Riverman
GP: 82 | W: 47 | L: 31 | T: 3 | P: 98
GF: 287 | GA: 250 | PP%: 22.02% | PK%: 80.70%
GM : Patrick Poulin | Morale : 61 | Team Overall : 61
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
1Shaun Van AllenX100.007467586275777572677870736443415366660281650,000$
2Brent HughesX100.007965546970747465566674726845465342650281350,000$
3Mike StapletonX100.006547836771667070666966756657565457650282525,000$
4Kris Draper (R)X100.006150737272666872647265786030288979640231350,000$
5Jamie LeachX100.007864636776747564637566606350477561640251250,000$
6Jeff NielsenX100.007661666674686671606970666245478179640241150,000$
7Michael Nylander (R)X100.005241777172707172657469586435329680630222400,000$
8Valery Bure (R)X100.004538777470666673647371576526299879620203450,000$
9Dan BylsmaX100.006750736778686859566461735836337579610251150,000$
10Andrei Nazarov (R)X100.008476496580666664636856725328289779610202350,000$
11Peter Ferraro (R)X100.006559557071636461576460615830359759590211325,000$
12Yan Kaminsky (R)X100.004035787168606061586560625829288933580233400,000$
13Alexander KarpovtsevX100.006346807078707062616759755840398364640241400,000$
14Jaroslav ModryX100.005645777076717266647257765435358965640232350,000$
15Chris TherienX100.007056646483707161596652765030308979630231800,000$
16Marcus RagnarssonX100.005848676678696976647667715637298858630233456,000$
17Richard Matvichuk (R)X100.007263556274697062505850804230309770620213350,000$
18Adrian Aucoin (R)X100.005449626976666662576449734730349755610211400,000$
Scratches
1Shawn Antoski (R)X100.007972426282676759566447674535378223580242180,000$
2Sergei Brylin (R)X100.005245736971585963606656675428319719580203495,000$
3Steve Staios (R)X100.006150717075596159556145654329329620560212330,000$
4Alexei Zhitnik (R)X100.005747676774727171647162665828289636610223375,000$
5Karl Dykhuis (R)X100.007164576278636457546242774029299019600231275,000$
6Dmitri Motkov (R)X100.005449637276626461566748684231388820600232200,000$
7Aaron Ward (R)X100.006152686672606261576348774628289720600211300,000$
8Michal Sykora (R)X100.006152735980575964526944673228279820580212320,000$
9Joel Bouchard (R)X100.005049676170575951465035653327309720540202300,000$
TEAM AVERAGE100.00635366677566676459675770533434875161
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
1Corey Schwab100.00677076747262707469686529418350640
2Andrew Verner (R)100.00656678767358667566686227279771620
Scratches
TEAM AVERAGE100.0066687775736068756868642834906163
Coaches Name PH DF OF PD EX LD PO CNT Age Contract Salary
Ken Hitchcock72777679778387CAN43295,000$


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
1Mike StapletonRiverman (VAN)C6930447422160321671874613316.04%10133419.34818266027911261693350.42%155500001.1100000572
2Shaun Van AllenRiverman (VAN)C67204565103351181801806013911.11%20150122.41821295427900093113151.49%177500110.8700001464
3Jeff NielsenRiverman (VAN)RW82342963178525153742005614017.00%4137916.82131326663360001329139.29%8400000.9100113445
