´╗┐

Moose
GP: 81 | W: 48 | L: 26 | OTL: 7 | P: 103
GF: 279 | GA: 223 | PP%: 24.26% | PK%: 81.90%
GM : Trevor Sifton | Morale : 50 | Team Overall : 65
Next Games #1308 vs Canucks
Your browser screen resolution is too small for this page. Some information are hidden to keep the page readable.

Moose
48-26-7, 103pts
3
FINAL
1 Eagles
35-40-6, 76pts
Team Stats
W4StreakOTL1
28-10-2Home Record20-16-4
20-16-5Away Record15-24-2
8-2-0Last 10 Games3-5-2
3.443.30
2.753.72
24.26%17.39%
81.90%77.27%
Firebirds
53-25-3, 109pts
1
FINAL
2 Moose
48-26-7, 103pts
Team Stats
L2StreakW4
31-9-1Home Record28-10-2
22-16-2Away Record20-16-5
8-2-0Last 10 Games8-2-0
3.863.44
2.862.75
26.09%24.26%
77.95%81.90%
Canucks
64-13-4, 132pts
2024-04-18
Moose
48-26-7, 103pts
Team Stats
W5StreakW4
33-4-428-10-2
31-9-020-16-5
9-1-0Last 10 Games8-2-0
5.203.44
2.682.75
23.08%24.26%
85.48%81.90%
Lukas ReichelGoals
Lukas Reichel
59
Lane PedersonAssists
Lane Pederson
55
Lukas ReichelPoints
Lukas Reichel
104
Lukas ReichelPlus/Minus
Lukas Reichel
34
Joseph WollWins
Joseph Woll
42
Joseph WollSave Percentage
Joseph Woll
0.931

Team Stats

279
3.44 GFG
Shots For
2692
33.23 Avg

24.3%
33 GF

35.7%
Goals Against
223
2.75 GAA
Shots Against
3037
37.49 Avg

81.9%
21 GA

38.7%


General ManagerTrevor Sifton
Central Division
Western Conference
Declan Chisholm
Lukas Reichel




