Out of Date Version of the STHS! Please update your version!
Login

Phantoms
GP: 80 | W: 38 | L: 33 | OTL: 9 | P: 85
GF: 344 | GA: 333 | PP%: 21.92% | PK%: 79.36%
GM : Simon DeChamplain | Morale : 31 | Team Overall : 65
Your browser screen resolution is too small for this page. Some information are hidden to keep the page readable.

Game Center
Admirals
34-42-4, 72pts
4
FINAL
3 Phantoms
38-33-9, 85pts
Team Stats
L3StreakL3
17-19-4Home Record16-19-5
17-23-0Away Record22-14-4
3-6-1Last 10 Games5-5-0
3.83Goals Per Game4.30
4.45Goals Against Per Game4.16
24.11%Power Play Percentage21.92%
75.09%Penalty Kill Percentage79.36%
Heat
42-33-5, 89pts
4
FINAL
1 Phantoms
38-33-9, 85pts
Team Stats
W1StreakL3
22-15-3Home Record16-19-5
20-18-2Away Record22-14-4
5-3-2Last 10 Games5-5-0
4.06Goals Per Game4.30
4.05Goals Against Per Game4.16
26.77%Power Play Percentage21.92%
76.83%Penalty Kill Percentage79.36%
Team Leaders
Goals
Michael Bournival
53
Assists
Nick Shore
71
Points
Alex DeBrincat
114
Plus/Minus
Nick Shore
18
Wins
Anton Forsberg
32
Save Percentage
Zachary Fucale
0.879

Team Stats
Goals For
344
4.30 GFG
Shots For
2768
34.60 Avg
Power Play Percentage
21.9%
73 GF
Offensive Zone Start
36.7%
Goals Against
333
4.16 GAA
Shots Against
2616
32.70 Avg
Penalty Kill Percentage
79.4%%
71 GA
Defensive Zone Start
36.5%
Team Info

General ManagerSimon DeChamplain
CoachKevin Dineen
DivisionFritz-Kraatz
ConferenceRobert-Lebel
CaptainDave Bolland
Assistant #1
Assistant #2


Arena Info

Capacity3,000
Attendance2,452
Season Tickets300


Roster Info

Pro Team34
Farm Team20
Contract Limit54 / 250
Prospects0


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
1Michael BournivalX100.007939797677757475716879717674603734730251995,000$
2Alex DeBrincat (R)X100.007754867877707769747475617851447156710201500,000$
3Sven Andrighetto (R)X100.007934816980747169746679607357514455700242700,000$
4Nick ShoreX100.005827737172757075837475555958593535690251850,000$
5Joe Snively (R)X100.006333818758725775717171508343466751680212500,000$
6Cristoval Nieves (R)X100.006926777667707573767969557048504243680231600,000$
7Lucas Wallmarkk (R)X100.007238736865736474727667666544445339680213700,000$
8Morgan Klimchuk (R)X100.006732727271757569667270707647444551680222650,000$
9Erik Nystrom (R)X100.007023756973706771656372677550483551670241600,000$
10David Kampf (R)X100.005943836671716972666774566644475051660224700,000$
11Brendan Leipsic (R)X100.005033706666656265747172556347494028640231500,000$
12Nick Sorensen (R)X100.005933787469666965635672527348494540640232525,000$
13Laurent Dauphin (R)X100.007340796169637070607163506744444344630222500,000$
14JC Lipon (R)X100.007156696966516867685762525749503851620241450,000$
15Anthony Angello (R)X100.004938806363746555656561575343434544600212450,000$
16A.J. Greer (R)X100.006043616769627258595962525245444444590214250,000$
17Brett Murray (R)X100.007639626776546558445563544241416450580191500,000$
18Reid McNeillX100.007647797378658275596857726871513652710251975,000$
19Blake Heinrich (R)X100.007034717273746258497268795454464435690222500,000$
20Brenden KichtonX100.006730787168706865565960736357583234670251750,000$
21Rinat Valiev (R)X100.007334807267686273546560696248465151670222500,000$
22Cal Foote (R)X100.008047646480845357336452695043418251660192500,000$
23Mikko Lehtonen (R)X100.006941766152667074506871586149504552650231500,000$
24Matt Kiersted (R)X100.006446636165555455415543574941415922570191500,000$
25Riley Stillman (R)X100.006741625961566152355751554541416222570191500,000$
Scratches
1Cooper Marody (R)X100.004335706251596160727256384745434920560214250,000$
2Fabian Zetterlund (R)X100.004535685362645654554568415840406920540182500,000$
3Devon Teows (R)X100.007347747066646270526455725449504639670233700,000$
4Victor Berglund (R)X100.006126655761514743285230662840407120550182500,000$
TEAM AVERAGE100.00663873686867666560656460614947504164
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
1Anton Forsberg100.00757473777279767272767469713750740251975,000$
2Zachary Fucale100.00667759687074737578745948464651710222500,000$
Scratches
1Jason Kasdorf100.00676778656470687067696653533720670251750,000$
2Kevin Lankinen (R)100.00676564676369596963635541416815630221500,000$
3Zachary Sawchenko (R)100.00605368515062664645717344466020560202500,000$
TEAM AVERAGE100.0067676866647168666571655151503166
Coaches Name PH DF OF PD EX LD PO CNT Age Contract Salary
Kevin Dineen73656679327257Can494500,000$


