192350.70%922182050.66%740144751.14%171695616767481450725
_Since Last GM Reset8034330334338036713402012013132111822940142102030169185-16880.550380633101320118132123132814881990924452641892619168438910125.96%2997275.92%9975192350.70%922182050.66%740144751.14%171695616767481450725
_Vs Conference512418023222592352425145013021441083626101301020115127-12610.5982594366951011813212313176388199092445166758742310892617327.97%2045175.00%5975192350.70%922182050.66%740144751.14%171695616767481450725
_Vs Division216901221100108-8103301201514561136000204963-14210.5001001682681011813212313724881990924456652382014461193428.57%963167.71%1975192350.70%922182050.66%740144751.14%171695616767481450725

Total For Players
Games PlayedPointsStreakGoalsAssistsPointsShots ForShots AgainstShots BlockedPenalty MinutesHitsEmpty Net GoalsShutouts
8088W1380633101328142641892619168420
All Games
GPWLOTWOTL SOWSOLGFGA
8034333343380367
Home Games
GPWLOTWOTL SOWSOLGFGA
4020121313211182
Visitor Games
GPWLOTWOTL SOWSOLGFGA
4014212030169185
Last 10 Games
WLOTWOTL SOWSOL
630001
Power Play AttempsPower Play GoalsPower Play %Penalty Kill AttempsPenalty Kill Goals AgainstPenalty Kill %Penalty Kill Goals For
38910125.96%2997275.92%9
Shots 1 PeriodShots 2 PeriodShots 3 PeriodShots 4+ PeriodGoals 1 PeriodGoals 2 PeriodGoals 3 PeriodGoals 4+ Period
8819909244511813212313
Face Offs
Won Offensive ZoneTotal OffensiveWon Offensive %Won Defensif ZoneTotal DefensiveWon Defensive %Won Neutral ZoneTotal NeutralWon Neutral %
975192350.70%922182050.66%740144751.14%
Puck Time
In Offensive ZoneControl In Offensive ZoneIn Defensive ZoneControl In Defensive ZoneIn Neutral ZoneControl In Neutral Zone
171695616767481450725


