Shot Prop Lab
Shots on Goal Projections for Monday, October 19, 2026
Expected shots on goal for every skater on tonight's slate, and the chance he clears 1.5, 2.5 and 3.5. Each number starts from the shooter's own attempt rate and accuracy, times the ice time we expect him to get at 5-on-5 and on the power play, then adjusts for the defenders he is likely to face and how well the opponent kills penalties.
4 games, 145 skaters · updated Oct 19, 5:50 PM ET · model shotprops-1.1.0. Projections, not picks. Book lines from 5 US sportsbooks (via The Odds API) are in the table as context, not as picks. Live since Oct 12 (1,094 graded lines): about even on shots on goal. Even with the books is not an edge once the margin is paid.
Final: 133 skaters played. Projected 208 shots in total, actual 212. Of the 8 skaters we gave a 50%+ chance of 3+ shots, 6 got there (75%; projected 57%).
Most likely to get 3+ shots
- Nathan MacKinnonCOL @ PHI67% · 3.57
- Macklin CelebriniSJS @ TOR65% · 3.44
- Auston MatthewsTOR vs SJS63% · 3.37
- Cutter GauthierANA @ NYR58% · 3.08
- Beckett SenneckeANA @ NYR54% · 2.90
- Nazem KadriCOL @ PHI51% · 2.78
Softest 5v5 matchups
- Macklin CelebriniSJS @ TOR+3% (+0.05) · 3.44
- Darnell NurseSJS @ TOR+3% (+0.05) · 1.77
- Alexis LafrenièreNYR vs ANA+2% (+0.04) · 2.21
- Mika ZibanejadNYR vs ANA+2% (+0.03) · 2.50
- Jack RoslovicTOR vs SJS+2% (+0.03) · 2.21
- Auston MatthewsTOR vs SJS+1% (+0.03) · 3.37
Toughest 5v5 matchups
- Rickard RakellPIT @ UTA−6% (−0.11) · 2.54
- Sidney CrosbyPIT @ UTA−6% (−0.10) · 2.31
- Anders LeeUTA vs PIT−2% (−0.04) · 1.82
- Leo CarlssonANA @ NYR−2% (−0.04) · 2.64
- Jack McBainUTA vs PIT−3% (−0.03) · 1.29
- Beckett SenneckeANA @ NYR−2% (−0.03) · 2.90
Every skater, Oct 19
Games: ANA @ NYR 7:00 PM ET · COL @ PHI 7:00 PM ET · SJS @ TOR 7:30 PM ET · PIT @ UTA 9:00 PM ET. Matchup is the 5-on-5 adjustment for the defenders he is expected to face and home ice (+5% = 5% more shots than his usual rate).
145 skaters
- Nathan MacKinnonF · COL @ PHI3.57Exp SOG
- Over 3.5
- 47%
- Best over
- −144
- Books
- 56%
- Actual
- 1
Ice time, SOG/60 and matchup
- TOI
- 20:57
- PP TOI
- 4:07
- SOG/60 5v5
- 9.5
- Matchup
- −1%
- 2+ / 3+ / 4+
- 85% / 67% / 47%
- Book line
- 3.5 · o −144 / u +120
- Macklin CelebriniF · SJS @ TOR3.44Exp SOG
- Over 3.5
- 44%
- Best over
- −109
- Books
- 49%
- Actual
- 5
Ice time, SOG/60 and matchup
- TOI
- 22:04
- PP TOI
- 3:52
- SOG/60 5v5
- 7.4
- Matchup
- +3%
- 2+ / 3+ / 4+
- 84% / 65% / 44%
- Book line
- 3.5 · o −109 / u −115
- Auston MatthewsF · TOR vs SJS3.37Exp SOG
- Over 3.5
- 43%
- Best over
- +100
- Books
- 50%
- Actual
- 3
Ice time, SOG/60 and matchup
- TOI
- 21:01
- PP TOI
- 3:50
- SOG/60 5v5
- 8.6
- Matchup
- +1%
- 2+ / 3+ / 4+
- 83% / 63% / 43%
- Book line
- 3.5 · o +100 / u −105