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
1Alex DeBrincatPhantoms (Phi)RW80466811412291510210631410218114.65%45183322.921828465527500092945047.92%2408420101.243101025311
2Nick ShorePhantoms (Phi)C68387110918875941062609517914.62%30141620.839283735236202131083555.41%20974024001.5414000294
3Michael BournivalPhantoms (Phi)LW715352105230013112331711619416.72%58166123.411623395224500072425050.57%5266337041.26180001043
4Joe SnivelyPhantoms (Phi)C80244266334068822158512911.16%17103012.89347161140001221347.34%6955311001.2814000304
5Cristoval NievesPhantoms (Phi)C78234063-133008771184599012.50%1792411.85291111640001123251.37%6563815001.3600000323
6Morgan KlimchukPhantoms (Phi)LW802339629540951052135511110.80%27129016.133710182190001213151.02%494616000.9612000144
7Sven AndrighettoPhantoms (Phi)RW80263056143010128901714712215.20%23142817.864481622101181613245.54%1123726010.7837101331
8Lucas WallmarkkPhantoms (Phi)C7724285272806676133439718.05%187669.95235582000092046.23%491198001.3600000141
9Reid McNeillPhantoms (Phi)D79730371471511514311558636.09%107209426.515813262970003305100.00%03466000.3500111011
10Erik NystromPhantoms (Phi)LW79151833-1528086711415210310.64%3287511.08011222000053056.76%372620000.7500000330
11Blake HeinrichPhantoms (Phi)D717233016981010112411537396.09%99158822.37347202150004211210.00%02850000.3800101021
12Brendan LeipsicPhantoms (Phi)LW7014132711602024100265214.00%95197.42000000000251066.67%12126001.0400000102
13Nick SorensenPhantoms (Phi)RW7471825-1416034487525439.33%1578310.5801108000000048.00%25188000.6400000002
14Jake DotchinFlyersD21516212200264642152011.90%3956526.933471179000090010.00%0821000.7400000100
15Devon TeowsPhantoms (Phi)D6831518-1034078916022235.00%63126918.6722441530113177000.00%01644000.2800000000
16Brenden KichtonPhantoms (Phi)D715111610200447545212311.11%5196413.58000073011275000.00%0332000.3300000001
17David KampfPhantoms (Phi)C807916-1008164392816.28%112583.23000090001101037.23%9490001.2400000003
18Rinat ValievPhantoms (Phi)D8001515-620059765720330.00%62125815.7402231160002118000.00%01132000.2400000000
19Ivan ProvorovFlyersD173111438025323612138.33%2445226.642241175000059000.00%01016000.6200000110
20Cal FootePhantoms (Phi)D8001414432042543013160.00%366878.5900005000032000.00%0122000.4100000001
21JC LiponPhantoms (Phi)RW8057128300901950204810.00%106287.8600008000001037.50%879000.3800000001
22Mikko LehtonenPhantoms (Phi)D801675235262828763.57%175466.8400001000028000.00%0413000.2600001000
23A.J. GreerPhantoms (Phi)LW75213940171182725.00%21962.63000000000940045.45%1111000.3000000010
24Brett MurrayPhantoms (Phi)LW7812321609671314.29%2921.1800004000000133.33%303000.6501000000
25Laurent DauphinPhantoms (Phi)C76202-1403030266.67%1550.7310119000001028.57%701000.7200000000
26Anthony AngelloPhantoms (Phi)C75011-100332110.00%01341.79000030002960040.43%4701000.1500000000
27Matt KierstedPhantoms (Phi)D50000-16011131310.00%92064.140000000006000.00%003000.00%00000000
28Riley StillmanPhantoms (Phi)D31000280313020.00%1912.940000200007000.00%003000.00%00000000
Team Total or Average19493415809216675260157116402768946162912.32%8252362312.12731302032862549235572220351651.23%5110568508150.781036416343743
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
1Anton ForsbergPhantoms (Phi)73322280.8754.073818602592076998400.581317010222
2Zachary FucalePhantoms (Phi)2861110.8793.8110240165538272120.50081070101
Team Total or Average101383390.8764.014843613242614127052398080323