4Yvon CorriveauCanucksLW69303060229597941794813616.76%9136319.771119305128600072328349.01%20200010.8800000681
5Jaroslav ModryRiverman (VAN)D63173451650080105101406916.83%81148023.50131124742690111246010.00%000100.6900000323
6Alexander KarpovtsevRiverman (VAN)D669415079001288277327311.69%85154823.4761925422720110248220.00%000000.6500000113
7Chris TherienRiverman (VAN)D821334471411151477686396115.12%89179521.89101727553340000274400.00%000000.5200001142
8Kris DraperRiverman (VAN)C822719461200581881955412713.85%22121214.793811251010000553049.28%124800000.7600000515
9Bryan EricksonCanucksLW4916254112401864142238811.27%792118.8161117342060008864055.32%9400000.8900000322
10Andrei NazarovRiverman (VAN)LW82132538013802258798449213.27%11113513.850449870000102145.33%7500000.6700000332
11Richard MatvichukRiverman (VAN)D781025356116201827383215512.05%76146818.836915432100001163000.00%000000.4800211122
12Marcus RagnarssonRiverman (VAN)D44727341930045527522439.33%4396922.033912531720110161120.00%000000.7000000202
13Valery BureRiverman (VAN)RW80101828-38014104143361056.99%5113114.151347540000493045.54%11200000.4900000021
14Randy McKayCanucksRW3681927-974101426511733896.84%1088924.71310133016000071441048.75%44100000.6100011311
15Adrian AucoinRiverman (VAN)D683192276515606230112210.00%74111116.351347640000111000.00%000000.4000101010
16Michael NylanderRiverman (VAN)C8281220-1113568771187111.27%57158.73000180004740048.71%73700000.5600100001
17Jamie LeachRiverman (VAN)RW3291019710041265993015.25%353916.87426241250001161145.71%3500100.7000000123
18Alexei ZhitnikRiverman (VAN)D5621517-735550592051410.00%4587715.67011528000086100.00%000000.3900010010
19Dan BylsmaRiverman (VAN)RW8289172120143447143317.02%45336.51000180000192054.55%3300000.6400000001
20Brent HughesRiverman (VAN)LW2531013837569364420446.82%149419.76123149620231010037.84%7400000.5300001001
21Yan KaminskyRiverman (VAN)LW4844828021531112312.90%44589.56000000000380045.16%3100000.3500000011
22Dmitri MotkovRiverman (VAN)D13145-18015843425.00%620615.9100005000023000.00%100000.4800000000
23Sergei GoncharCanucksD5145-140101013497.69%712024.14022927000019000.00%000000.8300000000
24Sergei BrylinRiverman (VAN)C241344201762416.67%1672.8200007000000050.00%6000001.1800000000
25Peter FerraroRiverman (VAN)RW661234602614103910.00%11973.00011024000000037.93%5800000.3000000000
26Aaron WardRiverman (VAN)D15022-614018122230.00%1223715.8600002000027000.00%000000.1700000000
27Karl DykhuisRiverman (VAN)D2011040401000.00%32713.920000000002000.00%000000.7200000000
28Shawn AntoskiRiverman (VAN)LW5000-220412000.00%0479.550000000008000.00%000000.0000000000
Team Total or Average14722855107951101024100175917822203656161612.94%6382377116.15971832806643453347482716471549.64%661500320.6700549424842
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
1Corey SchwabRiverman (VAN)73412630.8913.0741112221019320220.00007111222