- Cutter GauthierF · ANA @ NYR3.08Exp SOG
- Over 3.5
- 37%
- Best over
- +115
- Books
- 44%
- Actual
- 5
Ice time, SOG/60 and matchup
- TOI
- 16:22
- PP TOI
- 3:16
- SOG/60 5v5
- 10.4
- Matchup
- −1%
- 2+ / 3+ / 4+
- 79% / 58% / 37%
- Book line
- 3.5 · o +115 / u −132
- Beckett SenneckeF · ANA @ NYR2.90Exp SOG
- Over 2.5
- 54%
- Best over
- +102
- Books
- 49%
- Actual
- 4
Ice time, SOG/60 and matchup
- TOI
- 21:19
- PP TOI
- 4:00
- SOG/60 5v5
- 7.3
- Matchup
- −2%
- 2+ / 3+ / 4+
- 76% / 54% / 33%
- Book line
- 2.5 · o +102 / u −114
- Nazem KadriF · COL @ PHI2.78Exp SOG
- Over 2.5
- 51%
- Best over
- −110
- Books
- 51%
- Actual
- 1
Ice time, SOG/60 and matchup
- TOI
- 20:04
- PP TOI
- 3:55
- SOG/60 5v5
- 7.8
- Matchup
- −0%
- 2+ / 3+ / 4+
- 75% / 51% / 31%
- Book line
- 2.5 · o −110 / u −105
- Darren RaddyshD · TOR vs SJS2.73Exp SOG
- Over 2.5
- 50%
- Best over
- +100
- Books
- 49%
- Actual
- 5
Ice time, SOG/60 and matchup
- TOI
- 24:05
- PP TOI
- 3:49
- SOG/60 5v5
- 6.2
- Matchup
- +1%
- 2+ / 3+ / 4+
- 74% / 50% / 30%
- Book line
- 2.5 · o +100 / u −120
- William NylanderF · TOR vs SJS2.72Exp SOG
- Over 2.5
- 50%
- Best over
- −118
- Books
- 54%
- Actual
- 3
Ice time, SOG/60 and matchup
- TOI
- 20:38
- PP TOI
- 3:47
- SOG/60 5v5
- 6.9
- Matchup
- +2%
- 2+ / 3+ / 4+
- 74% / 50% / 29%
- Book line
- 2.5 · o −118 / u +105
- Dylan GuentherF · UTA vs PIT2.72Exp SOG
- Over 2.5
- 50%
- Best over
- −130
- Books
- 54%
- Actual
- 2
Ice time, SOG/60 and matchup
- TOI
- 16:09
- PP TOI
- 3:38
- SOG/60 5v5
- 9.1
- Matchup
- −2%
- 2+ / 3+ / 4+
- 74% / 50% / 29%
- Book line
- 2.5 · o −130 / u +110
- Leo CarlssonF · ANA @ NYR2.64Exp SOG
- Over 2.5
- 48%
- Best over
- +150
- Books
- 39%
- Actual
- 2
Ice time, SOG/60 and matchup
- TOI
- 19:53
- PP TOI
- 3:52
- SOG/60 5v5
- 7.8
- Matchup
- −2%
- 2+ / 3+ / 4+
- 72% / 48% / 28%
- Book line
- 2.5 · o +150 / u −175
- Pavel DorofeyevF · NYR vs ANA2.57Exp SOG
- Over 2.5
- 47%
- Best over
- −140
- Books
- 55%
- Actual
- 5
Ice time, SOG/60 and matchup
- TOI
- 17:25
- PP TOI
- 3:02
- SOG/60 5v5
- 7.8
- Matchup
- +2%
- 2+ / 3+ / 4+
- 71% / 47% / 26%
- Book line
- 2.5 · o −140 / u +120
- Will SmithF · SJS @ TOR2.57Exp SOG
- Over 2.5
- 47%
- Best over
- +115
- Books
- 44%
- Actual
- 4
Ice time, SOG/60 and matchup
- TOI
- 19:55
- PP TOI
- 3:34
- SOG/60 5v5
- 6.7
- Matchup
- +3%
- 2+ / 3+ / 4+
- 71% / 47% / 26%
- Book line
- 2.5 · o +115 / u −130
- Rickard RakellF · PIT @ UTA2.54Exp SOG
- Over 2.5
- 46%
- Best over
- +112
- Books
- 45%
- Actual
- 3
Ice time, SOG/60 and matchup
- TOI
- 19:55
- PP TOI
- 3:40
- SOG/60 5v5
- 7.4
- Matchup
- −6%
- 2+ / 3+ / 4+
- 70% / 46% / 26%
- Book line
- 2.5 · o +112 / u −130
- Kirill MarchenkoF · TOR vs SJS2.54Exp SOG
- Over 2.5
- 46%
- Best over
- −119
- Books
- 52%
- Actual
- 2