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
A.J. GreerPhantoms (Phi)LW211996-01-01Yes210 Lbs6 ft3NoNoNo4Pro & Farm250,000$0$0$No300,000$350,000$400,000$Link
Alex DeBrincatPhantoms (Phi)RW201997-01-01Yes165 Lbs5 ft7NoNoNo1Pro & Farm500,000$0$0$NoLink
Anthony AngelloPhantoms (Phi)C211996-01-01Yes210 Lbs6 ft5NoNoNo2Pro & Farm450,000$0$0$No450,000$Link
Anton ForsbergPhantoms (Phi)G251992-01-01No191 Lbs6 ft3NoNoNo1Pro & Farm975,000$0$0$No
Blake HeinrichPhantoms (Phi)D221995-01-01Yes185 Lbs5 ft11NoNoNo2Pro & Farm500,000$0$0$No500,000$Link
Brendan LeipsicPhantoms (Phi)LW231994-01-01Yes165 Lbs5 ft8NoNoNo1Pro & Farm500,000$0$0$NoLink
Brenden KichtonPhantoms (Phi)D251992-01-01No185 Lbs5 ft10NoNoNo1Pro & Farm750,000$0$0$No
Brett MurrayPhantoms (Phi)LW191998-01-01Yes216 Lbs6 ft4NoNoNo1Pro & Farm500,000$0$0$NoLink
Cal FootePhantoms (Phi)D191998-01-01Yes227 Lbs6 ft4NoNoNo2Pro & Farm500,000$0$0$No500,000$Link
Cooper MarodyPhantoms (Phi)C211996-01-01Yes184 Lbs6 ft0NoNoNo4Pro & Farm250,000$0$0$No300,000$350,000$400,000$Link
Cristoval NievesPhantoms (Phi)C231994-01-01Yes192 Lbs6 ft2NoNoNo1Pro & Farm600,000$0$0$NoLink
David KampfPhantoms (Phi)C221995-01-01Yes188 Lbs6 ft2NoNoNo4Pro & Farm700,000$0$0$No750,000$800,000$900,000$Link
Devon TeowsPhantoms (Phi)D231994-01-01Yes191 Lbs5 ft11NoNoNo3Pro & Farm700,000$0$0$No800,000$900,000$Link
Erik NystromPhantoms (Phi)LW241993-01-01Yes176 Lbs5 ft11NoNoNo1Pro & Farm600,000$0$0$NoLink
Fabian ZetterlundPhantoms (Phi)LW181999-01-01Yes220 Lbs5 ft11NoNoNo2Pro & Farm500,000$0$0$No500,000$Link
JC LiponPhantoms (Phi)RW241993-01-01Yes185 Lbs6 ft0NoNoNo1Pro & Farm450,000$0$0$NoLink
Jason KasdorfPhantoms (Phi)G251992-01-01No172 Lbs6 ft3NoNoNo1Pro & Farm750,000$0$0$No
Joe SnivelyPhantoms (Phi)C211996-01-01Yes176 Lbs5 ft9NoNoNo2Pro & Farm500,000$0$0$No500,000$Link
Kevin LankinenPhantoms (Phi)G221995-01-01Yes185 Lbs6 ft2NoNoNo1Pro & Farm500,000$0$0$NoLink
Laurent DauphinPhantoms (Phi)C221995-01-01Yes185 Lbs6 ft0NoNoNo2Pro & Farm500,000$0$0$No500,000$Link
Lucas WallmarkkPhantoms (Phi)C211996-01-01Yes178 Lbs6 ft0NoNoNo3Pro & Farm700,000$0$0$No800,000$900,000$
Matt KierstedPhantoms (Phi)D191998-01-01Yes184 Lbs5 ft11NoNoNo1Pro & Farm500,000$0$0$NoLink
Michael BournivalPhantoms (Phi)LW251992-01-01No195 Lbs5 ft11NoNoNo1Pro & Farm995,000$0$0$No
Mikko LehtonenPhantoms (Phi)D231994-01-01Yes196 Lbs6 ft0NoNoNo1Pro & Farm500,000$0$0$NoLink
Morgan KlimchukPhantoms (Phi)LW221995-01-01Yes185 Lbs5 ft11NoNoNo2Pro & Farm650,000$0$0$No650,000$Link
Nick ShorePhantoms (Phi)C251992-01-01No194 Lbs6 ft1NoNoNo1Pro & Farm850,000$0$0$No
Nick SorensenPhantoms (Phi)RW231994-01-01Yes185 Lbs6 ft1NoNoNo2Pro & Farm525,000$0$0$No525,000$Link
Reid McNeillPhantoms (Phi)D251992-01-01No210 Lbs6 ft3NoNoNo1Pro & Farm975,000$0$0$No
Riley StillmanPhantoms (Phi)D191998-01-01Yes196 Lbs6 ft1NoNoNo1Pro & Farm500,000$0$0$NoLink
Rinat ValievPhantoms (Phi)D221995-01-01Yes185 Lbs6 ft1NoNoNo2Pro & Farm500,000$0$0$No500,000$Link
Sven AndrighettoPhantoms (Phi)RW241993-01-01Yes185 Lbs5 ft10NoNoNo2Pro & Farm700,000$0$0$No700,000$Link
Victor BerglundPhantoms (Phi)D181999-01-01Yes183 Lbs6 ft1NoNoNo2Pro & Farm500,000$0$0$No500,000$Link
Zachary FucalePhantoms (Phi)G221995-01-01No185 Lbs6 ft1NoNoNo2Pro & Farm500,000$0$0$No500,000$Link
Zachary SawchenkoPhantoms (Phi)G201997-01-01Yes185 Lbs6 ft1NoNoNo2Pro & Farm500,000$0$0$No500,000$Link
Total PlayersAverage AgeAverage WeightAverage HeightAverage ContractAverage Year 1 Salary
3422.00190 Lbs6 ft01.76584,412$