Arena Capacity5,000
Attendance5,000
5,000




20
19
39 / 55
Prospects25


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
1Lukas Reichel (R) (A)0XX100.00675197708466556443727355686868050760212925,000$
2Reese Johnson (R)24XX100.00915294718247655555666972626262050760242907,258$
3Lane Pederson (R)18X100.00825591728350555856677055646464050730253990,675$
4Axel Jonsson-Fjallby (R)0X100.00725197718347605840687060646464050730253813,750$
5Will Bitten (R)14X100.00526483555480934265596444532540050620242952,750$
6Chase De Leo58XXX100.00525884555865754265606444532540050610272840,000$
7Chris Wagner0XX100.00546181545473844165576441532540050600321775,000$
8Travis Barron0X100.00556279525375873836576439512540050600241925,000$
9Cole Fonstad (R)0X100.00525384555558614336596438542540050590232925,000$
10Mike Hardman (R)86XX100.00535282545558584236596440532540050590242952,750$
11Chase Pearson22X100.00535582525359683965576436512540050570252909,090$
12Stelio Mattheos (R)0X100.00526083515369803665566333502540050570243841,533$
13Ville Heinola (R)0X100.00705394717951556040696855646464050720222925,000$
14Declan Chisholm (R) (C)20X100.00525783565662724336626443542540050610231925,000$
15William Villeneuve (R)0X100.00535782545463734036606344522540050600212817,778$
16Matt Bartkowski0X100.00546381525276883736576336502540050590351750,000$
17Simon Lundmark (R)0X100.00525984525367773836586339512540050580222850,833$
18Mikko Kokkonen (R)0X100.00534882515358493736576337502540050570222846,667$
Scratches
TEAM AVERAGE100.0059568658626270454761654555364705063
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 SPAgeContractSalary Average
1Joseph Woll (R)100.0086655370807274818748842651050790243797,333$
2Nico Daws (R)100.0073656877767573767774762555050770222850,833$
Scratches
TEAM AVERAGE100.008065617478747479826180265305078
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
1Lukas ReichelMoose (WIN)LW/RW815945104342010210530510020819.34%52136116.813111429107314109971116.816921459121.53150008310
2Lane PedersonMoose (WIN)C814655101272021616133611223413.69%95154119.03415194311710179810119.03116424661001.3102000789
3Axel Jonsson-FjallbyMoose (WIN)LW815051101286011919033310322515.02%124153818.9913518461170112959318.99108229104011.3112000894
4Reese JohnsonMoose (WIN)C/RW71395493314022726334611421211.27%140153221.58731032941235787021.58946239134041.21050009114
5Ville HeinolaMoose (WIN)D56213556156098114223811089.42%126134624.042352073000263410.00%010886010.8300000542
6Will BittenMoose (WIN)C81102737-2116612088146245841524.08%62129616.00022211000014016.0082711142000.57003515011
7Mike HardmanMoose (WIN)LW/RW8182028-21609775229711453.49%42130116.0700000000001016.074111822000.4300000030
8Declan ChisholmMoose (WIN)D81617232048075766734338.96%85193623.911348106000080010.00%04154000.2400000112
9Chase De LeoMoose (WIN)C/LW/RW8171219312915576260183211.67%18119314.7320281040001190014.73891913000.3200210001
10Chris WagnerMoose (WIN)C/RW8161319246240694535132917.14%22139817.271234117000000117.2763121000.2700224002
11Travis BarronMoose (WIN)LW8191019-212551067113446916.72%37132016.30000000000131116.30475834000.2900001011
12Cole FonstadMoose (WIN)LW8151318740533110733784.67%107559.320000000000109.32315317000.4800000021
13William VilleneuveMoose (WIN)D812161820100671156635303.03%137176521.8003341150112102100.00%03186000.2000000001
14Simon LundmarkMoose (WIN)D8139122181032624427156.82%65128115.8200001100002110.00%02951000.1900101000
15Dan RenoufJetsD40281012271529352313148.70%4780720.19033251000050000.00%01530000.2500021001
16Stelio MattheosMoose (WIN)C811786282037323011223.33%47349.060000000000009.064801411000.2200022000
17Morgan GeekieJetsC/RW101784001220197205.26%1712712.7600000000000012.761131510001.2500000000
18Matt BartkowskiMoose (WIN)D6616726573554363719112.70%52131519.94000293000063100.00%02340000.1100322000
19Chase PearsonMoose (WIN)C811236202920144187.14%63213.960000500000003.967967000.1900000000
20Mikko KokkonenMoose (WIN)D81123-210044493919242.56%61130616.1300001000044000.00%02347000.0500000000
Team Total or Average1458278409687228512260161117082692944170110.33%12022418216.593350832001130551029815472050.16%40571593929180.57214111426384339
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
1Joseph WollMoose (WIN)71422270.9312.6142844118626821686010.6431471101376
2Nico DawsMoose (WIN)106400.9123.106002131353210010.00%01071221
Team Total or Average81482670.9292.6748856221730351896020.6431481811597