Ice time, SOG/60 and matchup
- TOI
- 17:54
- PP TOI
- 3:30
- SOG/60 5v5
- 7.3
- Matchup
- +2%
- 2+ / 3+ / 4+
- 70% / 46% / 26%
- Book line
- 2.5 · o −119 / u −105
- Mika ZibanejadF · NYR vs ANA2.50Exp SOG
- Over 2.5
- 45%
- Best over
- +110
- Books
- 47%
- Actual
- 1
Ice time, SOG/60 and matchup
- TOI
- 20:46
- PP TOI
- 3:30
- SOG/60 5v5
- 6.3
- Matchup
- +2%
- 2+ / 3+ / 4+
- 70% / 45% / 25%
- Book line
- 2.5 · o +110 / u −120
- Martin NecasF · COL @ PHI2.40Exp SOG
- Over 2.5
- 43%
- Best over
- +134
- Books
- 43%
- Actual
- 2
Ice time, SOG/60 and matchup
- TOI
- 20:36
- PP TOI
- 3:58
- SOG/60 5v5
- 5.8
- Matchup
- −1%
- 2+ / 3+ / 4+
- 67% / 43% / 23%
- Book line
- 2.5 · o +134 / u −150
- Sidney CrosbyF · PIT @ UTA2.31Exp SOG
- Over 2.5
- 40%
- Best over
- +142
- Books
- 42%
- Actual
- 1
Ice time, SOG/60 and matchup
- TOI
- 19:41
- PP TOI
- 3:42
- SOG/60 5v5
- 6.6
- Matchup
- −6%
- 2+ / 3+ / 4+
- 66% / 40% / 21%
- Book line
- 2.5 · o +142 / u −155
- Clayton KellerF · UTA vs PIT2.29Exp SOG
- Over 2.5
- 40%
- Best over
- +128
- Books
- 45%
- Actual
- 1
Ice time, SOG/60 and matchup
- TOI
- 17:11
- PP TOI
- 3:38
- SOG/60 5v5
- 7.4
- Matchup
- −1%
- 2+ / 3+ / 4+
- 65% / 40% / 21%
- Book line
- 2.5 · o +128 / u −135
- Cale MakarD · COL @ PHI2.26Exp SOG
- Over 2.5
- 39%
- Best over
- +105
- Books
- 48%
- Actual
- 4
Ice time, SOG/60 and matchup
- TOI
- 22:21
- PP TOI
- 4:14
- SOG/60 5v5
- 5.9
- Matchup
- −0%
- 2+ / 3+ / 4+
- 65% / 39% / 20%
- Book line
- 2.5 · o +105 / u −125
- Bryan RustF · PIT @ UTA2.22Exp SOG
- Over 2.5
- 38%
- Best over
- +144
- Books
- 39%
- Actual
- 0
Ice time, SOG/60 and matchup
- TOI
- 19:45
- PP TOI
- 2:31
- SOG/60 5v5
- 6.7
- Matchup
- −6%
- 2+ / 3+ / 4+
- 64% / 38% / 19%
- Book line
- 2.5 · o +144 / u −185
- Jack RoslovicF · TOR vs SJS2.21Exp SOG
- Over 2.5
- 38%
- Best over
- +115
- Books
- 45%
- Actual
- 0
Ice time, SOG/60 and matchup
- TOI
- 16:34
- PP TOI
- 1:00
- SOG/60 5v5
- 7.7
- Matchup
- +2%
- 2+ / 3+ / 4+
- 63% / 38% / 19%
- Book line
- 2.5 · o +115 / u −130
- Alexis LafrenièreF · NYR vs ANA2.21Exp SOG
- Over 2.5
- 38%
- Best over
- +140
- Books
- 41%
- Actual
- 3
Ice time, SOG/60 and matchup
- TOI
- 18:48
- PP TOI
- 3:27
- SOG/60 5v5
- 6.2
- Matchup
- +2%
- 2+ / 3+ / 4+
- 63% / 38% / 19%
- Book line
- 2.5 · o +140 / u −160
- Nick SchmaltzF · UTA vs PIT2.19Exp SOG
- Over 2.5
- 37%
- Best over
- +120
- Books
- 44%
- Actual
- 2
Ice time, SOG/60 and matchup
- TOI
- 18:16
- PP TOI
- 3:31
- SOG/60 5v5
- 6.6
- Matchup
- −1%
- 2+ / 3+ / 4+
- 63% / 37% / 19%
- Book line
- 2.5 · o +120 / u −145
- Erik KarlssonD · PIT @ UTA2.09Exp SOG
- Over 1.5
- 60%
- Best over
- −148
- Books
- 57%
- Actual
- 1
Ice time, SOG/60 and matchup
- TOI
- 23:12
- PP TOI
- 3:43
- SOG/60 5v5
- 5.0
- Matchup
- −6%
- 2+ / 3+ / 4+
- 60% / 35% / 17%