5 vs 5 Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Michael BournivalNick ShoreAlex DeBrincat40122
2Morgan KlimchukLucas WallmarkkSven Andrighetto30122
3Erik NystromCristoval NievesNick Sorensen20122
4Brendan LeipsicJoe SnivelyJC Lipon10122
5 vs 5 Defense
Line #DefenseDefenseTime %PHYDFOF
1Reid McNeillBlake Heinrich40122
2Rinat ValievBrenden Kichton30122
3Cal FooteMikko Lehtonen20122
4Matt KierstedRiley Stillman10122
Power Play Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Michael BournivalNick ShoreAlex DeBrincat60122
2Morgan KlimchukLucas WallmarkkSven Andrighetto40122
Power Play Defense
Line #DefenseDefenseTime %PHYDFOF
1Reid McNeillBlake Heinrich60122
2Rinat ValievBrenden Kichton40122
Penalty Kill 4 Players Forward
Line #CenterWingTime %PHYDFOF
1Michael BournivalAlex DeBrincat60122
2Sven AndrighettoNick Shore40122
Penalty Kill 4 Players Defense
Line #DefenseDefenseTime %PHYDFOF
1Reid McNeillBlake Heinrich60122
2Rinat ValievBrenden Kichton40122
Penalty Kill 3 Players
Line #WingTime %PHYDFOFDefenseDefenseTime %PHYDFOF
1Michael Bournival60122Reid McNeillBlake Heinrich60122
2Alex DeBrincat40122Rinat ValievBrenden Kichton40122
4 vs 4 Forward
Line #CenterWingTime %PHYDFOF
1Michael BournivalAlex DeBrincat60122
2Sven AndrighettoNick Shore40122
4 vs 4 Defense
Line #DefenseDefenseTime %PHYDFOF
1Reid McNeillBlake Heinrich60122
2Rinat ValievBrenden Kichton40122
Last Minutes Offensive
Left WingCenterRight WingDefenseDefense
Michael BournivalNick ShoreAlex DeBrincatReid McNeillBlake Heinrich
Last Minutes Defensive
Left WingCenterRight WingDefenseDefense
Michael BournivalNick ShoreAlex DeBrincatReid McNeillBlake Heinrich
Extra Forwards
Normal PowerPlayPenalty Kill
David Kampf, Laurent Dauphin, Anthony AngelloDavid Kampf, Laurent DauphinAnthony Angello
Extra Defensemen
Normal PowerPlayPenalty Kill
Cal Foote, Mikko Lehtonen, Matt KierstedCal FooteMikko Lehtonen, Matt Kiersted
Penalty Shots
Michael Bournival, Alex DeBrincat, Sven Andrighetto, Nick Shore, Lucas Wallmarkk
Goalie
#1 : Zachary Fucale, #2 : Anton Forsberg