2Andrew VernerRiverman (VAN)176600.8992.7881921383750000.00001171100
Team Total or Average90473230.8933.0249304324823070220.00008282322


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 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
Aaron WardRiverman (VAN)D212000-02-09 9:08:37 PMYes200 Lbs6 ft2NoNoNo1Pro & Farm300,000$30,000$221$No
Adrian AucoinRiverman (VAN)D212000-02-09 9:08:37 PMYes210 Lbs6 ft2NoNoNo1Pro & Farm400,000$40,000$294$No
Alexander KarpovtsevRiverman (VAN)D241997-02-09 9:08:37 PMNo205 Lbs6 ft3NoNoNo1Pro & Farm400,000$40,000$294$No
Alexei ZhitnikRiverman (VAN)D221999-02-09 9:08:37 PMYes204 Lbs5 ft11NoNoNo3Pro & Farm375,000$37,500$276$No375,000$375,000$
Andrei NazarovRiverman (VAN)LW202001-02-09 9:08:37 PMYes228 Lbs6 ft5NoNoNo2Pro & Farm350,000$35,000$257$No350,000$
Andrew VernerRiverman (VAN)G221999-02-09 9:08:37 PMYes194 Lbs6 ft0NoNoNo1Pro & Farm200,000$20,000$147$No
Brent HughesRiverman (VAN)LW281993-02-09 9:08:37 PMNo180 Lbs5 ft11NoNoNo1Pro & Farm350,000$35,000$257$No
Chris TherienRiverman (VAN)D231998-02-09 9:08:37 PMNo230 Lbs6 ft5NoNoNo1Pro & Farm800,000$80,000$588$No
Corey SchwabRiverman (VAN)G241997-02-09 9:08:37 PMNo185 Lbs6 ft0NoNoNo2Pro & Farm150,000$15,000$110$No150,000$
Dan BylsmaRiverman (VAN)RW251996-02-09 9:08:37 PMNo215 Lbs6 ft2NoNoNo1Pro & Farm150,000$15,000$110$No
Dmitri MotkovRiverman (VAN)D231998-02-09 9:08:37 PMYes198 Lbs6 ft4NoNoNo2Pro & Farm200,000$20,000$147$No200,000$
Jamie LeachRiverman (VAN)RW251996-02-09 9:08:37 PMNo205 Lbs6 ft1NoNoNo1Pro & Farm250,000$25,000$184$No
Jaroslav ModryRiverman (VAN)D231998-02-09 9:08:37 PMNo205 Lbs6 ft2NoNoNo2Pro & Farm350,000$350,000$2,574$No350,000$
Jeff NielsenRiverman (VAN)RW241997-02-09 9:08:37 PMNo200 Lbs6 ft0NoNoNo1Pro & Farm150,000$15,000$110$No
Joel BouchardRiverman (VAN)D202001-02-09 9:08:37 PMYes183 Lbs6 ft0NoNoNo2Pro & Farm300,000$30,000$221$No300,000$
Karl DykhuisRiverman (VAN)D231998-02-09 9:08:37 PMYes214 Lbs6 ft3NoNoNo1Pro & Farm275,000$27,500$202$No
Kris DraperRiverman (VAN)C231998-02-09 9:08:37 PMYes188 Lbs5 ft11NoNoNo1Pro & Farm350,000$35,000$257$No
Marcus RagnarssonRiverman (VAN)D231998-02-09 9:08:37 PMNo215 Lbs6 ft1NoNoNo3Pro & Farm456,000$456,000$3,353$No456,000$456,000$
Michael NylanderRiverman (VAN)C221999-02-09 9:08:37 PMYes194 Lbs5 ft11NoNoNo2Pro & Farm400,000$40,000$294$No400,000$
Michal SykoraRiverman (VAN)D212000-02-09 9:08:37 PMYes223 Lbs6 ft5NoNoNo2Pro & Farm320,000$32,000$235$No320,000$
Mike StapletonRiverman (VAN)C281993-02-09 9:08:37 PMNo183 Lbs5 ft10NoNoNo2Pro & Farm525,000$52,500$386$No525,000$
Peter FerraroRiverman (VAN)RW212000-02-09 9:08:37 PMYes180 Lbs5 ft10NoNoNo1Pro & Farm325,000$32,500$239$No
Richard MatvichukRiverman (VAN)D212000-02-09 9:08:37 PMYes190 Lbs6 ft2NoNoNo3Pro & Farm350,000$35,000$257$No350,000$350,000$
Sergei BrylinRiverman (VAN)C202001-02-09 9:08:37 PMYes190 Lbs5 ft10NoNoNo3Pro & Farm495,000$49,500$364$No495,000$495,000$