- Book line
- 1.5 · o −148 / u +120
- Brock NelsonF · COL @ PHI2.01Exp SOG
- Over 1.5
- 58%
- Best over
- −145
- Books
- 59%
- Actual
- 3
Ice time, SOG/60 and matchup
- TOI
- 19:20
- PP TOI
- 1:29
- SOG/60 5v5
- 6.5
- Matchup
- −0%
- 2+ / 3+ / 4+
- 58% / 33% / 15%
- Book line
- 1.5 · o −145 / u +140
- Artturi LehkonenF · COL @ PHI2.01Exp SOG
- Over 1.5
- 58%
- Best over
- −135
- Books
- 54%
- Actual
- 2
Ice time, SOG/60 and matchup
- TOI
- 19:28
- PP TOI
- 1:34
- SOG/60 5v5
- 6.3
- Matchup
- −0%
- 2+ / 3+ / 4+
- 58% / 33% / 15%
- Book line
- 1.5 · o −135 / u +110
- Tyson FoersterF · PHI vs COL1.99Exp SOG
- Over 2.5
- 32%
- Best over
- +135
- Books
- 41%
- Actual
- DNP
Ice time, SOG/60 and matchup
- TOI
- 17:46
- PP TOI
- 2:46
- SOG/60 5v5
- 6.1
- Matchup
- +1%
- 2+ / 3+ / 4+
- 58% / 32% / 15%
- Book line
- 2.5 · o +135 / u −161
- J.T. MillerF · NYR vs ANA1.97Exp SOG
- Over 1.5
- 57%
- Best over
- −156
- Books
- 58%
- Actual
- 2
Ice time, SOG/60 and matchup
- TOI
- 18:31
- PP TOI
- 3:13
- SOG/60 5v5
- 5.4
- Matchup
- +2%
- 2+ / 3+ / 4+
- 57% / 32% / 15%
- Book line
- 1.5 · o −156 / u +130
- Gabriel LandeskogF · COL @ PHI1.97Exp SOG
- Over 1.5
- 57%
- Best over
- −135
- Books
- 54%
- Actual
- 0
Ice time, SOG/60 and matchup
- TOI
- 15:36
- PP TOI
- 2:00
- SOG/60 5v5
- 7.4
- Matchup
- −0%
- 2+ / 3+ / 4+
- 57% / 31% / 14%
- Book line
- 1.5 · o −135 / u +110
- Trevor ZegrasF · PHI vs COL1.93Exp SOG
- Over 1.5
- 56%
- Best over
- −141
- Books
- 55%
- Actual
- 3
Ice time, SOG/60 and matchup
- TOI
- 19:10
- PP TOI
- 2:59
- SOG/60 5v5
- 5.1
- Matchup
- +1%
- 2+ / 3+ / 4+
- 56% / 31% / 14%
- Book line
- 1.5 · o −141 / u +110
- Kiefer SherwoodF · SJS @ TOR1.91Exp SOG
- Over 1.5
- 56%
- Best over
- −110
- Books
- 51%
- Actual
- 0
Ice time, SOG/60 and matchup
- TOI
- 15:01
- PP TOI
- 0:27
- SOG/60 5v5
- 7.5
- Matchup
- +3%
- 2+ / 3+ / 4+
- 56% / 30% / 14%
- Book line
- 1.5 · o −110 / u −102
- Evgeni MalkinF · PIT @ UTA1.90Exp SOG
- Over 1.5
- 56%
- Best over
- −154
- Books
- 59%
- Actual
- 1
Ice time, SOG/60 and matchup
- TOI
- 16:23
- PP TOI
- 2:22
- SOG/60 5v5
- 6.6
- Matchup
- −6%
- 2+ / 3+ / 4+
- 56% / 30% / 13%
- Book line
- 1.5 · o −154 / u +130
- Ben KindelF · PIT @ UTA1.89Exp SOG
- Over 1.5
- 55%
- Best over
- −149
- Books
- 57%
- Actual
- 1
Ice time, SOG/60 and matchup
- TOI
- 16:05
- PP TOI
- 2:23
- SOG/60 5v5
- 6.9
- Matchup
- −6%
- 2+ / 3+ / 4+
- 55% / 30% / 13%
- Book line
- 1.5 · o −149 / u +120
- Jackson LaCombeD · ANA @ NYR1.82Exp SOG
- Over 1.5
- 53%
- Best over
- +100
- Books
- 48%
- Actual
- 1
Ice time, SOG/60 and matchup
- TOI
- 25:48
- PP TOI
- 3:57
- SOG/60 5v5
- 3.9
- Matchup
- −2%
- 2+ / 3+ / 4+
- 53% / 28% / 12%
- Book line
- 1.5 · o +100 / u −120
- Anders LeeF · UTA vs PIT1.82Exp SOG
- Over 1.5
- 53%
- Best over
- −140