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
1Admirals31100001131302010000168-21100000075230.500132437009014310711121962936858488536316312325.00%10460.00%0980187352.32%934186750.03%704137051.39%173699416927551422702
2Barracuda30300000915-62020000068-21010000037-400.00091726009014310711114962936858489325326110440.00%16475.00%0980187352.32%934186750.03%704137051.39%173699416927551422702
3Bears211000009811010000024-21100000074320.500915240090143107116896293685848772816335240.00%8362.50%0980187352.32%934186750.03%704137051.39%173699416927551422702
4Comets742000012728-1311000011113-2431000001615190.64327457210901431071124296293685848239775411927414.81%26869.23%0980187352.32%934186750.03%704137051.39%173699416927551422702
5Condors31000101141312100000110821000010045-140.66714223600901431071197962936858489525225815426.67%11281.82%0980187352.32%934186750.03%704137051.39%173699416927551422702
6Crunch211000008711010000035-21100000052320.500813210090143107117796293685848582426425360.00%13284.62%0980187352.32%934186750.03%704137051.39%173699416927551422702
7Devils21000010853100000103211100000053241.00081321009014310711659629368584861162238500.00%110100.00%0980187352.32%934186750.03%704137051.39%173699416927551422702
8Eagles32100000191362110000012841100000075240.6671936550090143107111069629368584810433275510550.00%11190.91%0980187352.32%934186750.03%704137051.39%173699416927551422702
9Griffins312000001112-1211000009811010000024-220.3331121320090143107111099629368584810636287910220.00%14378.57%0980187352.32%934186750.03%704137051.39%173699416927551422702
10Heat623000102429-530200010915-6321000001514160.50024355900901431071117696293685848194668213135720.00%411173.17%0980187352.32%934186750.03%704137051.39%173699416927551422702
11Icehogs32100000161241010000036-322000000136740.66716284400901431071110296293685848943428618225.00%14471.43%0980187352.32%934186750.03%704137051.39%173699416927551422702
12Little Stars31100001811-3210000015321010000038-530.5008142200901431071110096293685848100402650800.00%13284.62%0980187352.32%934186750.03%704137051.39%173699416927551422702
13Marlies72300101302913110000115141412001001515060.42930477700901431071123696293685848197759112839820.51%33584.85%1980187352.32%934186750.03%704137051.39%173699416927551422702
14Monsters3300000014682200000010461100000042261.000142640009014310711107962936858488232336211436.36%13192.31%1980187352.32%934186750.03%704137051.39%173699416927551422702
15Moose31200000151501010000046-221100000119220.333152540009014310711111962936858489931235711436.36%9188.89%0980187352.32%934186750.03%704137051.39%173699416927551422702
16Penguins20200000511-61010000048-41010000013-200.0005813009014310711619629368584880201631400.00%8275.00%0980187352.32%934186750.03%704137051.39%173699416927551422702
17Punishers211000009901010000036-31100000063320.500913220090143107116696293685848812128466116.67%9188.89%0980187352.32%934186750.03%704137051.39%173699416927551422702
18Rampage20200000510-51010000036-31010000024-200.000591400901431071166962936858486016184410220.00%9188.89%0980187352.32%934186750.03%704137051.39%173699416927551422702
19Reign65100000312293210000015132330000001697100.83331538411901431071120496293685848190545213231722.58%26580.77%0980187352.32%934186750.03%704137051.39%173699416927551422702
20Rocket31200000151321100000061520200000912-320.333152439009014310711110962936858481081912511516.67%6266.67%0980187352.32%934186750.03%704137051.39%173699416927551422702
21Senators311000011113-21010000024-22100000199030.5001120310090143107111079629368584810628247216212.50%12283.33%0980187352.32%934186750.03%704137051.39%173699416927551422702
22Sound Tigers210010001073100010004311100000064241.0001017270090143107116496293685848681716409222.22%8187.50%0980187352.32%934186750.03%704137051.39%173699416927551422702
23Thunderbirds20200000611-51010000045-11010000026-400.0006111700901431071172962936858486424829700.00%4175.00%0980187352.32%934186750.03%704137051.39%173699416927551422702
24Wolfpack301000111214-2100000106512010000169-330.5001221330090143107111129629368584810530245212433.33%12375.00%0980187352.32%934186750.03%704137051.39%173699416927551422702
25Wolves220000001578110000007431100000083541.00015233800901431071175962936858487018193712216.67%7271.43%0980187352.32%934186750.03%704137051.39%173699416927551422702
Total803433012373443331140121901035162167-54022140020218216616850.531344580924219014310711276896293685848261682575815713337321.92%3447179.36%2980187352.32%934186750.03%704137051.39%173699416927551422702
_Since Last GM Reset803433012373443331140121901035162167-54022140020218216616850.531344580924219014310711276896293685848261682575815713337321.92%3447179.36%2980187352.32%934186750.03%704137051.39%173699416927551422702
_Vs Conference462019002142031921123811000139595023128002011089711480.52220334254511901431071115949629368584814494614589552134822.54%2054478.54%2980187352.32%934186750.03%704137051.39%173699416927551422702
_Vs Division19970011185805934000113942-310630010046388220.57985135220119014310711616962936858485811952253911052220.95%1002179.00%1980187352.32%934186750.03%704137051.39%173699416927551422702