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 Clause Trade Block Force Waivers Contract Type Current Salary Salary RemainingSalary AverageSalary Ave 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
Axel Jonsson-FjallbyMoose (WIN)LW251998-02-10Yes194 Lbs6 ft1NoNoNo3Pro & Farm813,750$8,477$813,750$8,477$0$0$No813,750$813,750$Link / NHL Link
Chase De LeoMoose (WIN)C/LW/RW271995-10-25No185 Lbs5 ft9NoNoNo2Pro & Farm840,000$8,750$840,000$8,750$0$0$No840,000$Link / NHL Link
Chase PearsonMoose (WIN)C251997-08-23No202 Lbs6 ft3NoNoNo2Pro & Farm909,090$9,470$909,090$9,470$0$0$No909,090$Link / NHL Link
Chris WagnerMoose (WIN)C/RW321991-05-27No191 Lbs6 ft0NoNoNo1Pro & Farm775,000$8,073$775,000$8,073$0$0$NoLink / NHL Link
Cole FonstadMoose (WIN)LW232000-04-24Yes165 Lbs5 ft10NoNoNo2Pro & Farm925,000$9,635$925,000$9,635$0$0$No925,000$Link / NHL Link
Declan ChisholmMoose (WIN)D232000-01-12Yes185 Lbs6 ft1NoNoNo1Pro & Farm925,000$9,635$925,000$9,635$0$0$NoLink / NHL Link
Joseph WollMoose (WIN)G241998-07-12Yes203 Lbs6 ft4NoNoNo3Pro & Farm797,333$8,306$797,333$8,306$0$0$No797,333$797,333$Link / NHL Link
Lane PedersonMoose (WIN)C251997-08-04Yes190 Lbs6 ft0NoNoNo3Pro & Farm990,675$10,320$990,675$10,320$0$0$No990,675$990,675$Link / NHL Link
Lukas ReichelMoose (WIN)LW/RW212002-05-17Yes170 Lbs6 ft0NoNoNo2Pro & Farm925,000$9,635$925,000$9,635$0$0$No925,000$Link / NHL Link
Matt BartkowskiMoose (WIN)D351988-06-04No201 Lbs6 ft1NoNoNo1Pro & Farm750,000$7,812$750,000$7,812$0$0$NoLink / NHL Link
Mike HardmanMoose (WIN)LW/RW241999-02-05Yes205 Lbs6 ft2NoNoNo2Pro & Farm952,750$9,924$952,750$9,924$0$0$No952,750$Link / NHL Link
Mikko KokkonenMoose (WIN)D222001-01-18Yes198 Lbs6 ft2NoNoNo2Pro & Farm846,667$8,819$846,667$8,819$0$0$No846,667$Link / NHL Link
Nico DawsMoose (WIN)G222000-12-22Yes203 Lbs6 ft4NoNoNo2Pro & Farm850,833$8,863$850,833$8,863$0$0$No850,833$Link / NHL Link
Reese JohnsonMoose (WIN)C/RW241998-07-10Yes193 Lbs6 ft1NoNoNo2Pro & Farm907,258$9,451$907,258$9,451$0$0$No907,258$Link / NHL Link
Simon LundmarkMoose (WIN)D222000-10-08Yes201 Lbs6 ft2NoNoNo2Pro & Farm850,833$8,863$850,833$8,863$0$0$No850,833$Link / NHL Link
Stelio MattheosMoose (WIN)C241999-06-14Yes196 Lbs6 ft1NoNoNo3Pro & Farm841,533$8,766$841,533$8,766$0$0$No841,533$841,533$Link / NHL Link
Travis BarronMoose (WIN)LW241998-08-17No205 Lbs6 ft1NoNoNo1Pro & Farm925,000$9,635$925,000$9,635$0$0$NoLink / NHL Link
Ville HeinolaMoose (WIN)D222001-03-02Yes178 Lbs5 ft11NoNoNo2Pro & Farm925,000$9,635$925,000$9,635$0$0$No925,000$Link / NHL Link
Will BittenMoose (WIN)C241998-07-10Yes180 Lbs5 ft11NoNoNo2Pro & Farm952,750$9,924$952,750$9,924$0$0$No952,750$Link / NHL Link
William VilleneuveMoose (WIN)D212002-03-20Yes184 Lbs6 ft2NoNoNo2Pro & Farm817,778$8,519$817,778$8,519$0$0$No817,778$Link / NHL Link
Total PlayersAverage AgeAverage WeightAverage HeightAverage ContractAverage Year 1 Salary
2024.45191 Lbs6 ft12.00876,063$