- Books
- 55%
- Actual
- 1
Ice time, SOG/60 and matchup
- TOI
- 13:34
- PP TOI
- 1:12
- SOG/60 5v5
- 8.0
- Matchup
- −2%
- 2+ / 3+ / 4+
- 53% / 28% / 12%
- Book line
- 1.5 · o −140 / u +110
- Matvei MichkovF · PHI vs COL1.81Exp SOG
- Over 1.5
- 53%
- Best over
- −150
- Books
- 56%
- Actual
- 2
Ice time, SOG/60 and matchup
- TOI
- 14:52
- PP TOI
- 2:49
- SOG/60 5v5
- 6.8
- Matchup
- +1%
- 2+ / 3+ / 4+
- 53% / 27% / 12%
- Book line
- 1.5 · o −150 / u +116
- Logan CooleyF · UTA vs PIT1.81Exp SOG
- Over 1.5
- 53%
- Best over
- −161
- Books
- 61%
- Actual
- 2
Ice time, SOG/60 and matchup
- TOI
- 17:55
- PP TOI
- 3:39
- SOG/60 5v5
- 5.8
- Matchup
- −2%
- 2+ / 3+ / 4+
- 53% / 27% / 12%
- Book line
- 1.5 · o −161 / u +140
- Mikhail SergachevD · UTA vs PIT1.80Exp SOG
- Over 1.5
- 53%
- Best over
- −138
- Books
- 56%
- Actual
- 4
Ice time, SOG/60 and matchup
- TOI
- 23:58
- PP TOI
- 3:21
- SOG/60 5v5
- 4.2
- Matchup
- −1%
- 2+ / 3+ / 4+
- 53% / 27% / 12%
- Book line
- 1.5 · o −138 / u +130
- Ivar StenbergF · SJS @ TOR1.80Exp SOG
- Over 1.5
- 53%
- Best over
- −116
- Books
- 52%
- Actual
- 1
Ice time, SOG/60 and matchup
- TOI
- 15:47
- PP TOI
- 3:13
- SOG/60 5v5
- 5.5
- Matchup
- +3%
- 2+ / 3+ / 4+
- 53% / 27% / 12%
- Book line
- 1.5 · o −116 / u +100
- Jacob TroubaD · SJS @ TOR1.80Exp SOG
- Over 1.5
- 53%
- Best over
- −114
- Books
- 50%
- Actual
- 1
Ice time, SOG/60 and matchup
- TOI
- 21:33
- PP TOI
- 0:26
- SOG/60 5v5
- 5.4
- Matchup
- +3%
- 2+ / 3+ / 4+
- 53% / 27% / 12%
- Book line
- 1.5 · o −114 / u −114
- Will CuylleF · NYR vs ANA1.80Exp SOG
- Over 1.5
- 53%
- Best over
- −145
- Books
- 57%
- Actual
- 3
Ice time, SOG/60 and matchup
- TOI
- 15:31
- PP TOI
- 1:19
- SOG/60 5v5
- 6.9
- Matchup
- +2%
- 2+ / 3+ / 4+
- 53% / 27% / 12%
- Book line
- 1.5 · o −145 / u +130
- Darnell NurseD · SJS @ TOR1.77Exp SOG
- Over 1.5
- 52%
- Best over
- −154
- Books
- 58%
- Actual
- 3
Ice time, SOG/60 and matchup
- TOI
- 20:38
- PP TOI
- 0:00
- SOG/60 5v5
- 5.6
- Matchup
- +3%
- 2+ / 3+ / 4+
- 52% / 26% / 11%
- Book line
- 1.5 · o −154 / u +125
- Christian DvorakF · PHI vs COL1.75Exp SOG
- Over 1.5
- 51%
- Best over
- +100
- Books
- 49%
- Actual
- 1
Ice time, SOG/60 and matchup
- TOI
- 18:47
- PP TOI
- 1:30
- SOG/60 5v5
- 5.3
- Matchup
- +1%
- 2+ / 3+ / 4+
- 51% / 26% / 11%
- Book line
- 1.5 · o +100 / u −114
- Gabe PerreaultF · NYR vs ANA1.75Exp SOG
- Over 1.5
- 51%
- Best over
- −125
- Books
- 53%
- Actual
- 4
Ice time, SOG/60 and matchup
- TOI
- 16:40
- PP TOI
- 1:33
- SOG/60 5v5
- 5.9
- Matchup
- +2%
- 2+ / 3+ / 4+
- 51% / 26% / 11%
- Book line
- 1.5 · o −125 / u +105
- Alex KillornF · ANA @ NYR1.75Exp SOG
- Over 1.5
- 51%
- Best over
- −128
- Books
- 53%
- Actual
- 1
Ice time, SOG/60 and matchup
- TOI
- 16:23
- PP TOI
- 1:10
- SOG/60 5v5
- 6.6
- Matchup