Shaun Van AllenRiverman (VAN)C281993-02-09 9:08:37 PMNo206 Lbs6 ft1NoNoNo1Pro & Farm650,000$65,000$478$No
Shawn AntoskiRiverman (VAN)LW241997-02-09 9:08:37 PMYes235 Lbs6 ft4NoNoNo2Pro & Farm180,000$18,000$132$No180,000$
Steve StaiosRiverman (VAN)RW212000-02-09 9:08:37 PMYes200 Lbs6 ft0NoNoNo2Pro & Farm330,000$33,000$243$No330,000$
Valery BureRiverman (VAN)RW202001-02-09 9:08:37 PMYes179 Lbs5 ft11NoNoNo3Pro & Farm450,000$45,000$331$No450,000$450,000$
Yan KaminskyRiverman (VAN)LW231998-02-09 9:08:37 PMYes176 Lbs6 ft1NoNoNo3Pro & Farm400,000$40,000$294$No400,000$400,000$
Total PlayersAverage AgeAverage WeightAverage HeightAverage ContractAverage Year 1 Salary
2922.86201 Lbs6 ft11.76352,793$



5 vs 5 Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Brent HughesShaun Van AllenJeff Nielsen35122
2Andrei NazarovMike StapletonJamie Leach30122
3Yan KaminskyKris DraperValery Bure20122
4Shaun Van AllenMichael NylanderDan Bylsma15122
5 vs 5 Defense
Line #DefenseDefenseTime %PHYDFOF
1Jaroslav ModryAlexander Karpovtsev35122
2Chris TherienMarcus Ragnarsson30122
3Richard MatvichukAdrian Aucoin20122
4Jaroslav ModryAlexander Karpovtsev15122
Power Play Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Brent HughesShaun Van AllenJeff Nielsen60122
2Andrei NazarovMike StapletonJamie Leach40122
Power Play Defense
Line #DefenseDefenseTime %PHYDFOF
1Jaroslav ModryAlexander Karpovtsev60122
2Chris TherienMarcus Ragnarsson40122
Penalty Kill 4 Players Forward
Line #CenterWingTime %PHYDFOF
1Shaun Van AllenBrent Hughes60122
2Mike StapletonJeff Nielsen40122
Penalty Kill 4 Players Defense
Line #DefenseDefenseTime %PHYDFOF
1Jaroslav ModryAlexander Karpovtsev60122
2Chris TherienMarcus Ragnarsson40122
Penalty Kill 3 Players
Line #WingTime %PHYDFOFDefenseDefenseTime %PHYDFOF
1Shaun Van Allen60122Jaroslav ModryAlexander Karpovtsev60122
2Brent Hughes40122Chris TherienMarcus Ragnarsson40122
4 vs 4 Forward
Line #CenterWingTime %PHYDFOF
1Shaun Van AllenBrent Hughes60122
2Mike StapletonJeff Nielsen40122
4 vs 4 Defense
Line #DefenseDefenseTime %PHYDFOF
1Jaroslav ModryAlexander Karpovtsev60122
2Chris TherienMarcus Ragnarsson40122
Last Minutes Offensive
Left WingCenterRight WingDefenseDefense
Brent HughesShaun Van AllenJeff NielsenJaroslav ModryAlexander Karpovtsev
Last Minutes Defensive
Left WingCenterRight WingDefenseDefense
Brent HughesShaun Van AllenJeff NielsenJaroslav ModryAlexander Karpovtsev
Extra Forwards
Normal PowerPlayPenalty Kill
Peter Ferraro, Kris Draper, Michael NylanderPeter Ferraro, Kris DraperMichael Nylander
Extra Defensemen
Normal PowerPlayPenalty Kill
Richard Matvichuk, Adrian Aucoin, Chris TherienRichard MatvichukAdrian Aucoin, Chris Therien
Penalty Shots
Shaun Van Allen, Brent Hughes, Mike Stapleton, Jeff Nielsen, Jamie Leach
Goalie
#1 : Corey Schwab, #2 : Andrew Verner


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