5 vs 5 Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Lukas ReichelReese JohnsonChase De Leo30122
2Axel Jonsson-FjallbyLane PedersonChris Wagner30122
3Travis BarronWill BittenMike Hardman20122
4Cole FonstadStelio MattheosReese Johnson20122
5 vs 5 Defence
Line #DefenceDefenceTime %PHYDFOF
1Ville HeinolaDeclan Chisholm30122
2William VilleneuveMatt Bartkowski30122
3Simon LundmarkMikko Kokkonen20122
4Ville HeinolaDeclan Chisholm20122
Power Play Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Lukas ReichelReese JohnsonChase De Leo50122
2Axel Jonsson-FjallbyLane PedersonChris Wagner50122
Power Play Defence
Line #DefenceDefenceTime %PHYDFOF
1Ville HeinolaDeclan Chisholm50122
2William VilleneuveMatt Bartkowski50122
Penalty Kill 4 Players Forward
Line #CenterWingTime %PHYDFOF
1Reese JohnsonLukas Reichel50122
2Axel Jonsson-FjallbyLane Pederson50122
Penalty Kill 4 Players Defence
Line #DefenceDefenceTime %PHYDFOF
1Ville HeinolaDeclan Chisholm50122
2William VilleneuveMatt Bartkowski50122
Penalty Kill 3 Players
Line #WingTime %PHYDFOFDefenceDefenceTime %PHYDFOF
1Reese Johnson50122Ville HeinolaDeclan Chisholm50122
2Lukas Reichel50122William VilleneuveMatt Bartkowski50122
4 vs 4 Forward
Line #CenterWingTime %PHYDFOF
1Reese JohnsonLukas Reichel50122
2Axel Jonsson-FjallbyLane Pederson50122
4 vs 4 Defence
Line #DefenceDefenceTime %PHYDFOF
1Ville HeinolaDeclan Chisholm50122
2William VilleneuveMatt Bartkowski50122
Last Minute Offensive
Left WingCenterRight WingDefenceDefence
Lukas ReichelReese JohnsonChase De LeoVille HeinolaDeclan Chisholm
Last Minute Defensive
Left WingCenterRight WingDefenceDefence
Lukas ReichelReese JohnsonChase De LeoVille HeinolaDeclan Chisholm
Extra Forwards
Normal PowerPlayPenalty Kill
Chase Pearson, Will Bitten, Travis BarronChase Pearson, Will BittenTravis Barron
Extra Defencemen
Normal PowerPlayPenalty Kill
Simon Lundmark, Mikko Kokkonen, William VilleneuveSimon LundmarkMikko Kokkonen, William Villeneuve
Penalty Shots
Reese Johnson, Lukas Reichel, Axel Jonsson-Fjallby, Lane Pederson, Will Bitten
Goalie
#1 : Joseph Woll, #2 : Nico Daws
Custom OT Lines Forwards
Reese Johnson, Lukas Reichel, Axel Jonsson-Fjallby, Lane Pederson, Will Bitten, Chase De Leo, Chase De Leo, Travis Barron, Chris Wagner, Cole Fonstad, Mike Hardman
Custom OT Lines Defencemen
Ville Heinola, Declan Chisholm, William Villeneuve, Matt Bartkowski, Simon Lundmark