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 - 2020-10-109Punishers5Little Stars3LBoxScore
4 - 2020-10-1220Little Stars5Punishers9LBoxScore
6 - 2020-10-1431Thunderbirds6Little Stars7WXBoxScore
7 - 2020-10-1537Little Stars3Punishers9LBoxScore
11 - 2020-10-1956Little Stars5Comets7LR1BoxScore
13 - 2020-10-2172Punishers5Little Stars7WBoxScore
15 - 2020-10-2381Little Stars3Thunderbirds2WBoxScore
17 - 2020-10-2592Eagles5Little Stars4LXXR1BoxScore
20 - 2020-10-28106Little Stars2Thunderbirds8LBoxScore
22 - 2020-10-30120Comets5Little Stars4LXR1BoxScore
25 - 2020-11-02134Little Stars8Punishers6WBoxScore
28 - 2020-11-05150Penguins5Little Stars7WR2BoxScore
30 - 2020-11-07162Little Stars3Checkers6LBoxScore
32 - 2020-11-09175Wolfpack7Little Stars6LBoxScore
34 - 2020-11-11184Little Stars7Devils3WBoxScore
36 - 2020-11-13196Senators3Little Stars8WR1BoxScore
39 - 2020-11-16212Little Stars5Condors6LBoxScore
41 - 2020-11-18223Eagles4Little Stars3LXR1BoxScore
43 - 2020-11-20233Little Stars5Influenza1WBoxScore
45 - 2020-11-22243Little Stars4IceHogs2WR1BoxScore
47 - 2020-11-24255Punishers6Little Stars5LXXBoxScore
52 - 2020-11-29277Admirals6Little Stars2LBoxScore
55 - 2020-12-02295Condors8Little Stars6LBoxScore
57 - 2020-12-04306Little Stars3Rocket2WXBoxScore
61 - 2020-12-08326Senators2Little Stars5WR1BoxScore
64 - 2020-12-11344Barracuda8Little Stars3LBoxScore
67 - 2020-12-14360Little Stars6Eagles3WR1BoxScore
69 - 2020-12-16369Penguins2Little Stars3WBoxScore
71 - 2020-12-18376Little Stars5Heat6LBoxScore
75 - 2020-12-22396Reign5Little Stars8WR1BoxScore
77 - 2020-12-24407Little Stars3Senators4LR1BoxScore
79 - 2020-12-26421Rampage2Little Stars9WBoxScore
81 - 2020-12-28431Little Stars5Punishers8LBoxScore
84 - 2020-12-31448Checkers6Little Stars4LR1BoxScore
87 - 2021-01-03461Little Stars3Monsters2WXXBoxScore
89 - 2021-01-05475Comets3Little Stars2LR1BoxScore
92 - 2021-01-08486Little Stars7Comets3WBoxScore
94 - 2021-01-10501Wolfpack4Little Stars6WBoxScore
100 - 2021-01-16523Little Stars2Moose5LBoxScore
101 - 2021-01-17530Sound Tigers3Little Stars5WR1BoxScore
104 - 2021-01-20542Little Stars5Rampage4WR1BoxScore
107 - 2021-01-23555Little Stars2Punishers4LBoxScore
108 - 2021-01-24559Heat4Little Stars7WBoxScore
111 - 2021-01-27579Punishers3Little Stars8WBoxScore
113 - 2021-01-29593Little Stars8Bears3WBoxScore
115 - 2021-01-31605Monsters4Little Stars2LBoxScore
117 - 2021-02-02611Little Stars2Griffins4LBoxScore
119 - 2021-02-04623Little Stars5Sound Tigers6LR1BoxScore
121 - 2021-02-06633Little Stars6Heat5WXBoxScore
122 - 2021-02-07639Devils5Little Stars7WBoxScore
126 - 2021-02-11660Griffins2Little Stars4WBoxScore
131 - 2021-02-16684Phantoms5Little Stars4LBoxScore
133 - 2021-02-18692Little Stars2Admirals6LBoxScore
135 - 2021-02-20703Little Stars2Crunch5LBoxScore
137 - 2021-02-22714Thunderbirds3Little Stars8WBoxScore
139 - 2021-02-24730Little Stars5Thunderbirds4WXXBoxScore
141 - 2021-02-26738Comets4Little Stars3LXR1BoxScore
147 - 2021-03-04762Thunderbirds5Little Stars4LBoxScore
149 - 2021-03-06775Little Stars2Admirals5LBoxScore
151 - 2021-03-08787Influenza8Little Stars2LBoxScore
153 - 2021-03-10796Little Stars4Checkers3WR1BoxScore
158 - 2021-03-15813Bears8Little Stars5LBoxScore
Trade Deadline --- Trades can’t be done after this day is simulated!
161 - 2021-03-18831Little Stars2Rampage5LR1BoxScore
162 - 2021-03-19840Eagles5Little Stars7WBoxScore
165 - 2021-03-22853Little Stars8Barracuda6WBoxScore
168 - 2021-03-25866Moose2Little Stars6WBoxScore
170 - 2021-03-27880Little Stars4Comets3WXXR1BoxScore
172 - 2021-03-29889Rocket4Little Stars7WBoxScore
174 - 2021-03-31899Little Stars2Reign4LR1BoxScore
177 - 2021-04-03915Griffins3Little Stars4WXXBoxScore
178 - 2021-04-04920Little Stars7Wolfpack5WBoxScore
181 - 2021-04-07933Little Stars5Checkers1WR1BoxScore
184 - 2021-04-10944Little Stars6Wolfpack3WBoxScore
186 - 2021-04-12950IceHogs4Little Stars3LXXR1BoxScore
188 - 2021-04-14966Little Stars2Penguins5LR2BoxScore
189 - 2021-04-15972Little Stars3Phantoms6LBoxScore
191 - 2021-04-17983Crunch7Little Stars10WBoxScore
195 - 2021-04-211001Crunch2Little Stars7WBoxScore
198 - 2021-04-241015Little Stars3Devils6LBoxScore
201 - 2021-04-271029IceHogs4Little Stars6WR1BoxScore



Arena Capacity - Ticket Price Attendance - %
Level 1Level 2
Capacity20001000
Ticket Price4020
Attendance54,12727,364
Attendance PCT67.66%68.41%

Income
Home Games LeftAverage Attendance - %Average Income per GameYear to Date RevenueCapacityTeam Popularity
0 2037 - 67.91% 70,881$2,835,241$3000100

Expenses
Year To Date ExpensesPlayers Total SalariesPlayers Total Average SalariesCoaches Salaries
2,726,854$ 1,765,000$ 2,642,500$ 0$
Salary Cap Per DaysSalary Cap To DatePlayers In Salary CapPlayers Out of Salary Cap
8,610$ 1,706,359$ 0 0

Estimate
Estimated Season RevenueRemaining Season DaysExpenses Per DaysEstimated Season Expenses
0$ 0 13,488$ 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