1Ailes Rouges5311000016124311100009722200000075270.7001626420010295891135725714770714241679930723.33%24387.50%11325267449.55%1377273950.27%640133248.05%1915127119486481076536
2As5401000018993201000084422000000105590.90018335101102958911587257147707138385311229827.59%23291.30%01325267449.55%1377273950.27%640133248.05%1915127119486481076536
3Banshees642000002520521100000660431000001914580.66725457000102958911677257147707190586111626934.62%26965.38%01325267449.55%1377273950.27%640133248.05%1915127119486481076536
4Canadiens54100000171163210000076122000000105580.8001732490110295891135725714770710126429831516.13%20385.00%01325267449.55%1377273950.27%640133248.05%1915127119486481076536
5Chiefs66000000261016220000008264400000018810121.00026477301102958911737257147707175426711638718.42%29389.66%01325267449.55%1377273950.27%640133248.05%1915127119486481076536
6Citadelles624000001720-32110000067-1413000001113-240.33317314800102958911387257147707176446510326726.92%28775.00%01325267449.55%1377273950.27%640133248.05%1915127119486481076536
7Croque-Morts623010001724-730201000715-832100000109160.50017304700102958911557257147707195577313326415.38%31583.87%11325267449.55%1377273950.27%640133248.05%1915127119486481076536
8Harvard632001002324-1421001001415-12110000099070.58323406300102958911417257147707193588911319526.32%341264.71%01325267449.55%1377273950.27%640133248.05%1915127119486481076536
9Isotopes94410000372985230000019154421100001814490.50037671041010295891296725714770727067113183501428.00%501178.00%01325267449.55%1377273950.27%640133248.05%1915127119486481076536
10Pacifiques de la route963000003024642200000121115410000018135120.667305383101029589125272571477072326615422056814.29%56983.93%01325267449.55%1377273950.27%640133248.05%1915127119486481076536
11Snipers826000002332-941300000815-7413000001517-240.250233962001029589119172571477072156113021849714.29%58886.21%11325267449.55%1377273950.27%640133248.05%1915127119486481076536
12Spoonman's642000002216643100000161062110000066080.667224062001029589115472571477071483968131381334.21%29679.31%01325267449.55%1377273950.27%640133248.05%1915127119486481076536
13Wolves523000001619-32110000079-231200000910-140.40016294500102958911217257147707134454611927414.81%22577.27%01325267449.55%1377273950.27%640133248.05%1915127119486481076536
Total82463131100287250374120172110012712254126141000016012832980.5982875127992310295891221672571477072309642102817614459822.02%4308380.70%31325267449.55%1377273950.27%640133248.05%1915127119486481076536
_Since Last GM Reset8249310110028725037412017211001271225412914-20000160128321010.6162875127992310295891221672571477072309642102817614459822.02%4308380.70%31325267449.55%1377273950.27%640133248.05%1915127119486481076536
_Vs Conference3821160100012012001979210005161-1019147-20000695910440.57912021033011102958911012725714770710563085239012173817.51%2143285.05%31325267449.55%1377273950.27%640133248.05%1915127119486481076536