Total For Players
Games PlayedPointsStreakGoalsAssistsPointsShots ForShots AgainstShots BlockedPenalty MinutesHitsEmpty Net GoalsShutouts
8085L334458092427682616825758157121
All Games
GPWLOTWOTL SOWSOLGFGA
8034331237344333
Home Games
GPWLOTWOTL SOWSOLGFGA
4012191035162167
Visitor Games
GPWLOTWOTL SOWSOLGFGA
4022140202182166
Last 10 Games
WLOTWOTL SOWSOL
550000
Power Play AttempsPower Play GoalsPower Play %Penalty Kill AttempsPenalty Kill Goals AgainstPenalty Kill %Penalty Kill Goals For
3337321.92%3447179.36%2
Shots 1 PeriodShots 2 PeriodShots 3 PeriodShots 4+ PeriodGoals 1 PeriodGoals 2 PeriodGoals 3 PeriodGoals 4+ Period
962936858489014310711
Face Offs
Won Offensive ZoneTotal OffensiveWon Offensive %Won Defensif ZoneTotal DefensiveWon Defensive %Won Neutral ZoneTotal NeutralWon Neutral %
980187352.32%934186750.03%704137051.39%
Puck Time
In Offensive ZoneControl In Offensive ZoneIn Defensive ZoneControl In Defensive ZoneIn Neutral ZoneControl In Neutral Zone
173699416927551422702