- −2%
- 2+ / 3+ / 4+
- 51% / 26% / 11%
- Book line
- 1.5 · o −128 / u +110
- Mason MarchmentF · SJS @ TOR1.72Exp SOG
- Over 1.5
- 51%
- Best over
- −122
- Books
- 52%
- Actual
- 4
Ice time, SOG/60 and matchup
- TOI
- 15:53
- PP TOI
- 1:15
- SOG/60 5v5
- 5.9
- Matchup
- +3%
- 2+ / 3+ / 4+
- 51% / 25% / 11%
- Book line
- 1.5 · o −122 / u −105
- T.J. HughesF · COL @ PHI1.70Exp SOG
- Over 1.5
- 50%
- Best over
- −118
- Books
- 51%
- Actual
- 2
Ice time, SOG/60 and matchup
- TOI
- 13:27
- PP TOI
- 3:52
- SOG/60 5v5
- 6.7
- Matchup
- +0%
- 2+ / 3+ / 4+
- 50% / 25% / 10%
- Book line
- 1.5 · o −118 / u −110
- Tyler ToffoliF · SJS @ TOR1.70Exp SOG
- Over 1.5
- 50%
- Best over
- −149
- Books
- 57%
- Actual
- 2
Ice time, SOG/60 and matchup
- TOI
- 12:52
- PP TOI
- 1:24
- SOG/60 5v5
- 7.0
- Matchup
- +4%
- 2+ / 3+ / 4+
- 50% / 25% / 10%
- Book line
- 1.5 · o −149 / u +120
- Tommy NovakF · PIT @ UTA1.68Exp SOG
- Over 1.5
- 49%
- Best over
- +109
- Books
- 45%
- Actual
- 1
Ice time, SOG/60 and matchup
- TOI
- 15:33
- PP TOI
- 2:34
- SOG/60 5v5
- 6.0
- Matchup
- −6%
- 2+ / 3+ / 4+
- 49% / 24% / 10%
- Book line
- 1.5 · o +109 / u −141
- Sam MalinskiD · COL @ PHI1.66Exp SOG
- Over 2.5
- 24%
- Best over
- –
- Books
- –
- Actual
- 2
Ice time, SOG/60 and matchup
- TOI
- 16:08
- PP TOI
- 0:17
- SOG/60 5v5
- 6.3
- Matchup
- +0%
- 2+ / 3+ / 4+
- 49% / 24% / 10%
- Lawson CrouseF · UTA vs PIT1.66Exp SOG
- Over 1.5
- 49%
- Best over
- −108
- Books
- 48%
- Actual
- 1
Ice time, SOG/60 and matchup
- TOI
- 16:22
- PP TOI
- 0:09
- SOG/60 5v5
- 6.7
- Matchup
- −1%
- 2+ / 3+ / 4+
- 49% / 24% / 9%
- Book line
- 1.5 · o −108 / u −120
- Gavin McKennaF · TOR vs SJS1.66Exp SOG
- Over 1.5
- 49%
- Best over
- −139
- Books
- 55%
- Actual
- 1
Ice time, SOG/60 and matchup
- TOI
- 13:41
- PP TOI
- 1:54
- SOG/60 5v5
- 6.5
- Matchup
- +2%
- 2+ / 3+ / 4+
- 49% / 23% / 9%
- Book line
- 1.5 · o −139 / u +110
- MacKenzie WeegarD · UTA vs PIT1.64Exp SOG
- Over 1.5
- 48%
- Best over
- −115
- Books
- 51%
- Actual
- 3
Ice time, SOG/60 and matchup
- TOI
- 23:13
- PP TOI
- 0:14
- SOG/60 5v5
- 4.8
- Matchup
- −2%
- 2+ / 3+ / 4+
- 48% / 23% / 9%
- Book line
- 1.5 · o −115 / u −110
- Brent BurnsD · COL @ PHI1.58Exp SOG
- Over 2.5
- 22%
- Best over
- –
- Books
- –
- Actual
- 1
Ice time, SOG/60 and matchup
- TOI
- 16:09
- PP TOI
- 0:06
- SOG/60 5v5
- 6.5
- Matchup
- +0%
- 2+ / 3+ / 4+
- 46% / 22% / 8%
- Alexander WennbergF · SJS @ TOR1.56Exp SOG
- Over 2.5
- 21%
- Best over
- –
- Books
- –
- Actual
- 0
Ice time, SOG/60 and matchup
- TOI
- 20:15
- PP TOI
- 3:39
- SOG/60 5v5
- 3.7
- Matchup
- +3%
- 2+ / 3+ / 4+
- 46% / 21% / 8%
- Sean CouturierF · PHI vs COL1.56Exp SOG
- Over 2.5
- 21%
- Best over
- –
- Books
- –
- Actual
- 2
Ice time, SOG/60 and matchup
- TOI
- 17:43
- PP TOI
- 0:14