_Vs Division1789000005356-3835000002026-69540000033303160.4715392145101029589144372571477074471272844381051514.29%1141785.09%11325267449.55%1377273950.27%640133248.05%1915127119486481076536

Total For Players
Games PlayedPointsStreakGoalsAssistsPointsShots ForShots AgainstShots BlockedPenalty MinutesHitsEmpty Net GoalsShutouts
8298L1287512799221623096421028176123
All Games
GPWLOTWOTL TGFGA
824631113287250
Home Games
GPWLOTWOTL TGFGA
412017112127122
Visitor Games
GPWLOTWOTL TGFGA
412614001160128
Last 10 Games
WLOTWOTL T
55000
Power Play AttempsPower Play GoalsPower Play %Penalty Kill AttempsPenalty Kill Goals AgainstPenalty Kill %Penalty Kill Goals For
4459822.02%4308380.70%3
Shots 1 PeriodShots 2 PeriodShots 3 PeriodShots 4+ PeriodGoals 1 PeriodGoals 2 PeriodGoals 3 PeriodGoals 4+ Period
725714770710295891
Face Offs
Won Offensive ZoneTotal OffensiveWon Offensive %Won Defensif ZoneTotal DefensiveWon Defensive %Won Neutral ZoneTotal NeutralWon Neutral %
1325267449.55%1377273950.27%640133248.05%
Puck Time
In Offensive ZoneControl In Offensive ZoneIn Defensive ZoneControl In Defensive ZoneIn Neutral ZoneControl In Neutral Zone
1915127119486481076536


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
1 - 2020-09-214Riverman7Chiefs2WBoxScore
2 - 2020-09-229Harvard7Riverman3LBoxScore
3 - 2020-09-2316Riverman2Pacifiques de la route5LBoxScore
4 - 2020-09-2421Riverman1Isotopes4LBoxScore
6 - 2020-09-2627Isotopes2Riverman6WBoxScore
8 - 2020-09-2837Isotopes2Riverman6WBoxScore
10 - 2020-09-3047Snipers1Riverman2WBoxScore
11 - 2020-10-0154Riverman2Snipers3LBoxScore
12 - 2020-10-0260Spoonman's2Riverman5WBoxScore
14 - 2020-10-0465Riverman1Citadelles3LBoxScore
16 - 2020-10-0673Riverman6Citadelles4WBoxScore
18 - 2020-10-0880Isotopes4Riverman2LBoxScore
20 - 2020-10-1088Spoonman's2Riverman5WBoxScore
22 - 2020-10-1295Riverman4Isotopes4TXBoxScore
24 - 2020-10-14102Riverman5Spoonman's4WBoxScore
26 - 2020-10-16108Chiefs2Riverman3WBoxScore
28 - 2020-10-18115Riverman7Isotopes4WBoxScore
30 - 2020-10-20122Citadelles3Riverman4WBoxScore
32 - 2020-10-22130Riverman1Spoonman's2LBoxScore
34 - 2020-10-24136Spoonman's2Riverman3WBoxScore
36 - 2020-10-26144Riverman6Isotopes2WBoxScore
38 - 2020-10-28150Citadelles4Riverman2LBoxScore
40 - 2020-10-30158Spoonman's4Riverman3LBoxScore
42 - 2020-11-01166Riverman6As2WBoxScore
43 - 2020-11-02172Isotopes3Riverman2LBoxScore
46 - 2020-11-05180Riverman4Croque-Morts3WBoxScore
47 - 2020-11-06185Riverman3Citadelles4LBoxScore
48 - 2020-11-07192Canadiens3Riverman4WBoxScore
49 - 2020-11-08199Riverman1Citadelles2LBoxScore
51 - 2020-11-10206Isotopes4Riverman3LBoxScore
52 - 2020-11-11213Riverman2Croque-Morts4LBoxScore
55 - 2020-11-14220Snipers6Riverman2LBoxScore
56 - 2020-11-15229Ailes Rouges1Riverman4WBoxScore
58 - 2020-11-17236Riverman4Snipers5LBoxScore
59 - 2020-11-18242Banshees3Riverman1LBoxScore
61 - 2020-11-20249Riverman3Snipers6LBoxScore
62 - 2020-11-21258Ailes Rouges3Riverman3TXBoxScore
64 - 2020-11-23263Riverman3Ailes Rouges2WBoxScore