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
1Admirals440000002141722000000122102200000092781.00021315202971017661449029128583413647388711327.27%90100.00%0717143649.93%807155751.83%511103049.61%1693104818836711313643
2Americans210010001046100010003211100000072541.00010152500971017666290291285834863011386233.33%30100.00%0717143649.93%807155751.83%511103049.61%1693104818836711313643
3Barracuda321000007521010000012-12200000063340.66771118009710176683902912858341163711494125.00%30100.00%0717143649.93%807155751.83%511103049.61%1693104818836711313643
4Bears21000001440110000003211000000112-130.7504711009710176675902912858346032246300.00%10100.00%0717143649.93%807155751.83%511103049.61%1693104818836711313643
5Bruins22000000963110000006421100000032141.000915240097101766749029128583462188433133.33%4175.00%0717143649.93%807155751.83%511103049.61%1693104818836711313643
6Canucks21001000862000000000002100100086241.00081321009710176673902912858349014645300.00%30100.00%0717143649.93%807155751.83%511103049.61%1693104818836711313643
7Checkers2010100056-1100010002111010000035-220.50058130097101766599029128583474264453133.33%2150.00%0717143649.93%807155751.83%511103049.61%1693104818836711313643
8Comets20200000711-41010000057-21010000024-200.00071017009710176669902912858348947434000.00%2150.00%0717143649.93%807155751.83%511103049.61%1693104818836711313643
9Condors330000001248220000008261100000042261.0001219310097101766103902912858341236226487342.86%8187.50%1717143649.93%807155751.83%511103049.61%1693104818836711313643
10Crunch210000014311000000112-11100000031230.75045900971017666390291285834653611443133.33%3166.67%0717143649.93%807155751.83%511103049.61%1693104818836711313643
11Eagles320000011284110000005232100000176150.8331217290097101766104902912858341193616586466.67%80100.00%0717143649.93%807155751.83%511103049.61%1693104818836711313643
12Firebirds330000001266220000008441100000042261.000121931009710176610590291285834100422658225.00%110.00%0717143649.93%807155751.83%511103049.61%1693104818836711313643
13Griffins20200000310-71010000014-31010000026-400.00033600971017667490291285834743518403266.67%4250.00%0717143649.93%807155751.83%511103049.61%1693104818836711313643
14Gulls31200000711-41100000051420200000210-820.3337121900971017669990291285834110442455400.00%2150.00%0717143649.93%807155751.83%511103049.61%1693104818836711313643
15IceHogs42200000161422200000084420200000810-240.5001622381097101766119902912858341686337677114.29%11190.91%1717143649.93%807155751.83%511103049.61%1693104818836711313643
16Islanders2010000136-31010000024-21000000112-110.2503580097101766599029128583479281034600.00%000.00%0717143649.93%807155751.83%511103049.61%1693104818836711313643
17Marlies21100000880110000006421010000024-220.500810180097101766739029128583475221552200.00%000.00%0717143649.93%807155751.83%511103049.61%1693104818836711313643
18Monsters21100000954110000006151010000034-120.500913220097101766639029128583470391145700.00%3166.67%0717143649.93%807155751.83%511103049.61%1693104818836711313643
19Penguins2110000045-11010000014-31100000031220.50047110097101766579029128583466231143300.00%30100.00%0717143649.93%807155751.83%511103049.61%1693104818836711313643
20Phantoms220000001147110000003121100000083541.0001116270097101766749029128583464391740300.00%10100.00%0717143649.93%807155751.83%511103049.61%1693104818836711313643
21Reign320001001587210001009541100000063350.83315203500971017669390291285834984652655480.00%6183.33%0717143649.93%807155751.83%511103049.61%1693104818836711313643
22Roadrunners42200000990220000008442020000015-440.500914230097101766119902912858341375716757114.29%30100.00%0717143649.93%807155751.83%511103049.61%1693104818836711313643
23Rocket20000110440100000103211000010012-130.750437009710176687902912858347423438300.00%20100.00%1717143649.93%807155751.83%511103049.61%1693104818836711313643
24Senators2200000013211110000007161100000061541.0001317300097101766789029128583470291345100.00%4250.00%0717143649.93%807155751.83%511103049.61%1693104818836711313643
25Silver Knights312000001113-2211000006601010000057-220.333111627009710176697902912858341234021575360.00%30100.00%0717143649.93%807155751.83%511103049.61%1693104818836711313643
26Stars43100000161152110000078-12200000093660.75016203610971017661259029128583413453981200.00%20100.00%1717143649.93%807155751.83%511103049.61%1693104818836711313643
27Thunderbirds30300000511-62020000035-21010000026-400.0005611009710176698902912858341134817663133.33%6266.67%0717143649.93%807155751.83%511103049.61%1693104818836711313643
28Wild412010001318-52100100097220200000411-740.5001322350097101766140902912858341696559695120.00%9277.78%1717143649.93%807155751.83%511103049.61%1693104818836711313643
29Wolf Pack2010010057-21010000012-11000010045-110.250561100971017666090291285834905326384125.00%3166.67%0717143649.93%807155751.83%511103049.61%1693104818836711313643
30Wolves2110000035-2110000002111010000014-320.500369009710176657902912858348333637300.00%3166.67%0717143649.93%807155751.83%511103049.61%1693104818836711313643
31Wranglers330000001358110000005322200000082661.0001321340097101766106902912858341203513626116.67%4175.00%0717143649.93%807155751.83%511103049.61%1693104818836711313643
Total81432604314279223564024100311114697494119160120313312671030.63627940968822971017662692902912858343037120251816111363324.26%1162181.90%5717143649.93%807155751.83%511103049.61%1693104818836711313643
_Since Last GM Reset81432604314279223564024100311114697494119160120313312671030.63627940968822971017662692902912858343037120251816111363324.26%1162181.90%5717143649.93%807155751.83%511103049.61%1693104818836711313643
_Vs Conference493015021011771334424175011009455392513100100183785660.67317726344022971017661608902912858341856689347949832530.12%781087.18%4717143649.93%807155751.83%511103049.61%1693104818836711313643
_Vs Division261410010019275171393010005232201357000014043-3310.59692132224229710176684990291285834976369192503411126.83%48589.58%3717143649.93%807155751.83%511103049.61%1693104818836711313643