- SOG/60 5v5
- 5.4
- Matchup
- +1%
- 2+ / 3+ / 4+
- 46% / 21% / 8%
- Porter MartoneF · PHI vs COL1.55Exp SOG
- Over 1.5
- 45%
- Best over
- −123
- Books
- 55%
- Actual
- 1
Ice time, SOG/60 and matchup
- TOI
- 13:38
- PP TOI
- 2:17
- SOG/60 5v5
- 5.5
- Matchup
- +1%
- 2+ / 3+ / 4+
- 45% / 21% / 8%
- Book line
- 1.5 · o −123 / u +115
- Easton CowanF · TOR vs SJS1.55Exp SOG
- Over 1.5
- 45%
- Best over
- −118
- Books
- 51%
- Actual
- 2
Ice time, SOG/60 and matchup
- TOI
- 15:11
- PP TOI
- 0:43
- SOG/60 5v5
- 6.0
- Matchup
- +2%
- 2+ / 3+ / 4+
- 45% / 21% / 8%
- Book line
- 1.5 · o −118 / u −105
- Michael BuntingF · PHI vs COL1.54Exp SOG
- Over 1.5
- 45%
- Best over
- −105
- Books
- 48%
- Actual
- 1
Ice time, SOG/60 and matchup
- TOI
- 12:14
- PP TOI
- 2:12
- SOG/60 5v5
- 7.1
- Matchup
- +1%
- 2+ / 3+ / 4+
- 45% / 21% / 8%
- Book line
- 1.5 · o −105 / u −120
- Barrett HaytonF · UTA vs PIT1.51Exp SOG
- Over 1.5
- 44%
- Best over
- +102
- Books
- 47%
- Actual
- 2
Ice time, SOG/60 and matchup
- TOI
- 14:06
- PP TOI
- 0:53
- SOG/60 5v5
- 6.5
- Matchup
- −2%
- 2+ / 3+ / 4+
- 44% / 20% / 7%
- Book line
- 1.5 · o +102 / u −132
| Book line | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| Nathan MacKinnonF · COL @ PHI | 3.57 | 85% | 67% | 47% | 20:57PP 4:07 | 9.5 | −1% | 3.5 · o −144 / u +120 | 1 |
| Macklin CelebriniF · SJS @ TOR | 3.44 | 84% | 65% | 44% | 22:04PP 3:52 | 7.4 | +3% | 3.5 · o −109 / u −115 | 5 |
| Auston MatthewsF · TOR vs SJS | 3.37 | 83% | 63% | 43% | 21:01PP 3:50 | 8.6 | +1% | 3.5 · o +100 / u −105 | 3 |
| Cutter GauthierF · ANA @ NYR | 3.08 | 79% | 58% | 37% | 16:22PP 3:16 | 10.4 | −1% | 3.5 · o +115 / u −132 | 5 |
| Beckett SenneckeF · ANA @ NYR | 2.90 | 76% | 54% | 33% | 21:19PP 4:00 | 7.3 | −2% | 2.5 · o +102 / u −114 | 4 |
| Nazem KadriF · COL @ PHI | 2.78 | 75% | 51% | 31% | 20:04PP 3:55 | 7.8 | −0% | 2.5 · o −110 / u −105 | 1 |
| Darren RaddyshD · TOR vs SJS | 2.73 | 74% | 50% | 30% | 24:05PP 3:49 | 6.2 | +1% | 2.5 · o +100 / u −120 | 5 |
| William NylanderF · TOR vs SJS | 2.72 | 74% | 50% | 29% | 20:38PP 3:47 | 6.9 | +2% | 2.5 · o −118 / u +105 | 3 |
| Dylan GuentherF · UTA vs PIT | 2.72 | 74% | 50% | 29% | 16:09PP 3:38 | 9.1 | −2% | 2.5 · o −130 / u +110 | 2 |
| Leo CarlssonF · ANA @ NYR | 2.64 | 72% | 48% | 28% | 19:53PP 3:52 | 7.8 | −2% | 2.5 · o +150 / u −175 | 2 |
| Pavel DorofeyevF · NYR vs ANA | 2.57 | 71% | 47% | 26% | 17:25PP 3:02 | 7.8 | +2% | 2.5 · o −140 / u +120 | 5 |
| Will SmithF · SJS @ TOR | 2.57 | 71% | 47% | 26% | 19:55PP 3:34 | 6.7 | +3% | 2.5 · o +115 / u −130 | 4 |
| Rickard RakellF · PIT @ UTA | 2.54 | 70% | 46% | 26% | 19:55PP 3:40 | 7.4 | −6% | 2.5 · o +112 / u −130 | 3 |
| Kirill MarchenkoF · TOR vs SJS | 2.54 | 70% | 46% | 26% | 17:54PP 3:30 | 7.3 | +2% | 2.5 · o −119 / u −105 | 2 |