65 - 2020-11-24271As2Riverman4WBoxScore
67 - 2020-11-26280Riverman7Harvard3WBoxScore
68 - 2020-11-27285Wolves5Riverman2LBoxScore
70 - 2020-11-29294Croque-Morts2Riverman3WXBoxScore
71 - 2020-11-30296Riverman4Chiefs2WBoxScore
73 - 2020-12-02310Riverman4Chiefs2WBoxScore
74 - 2020-12-03315Chiefs0Riverman5WBoxScore
75 - 2020-12-04323Riverman2Wolves4LBoxScore
77 - 2020-12-06327As2Riverman2TXBoxScore
78 - 2020-12-07331Riverman2Pacifiques de la route1WBoxScore
79 - 2020-12-08341Riverman6Pacifiques de la route2WBoxScore
80 - 2020-12-09345Harvard2Riverman5WBoxScore
83 - 2020-12-12357Snipers4Riverman3LBoxScore
84 - 2020-12-13365Riverman4Pacifiques de la route2WBoxScore
86 - 2020-12-15368Canadiens0Riverman2WBoxScore
89 - 2020-12-18379Pacifiques de la route2Riverman3WBoxScore
90 - 2020-12-19385Riverman4Croque-Morts2WBoxScore
92 - 2020-12-21391Riverman2Harvard6LBoxScore
94 - 2020-12-23397Croque-Morts7Riverman2LBoxScore
96 - 2020-12-25403Riverman2Banshees3LBoxScore
98 - 2020-12-27409Harvard2Riverman3WBoxScore
100 - 2020-12-29417Riverman5Banshees3WBoxScore
101 - 2020-12-30424As0Riverman2WBoxScore
103 - 2021-01-01433Riverman6Snipers3WBoxScore
105 - 2021-01-03440Banshees3Riverman5WBoxScore
106 - 2021-01-04443Riverman6Wolves2WBoxScore
108 - 2021-01-06452Pacifiques de la route2Riverman5WBoxScore
Trade Deadline --- Trades can’t be done after this day is simulated!
110 - 2021-01-08460Riverman4Ailes Rouges3WBoxScore
112 - 2021-01-10468Riverman3Chiefs2WBoxScore
113 - 2021-01-11471Harvard4Riverman3LXBoxScore
115 - 2021-01-13480Riverman6Canadiens3WBoxScore
116 - 2021-01-14485Wolves4Riverman5WBoxScore
118 - 2021-01-16495Ailes Rouges3Riverman2LBoxScore
119 - 2021-01-17501Riverman1Wolves4LBoxScore
120 - 2021-01-18507Riverman4Canadiens2WBoxScore
121 - 2021-01-19514Canadiens3Riverman1LBoxScore
122 - 2021-01-20523Croque-Morts6Riverman2LBoxScore
123 - 2021-01-21527Riverman6Banshees4WBoxScore
125 - 2021-01-23537Riverman6Banshees4WBoxScore
126 - 2021-01-24538Riverman4Pacifiques de la route3WBoxScore
127 - 2021-01-25545Snipers4Riverman1LBoxScore
129 - 2021-01-27554Pacifiques de la route4Riverman3LBoxScore
130 - 2021-01-28556Riverman4As3WBoxScore
134 - 2021-02-01571Pacifiques de la route3Riverman1LBoxScore



Arena Capacity - Ticket Price Attendance - %
Level 1Level 2
Capacity20001000
Ticket Price3515
Attendance00
Attendance PCT0.00%0.00%

Income
Home Games LeftAverage Attendance - %Average Income per GameYear to Date RevenueCapacityTeam Popularity
0 0 - 0.00% 0$0$3000100

Expenses
Year To Date ExpensesPlayers Total SalariesPlayers Total Average SalariesCoaches Salaries
1,459,222$ 1,748,500$ 1,708,500$ 0$
Salary Cap Per DaysSalary Cap To DatePlayers In Salary CapPlayers Out of Salary Cap
1,748,500$ 1,459,222$ 29 0

Estimate
Estimated Season RevenueRemaining Season DaysExpenses Per DaysEstimated Season Expenses
0$ 1 13,555$ 13,555$




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