Total For Players
Games PlayedPointsStreakGoalsAssistsPointsShots ForShots AgainstShots BlockedPenalty MinutesHitsEmpty Net GoalsShutouts
81103W4279409688269230371202518161122
All Games
GPWLOTWOTL SOWSOLGFGA
8143264314279223
Home Games
GPWLOTWOTL SOWSOLGFGA
402410311114697
Visitor Games
GPWLOTWOTL SOWSOLGFGA
4119161203133126
Last 10 Games
WLOTWOTL SOWSOL
820000
Power Play AttempsPower Play GoalsPower Play %Penalty Kill AttempsPenalty Kill Goals AgainstPenalty Kill %Penalty Kill Goals For
1363324.26%1162181.90%5
Shots 1 PeriodShots 2 PeriodShots 3 PeriodShots 4+ PeriodGoals 1 PeriodGoals 2 PeriodGoals 3 PeriodGoals 4+ Period
9029128583497101766
Face Offs
Won Offensive ZoneTotal OffensiveWon Offensive %Won Defensif ZoneTotal DefensiveWon Defensive %Won Neutral ZoneTotal NeutralWon Neutral %
717143649.93%807155751.83%511103049.61%
Puck Time
In Offensive ZoneControl In Offensive ZoneIn Defensive ZoneControl In Defensive ZoneIn Neutral ZoneControl In Neutral Zone
1693104818836711313643