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 - 2022-10-271Marlies6Phantoms5BLXXBoxScore
3 - 2022-10-2914Phantoms3Comets2AWBoxScore
4 - 2022-10-3016Phantoms4Marlies6ALBoxScore
9 - 2022-11-0448Heat4Phantoms5BWXXR1BoxScore
11 - 2022-11-0653Phantoms4Marlies5ALXBoxScore
13 - 2022-11-0868Phantoms5Heat4AWR1BoxScore
15 - 2022-11-1076Comets5Phantoms1BLBoxScore
17 - 2022-11-1287Phantoms3Comets5ALBoxScore
19 - 2022-11-14101Reign7Phantoms6BLR1BoxScore
21 - 2022-11-16113Phantoms4Comets3AWBoxScore
22 - 2022-11-17117Phantoms7Reign6AWR1BoxScore
23 - 2022-11-18129Little Stars1Phantoms4BWBoxScore
29 - 2022-11-24153Griffins2Phantoms4BWBoxScore
32 - 2022-11-27170Phantoms4Reign0AWR1BoxScore
34 - 2022-11-29178Marlies2Phantoms5BWBoxScore
37 - 2022-12-02198Condors5Phantoms4BLXXBoxScore
40 - 2022-12-05212Phantoms4Monsters2AWBoxScore
43 - 2022-12-08225Wolfpack5Phantoms6BWXXBoxScore
46 - 2022-12-11239Phantoms5Reign3AWR1BoxScore
48 - 2022-12-13250Moose6Phantoms4BLBoxScore
52 - 2022-12-17266Phantoms6Comets5AWBoxScore
54 - 2022-12-19275Bears4Phantoms2BLBoxScore
58 - 2022-12-23295Heat7Phantoms3BLR1BoxScore
60 - 2022-12-25308Phantoms5Crunch2AWBoxScore
63 - 2022-12-28320Phantoms8Wolves3AWBoxScore
64 - 2022-12-29329Monsters1Phantoms3BWBoxScore
67 - 2023-01-01347Eagles5Phantoms3BLBoxScore
69 - 2023-01-03357Phantoms4Heat9ALR1BoxScore
71 - 2023-01-05365Phantoms2Thunderbirds6ALBoxScore
73 - 2023-01-07379Monsters3Phantoms7BWBoxScore
77 - 2023-01-11400Phantoms7Admirals5AWBoxScore
79 - 2023-01-13406Thunderbirds5Phantoms4BLBoxScore
81 - 2023-01-15415Phantoms6Heat1AWR1BoxScore
84 - 2023-01-18430Barracuda6Phantoms5BLBoxScore
86 - 2023-01-20440Phantoms2Griffins4ALBoxScore
89 - 2023-01-23457Crunch5Phantoms3BLBoxScore
92 - 2023-01-26476Phantoms6Sound Tigers4AWBoxScore
93 - 2023-01-27485Rampage6Phantoms3BLBoxScore
96 - 2023-01-30500Phantoms2Rampage4ALBoxScore
97 - 2023-01-31509Reign2Phantoms4BWR1BoxScore
101 - 2023-02-04526Phantoms1Penguins3ALBoxScore
103 - 2023-02-06535Penguins8Phantoms4BLBoxScore
106 - 2023-02-09551Phantoms4Moose5ALBoxScore
108 - 2023-02-11560Little Stars2Phantoms1BLXXBoxScore
111 - 2023-02-14580Phantoms6Punishers3AWBoxScore
112 - 2023-02-15587Senators4Phantoms2BLBoxScore
117 - 2023-02-20611Condors3Phantoms6BWBoxScore
119 - 2023-02-22619Phantoms4Condors5ALXBoxScore
123 - 2023-02-26637Marlies6Phantoms5BLBoxScore
125 - 2023-02-28648Phantoms5Rocket7ALBoxScore
127 - 2023-03-02661Sound Tigers3Phantoms4BWXBoxScore
129 - 2023-03-04671Phantoms3Barracuda7ALBoxScore
132 - 2023-03-07688Rocket1Phantoms6BWBoxScore