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 Visiting Team Score Home Team Score ST OT SO RI Link
2 - 2023-10-119Moose4Wranglers1AWBoxScore
5 - 2023-10-1420Checkers1Moose2BWXBoxScore
8 - 2023-10-1745Reign4Moose3BLXBoxScore
10 - 2023-10-1958Silver Knights3Moose5BWBoxScore
12 - 2023-10-2178Moose4Condors2AWBoxScore
15 - 2023-10-2493Thunderbirds3Moose2BLBoxScore
17 - 2023-10-26102Moose2Griffins6ALBoxScore
19 - 2023-10-28122Moose1Rocket2ALXBoxScore
21 - 2023-10-30134Wolf Pack2Moose1BLBoxScore
24 - 2023-11-02155Moose5Silver Knights7ALBoxScore
26 - 2023-11-04160Moose1Roadrunners2ALBoxScore
29 - 2023-11-07184Moose2Thunderbirds6ALBoxScore
31 - 2023-11-09200Admirals0Moose7BWBoxScore
33 - 2023-11-11211Stars3Moose4BWBoxScore
36 - 2023-11-14236Comets7Moose5BLBoxScore
39 - 2023-11-17252Americans2Moose3BWXBoxScore
40 - 2023-11-18259Roadrunners1Moose3BWBoxScore
44 - 2023-11-22284Moose3Crunch1AWBoxScore
46 - 2023-11-24304Moose3Checkers5ALBoxScore
48 - 2023-11-26319Moose5Admirals2AWBoxScore
50 - 2023-11-28332Stars5Moose3BLBoxScore
52 - 2023-11-30349Condors1Moose3BWBoxScore
54 - 2023-12-02357IceHogs2Moose5BWBoxScore
56 - 2023-12-04376Wolves1Moose2BWBoxScore
59 - 2023-12-07402Moose4Eagles5ALXXBoxScore
62 - 2023-12-10425Moose1Gulls5ALBoxScore
64 - 2023-12-12441Moose3Barracuda1AWBoxScore
65 - 2023-12-13446Moose6Reign3AWBoxScore
68 - 2023-12-16462Eagles2Moose5BWBoxScore
70 - 2023-12-18481Rocket2Moose3BWXXBoxScore
72 - 2023-12-20495Griffins4Moose1BLBoxScore
74 - 2023-12-22512Bruins4Moose6BWBoxScore
79 - 2023-12-27538Moose4IceHogs5ALBoxScore
82 - 2023-12-30555Wild4Moose5BWBoxScore
83 - 2023-12-31564Moose1Wild7ALBoxScore
85 - 2024-01-02580Crunch2Moose1BLXXBoxScore
87 - 2024-01-04601Moose3Barracuda2AWBoxScore
88 - 2024-01-05604Moose1Gulls5ALBoxScore
90 - 2024-01-07619Moose0Roadrunners3ALBoxScore
92 - 2024-01-09631Monsters1Moose6BWBoxScore
94 - 2024-01-11648IceHogs2Moose3BWBoxScore
96 - 2024-01-13657Phantoms1Moose3BWBoxScore
99 - 2024-01-16685Islanders4Moose2BLBoxScore
103 - 2024-01-20709Moose6Senators1AWBoxScore
105 - 2024-01-22724Moose3Bruins2AWBoxScore
107 - 2024-01-24740Moose2Marlies4ALBoxScore
110 - 2024-01-27763Marlies4Moose6BWBoxScore
120 - 2024-02-06788Moose3Penguins1AWBoxScore
122 - 2024-02-08797Moose8Phantoms3AWBoxScore
124 - 2024-02-10810Penguins4Moose1BLBoxScore
128 - 2024-02-14834Barracuda2Moose1BLBoxScore
131 - 2024-02-17860Moose4Canucks3AWBoxScore
133 - 2024-02-19873Moose4Wranglers1AWBoxScore
134 - 2024-02-20880Wild3Moose4BWXBoxScore
137 - 2024-02-23901Moose4IceHogs5ALBoxScore
139 - 2024-02-25919Roadrunners3Moose5BWBoxScore
141 - 2024-02-27934Thunderbirds2Moose1BLBoxScore
143 - 2024-02-29947Moose3Stars1AWBoxScore
145 - 2024-03-02956Moose1Wolves4ALBoxScore
146 - 2024-03-03972Moose7Americans2AWBoxScore
148 - 2024-03-05986Firebirds3Moose6BWBoxScore
151 - 2024-03-081008Moose4Firebirds2AWBoxScore
152 - 2024-03-091019Moose4Canucks3AWXBoxScore
154 - 2024-03-111029Bears2Moose3BWBoxScore
156 - 2024-03-131042Admirals2Moose5BWBoxScore
158 - 2024-03-151057Gulls1Moose5BWBoxScore
160 - 2024-03-171076Moose3Monsters4ALBoxScore
162 - 2024-03-191085Moose4Wolf Pack5ALXBoxScore
164 - 2024-03-211102Moose2Comets4ALBoxScore
166 - 2024-03-231113Moose1Islanders2ALXXBoxScore
167 - 2024-03-241124Moose1Bears2ALXXBoxScore
169 - 2024-03-261142Condors1Moose5BWBoxScore
171 - 2024-03-281158Silver Knights3Moose1BLBoxScore
173 - 2024-03-301170Senators1Moose7BWBoxScore
175 - 2024-04-011187Reign1Moose6BWBoxScore
178 - 2024-04-041209Wranglers3Moose5BWBoxScore
180 - 2024-04-061219Moose3Wild4ALBoxScore
183 - 2024-04-091247Moose4Admirals0AWBoxScore
185 - 2024-04-111262Moose6Stars2AWBoxScore
187 - 2024-04-131272Moose3Eagles1AWBoxScore
190 - 2024-04-161300Firebirds1Moose2BWBoxScore
192 - 2024-04-181308Canucks-Moose-