134 - 2023-03-09698Phantoms7Senators6AWBoxScore
137 - 2023-03-12714Phantoms5Marlies1AWBoxScore
138 - 2023-03-13720Comets6Phantoms5BLXXBoxScore
140 - 2023-03-15734Phantoms7Eagles5AWBoxScore
142 - 2023-03-17743Admirals4Phantoms3BLXXBoxScore
146 - 2023-03-21763Griffins6Phantoms5BLBoxScore
148 - 2023-03-23775Phantoms2Wolfpack3ALXXBoxScore
150 - 2023-03-25780Phantoms2Senators3ALXXBoxScore
152 - 2023-03-27794Phantoms2Marlies3ALBoxScore
153 - 2023-03-28800Eagles3Phantoms9BWBoxScore
157 - 2023-04-01819Devils2Phantoms3BWXXBoxScore
Trade Deadline --- Trades can’t be done after this day is simulated!
160 - 2023-04-04830Phantoms5Devils3AWBoxScore
163 - 2023-04-07846Barracuda2Phantoms1BLBoxScore
166 - 2023-04-10857Phantoms3Little Stars8ALBoxScore
168 - 2023-04-12872Reign4Phantoms5BWR1BoxScore
170 - 2023-04-14883Phantoms7Bears4AWBoxScore
173 - 2023-04-17897Phantoms4Rocket5ALBoxScore
174 - 2023-04-18903Icehogs6Phantoms3BLBoxScore
179 - 2023-04-23923Comets2Phantoms5BWBoxScore
181 - 2023-04-25936Phantoms7Moose4AWBoxScore
183 - 2023-04-27944Phantoms5Icehogs3AWBoxScore
184 - 2023-04-28952Phantoms4Wolfpack6ALBoxScore
186 - 2023-04-30960Wolves4Phantoms7BWBoxScore
188 - 2023-05-02970Phantoms8Icehogs3AWBoxScore
192 - 2023-05-06988Punishers6Phantoms3BLBoxScore
197 - 2023-05-111008Admirals4Phantoms3BLBoxScore
203 - 2023-05-171030Heat4Phantoms1BLR1BoxScore



Arena Capacity - Ticket Price Attendance - %
Level 1Level 2
Capacity20001000
Ticket Price3520
Attendance74,31123,762
Attendance PCT92.89%59.41%

Income
Home Games LeftAverage Attendance - %Average Income per GameYear to Date RevenueCapacityTeam Popularity
0 2452 - 81.73% 80,748$3,229,933$3000100

Expenses
Year To Date ExpensesPlayers Total SalariesPlayers Total Average SalariesCoaches Salaries
2,650,138$ 1,987,000$ 1,769,500$ 0$
Salary Cap Per DaysSalary Cap To DatePlayers In Salary CapPlayers Out of Salary Cap
9,646$ 2,141,725$ 0 0

Estimate
Estimated Season RevenueRemaining Season DaysExpenses Per DaysEstimated Season Expenses
0$ 0 12,073$ 0$




Phantoms Stat Leaders (Regular Season)

# 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

Phantoms Goalies Stat Leaders (Regular Season)

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

Phantoms Career Team Stats

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

Phantoms Stat Leaders (Play-Off)

# 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

Phantoms Goalies Stat Leaders (Play-Off)

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