Arena Capacity - Ticket Price Attendance - %
Level 1Level 2
Arena Capacity35001500
Ticket Price5025
Attendance140,00060,000
Attendance PCT100.00%100.00%

Income
Home Games LeftAverage Attendance - %Average Income per GameYear to Date RevenueArena CapacityTeam Popularity
1 5000 - 100.00% 108,375$4,335,000$5000100

Expenses
Year To Date ExpensesPlayers Total SalariesPlayers Total Average SalariesCoaches Salaries
17,298,503$ 17,521,250$ 17,521,250$ 0$
Salary Cap Per DaysSalary Cap To DatePlayers In Salary CapPlayers Out of Salary Cap
91,257$ 17,298,503$ 0 0

Estimate
Estimated Season RevenueRemaining Season DaysExpenses Per DaysEstimated Season Expenses
108,375$ 2 91,257$ 182,514$




Moose

# Player Name GP G A P +/- PIM HIT HTT SHT SHT% SB MP AMG PPG PPA PPP PPS PKG PKA PKP PKS GW GT FO% HT P/20 PSG PSS
1Lane Pederson2451892574461601853131290820.81%183504820.6127477410779162622751.31%171.77512
2Sebastien Aho1641951653601684917413455335.26%143356621.75292453827613191340.00%232.0212
3Mike Hardman245851722571004236717561513.82%82412416.841020303513458242.46%51.2500
4Morgan Geekie921021312331361813511028236.17%59168818.351123343240469253.12%152.7601
5Chase De Leo2026416623019424924121926124.52%80336116.64522272623564457.02%21.3736

Moose

# Goalie Name GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA
1Beck Warm75541730.8055.2543810538319681088610.72711
2Nico Daws92464150.9053.32555110330732231865420.70634
3Joseph Woll71422270.9312.6142844118626821686010.64314
4Sam Montembeault11000.7317.00600072612000.0000

Moose

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
Regular Season
20218254180423178941837141307001214302082224124110411035921014912578912912080170345261176251708268827902166872165614842059747.32%2545976.77%25668122454.58%648122352.98%999178955.84%1784114218955961263660
202282333704233270280-10412016021021391281141132102131131152-218527046073012998975142696943885852502871102434916111764324.43%1714076.61%10607136644.44%728156246.61%464106343.65%1719104818936771344670
2023814326043142792235640241003111146974941191601203133126710327940968822971017662692902912858343037120251816111363324.26%1162181.90%5717143649.93%807155751.83%511103049.61%1693104818836711313643
Total Regular Season2451308101277813389214171227433053347154332821235648074446234881353131338216034984111965354121967905184526232592874807430982523470651717333.46%54112077.82%401992402649.48%2183434250.28%1974388250.85%519732395673194639211974
Playoff
20211156000008576953200000453114624000004045-51085136221100422814321010611992375165152142321546.88%21576.19%29717655.11%11417365.90%13824257.02%2371562588016484
Total Playoff1156000008576953200000453114624000004045-51085136221100422814321010611992375165152142321546.88%21576.19%29717655.11%11417365.90%13824257.02%2371562588016484

Moose

# Player Name GP G A P +/- PIM HIT HTT SHT SHT% SB MP AMG PPG PPA PPP PPS PKG PKA PKP PKS GW GT FO% HT P/20 PSG PSS
1Lane Pederson11191736-1011186330.16%1425222.956391901113050.00%42.8500
2Chase De Leo111117282421253828.95%1425723.38257410140059.84%02.1800
3Sebastien Aho11819271726122334.78%1017015.5101100000000.00%03.1600
4Morgan Geekie11141125425163441.18%1521719.76347601101254.93%12.3000
5Eetu Luostarinen11817252016202729.63%622120.17055710110069.23%02.2500

Moose

# Goalie Name GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA
1Beck Warm115600.7996.836590075374208410.0000