| Mika ZibanejadF · NYR vs ANA | 2.50 | 70% | 45% | 25% | 20:46PP 3:30 | 6.3 | +2% | 2.5 · o +110 / u −120 | 1 |
| Martin NecasF · COL @ PHI | 2.40 | 67% | 43% | 23% | 20:36PP 3:58 | 5.8 | −1% | 2.5 · o +134 / u −150 | 2 |
| Sidney CrosbyF · PIT @ UTA | 2.31 | 66% | 40% | 21% | 19:41PP 3:42 | 6.6 | −6% | 2.5 · o +142 / u −155 | 1 |
| Clayton KellerF · UTA vs PIT | 2.29 | 65% | 40% | 21% | 17:11PP 3:38 | 7.4 | −1% | 2.5 · o +128 / u −135 | 1 |
| Cale MakarD · COL @ PHI | 2.26 | 65% | 39% | 20% | 22:21PP 4:14 | 5.9 | −0% | 2.5 · o +105 / u −125 | 4 |
| Bryan RustF · PIT @ UTA | 2.22 | 64% | 38% | 19% | 19:45PP 2:31 | 6.7 | −6% | 2.5 · o +144 / u −185 | 0 |
| Jack RoslovicF · TOR vs SJS | 2.21 | 63% | 38% | 19% | 16:34PP 1:00 | 7.7 | +2% | 2.5 · o +115 / u −130 | 0 |
| Alexis LafrenièreF · NYR vs ANA | 2.21 | 63% | 38% | 19% | 18:48PP 3:27 | 6.2 | +2% | 2.5 · o +140 / u −160 | 3 |
| Nick SchmaltzF · UTA vs PIT | 2.19 | 63% | 37% | 19% | 18:16PP 3:31 | 6.6 | −1% | 2.5 · o +120 / u −145 | 2 |
| Erik KarlssonD · PIT @ UTA | 2.09 | 60% | 35% | 17% | 23:12PP 3:43 | 5.0 | −6% | 1.5 · o −148 / u +120 | 1 |
| Brock NelsonF · COL @ PHI | 2.01 | 58% | 33% | 15% | 19:20PP 1:29 | 6.5 | −0% | 1.5 · o −145 / u +140 | 3 |
| Artturi LehkonenF · COL @ PHI | 2.01 | 58% | 33% | 15% | 19:28PP 1:34 | 6.3 | −0% | 1.5 · o −135 / u +110 | 2 |
| Tyson FoersterF · PHI vs COL | 1.99 | 58% | 32% | 15% | 17:46PP 2:46 | 6.1 | +1% | 2.5 · o +135 / u −161 | DNP |
| J.T. MillerF · NYR vs ANA | 1.97 | 57% | 32% | 15% | 18:31PP 3:13 | 5.4 | +2% | 1.5 · o −156 / u +130 | 2 |
| Gabriel LandeskogF · COL @ PHI | 1.97 | 57% | 31% | 14% | 15:36PP 2:00 | 7.4 | −0% | 1.5 · o −135 / u +110 | 0 |
| Trevor ZegrasF · PHI vs COL | 1.93 | 56% | 31% | 14% | 19:10PP 2:59 | 5.1 | +1% | 1.5 · o −141 / u +110 | 3 |
| Kiefer SherwoodF · SJS @ TOR | 1.91 | 56% | 30% | 14% | 15:01 | 7.5 | +3% | 1.5 · o −110 / u −102 | 0 |
| Evgeni MalkinF · PIT @ UTA | 1.90 | 56% | 30% | 13% | 16:23PP 2:22 | 6.6 | −6% | 1.5 · o −154 / u +130 | 1 |
| Ben KindelF · PIT @ UTA | 1.89 | 55% | 30% | 13% | 16:05PP 2:23 | 6.9 | −6% | 1.5 · o −149 / u +120 | 1 |
| Jackson LaCombeD · ANA @ NYR | 1.82 | 53% | 28% | 12% | 25:48PP 3:57 | 3.9 | −2% | 1.5 · o +100 / u −120 | 1 |
| Anders LeeF · UTA vs PIT | 1.82 | 53% | 28% | 12% | 13:34PP 1:12 | 8.0 | −2% | 1.5 · o −140 / u +110 | 1 |
| Matvei MichkovF · PHI vs COL | 1.81 | 53% | 27% | 12% | 14:52PP 2:49 | 6.8 | +1% | 1.5 · o −150 / u +116 | 2 |
| Logan CooleyF · UTA vs PIT | 1.81 | 53% | 27% | 12% | 17:55PP 3:39 | 5.8 | −2% | 1.5 · o −161 / u +140 | 2 |
| Mikhail SergachevD · UTA vs PIT | 1.80 | 53% | 27% | 12% | 23:58PP 3:21 | 4.2 | −1% | 1.5 · o −138 / u +130 | 4 |
| Ivar StenbergF · SJS @ TOR | 1.80 | 53% | 27% | 12% | 15:47PP 3:13 | 5.5 | +3% | 1.5 · o −116 / u +100 | 1 |
| Jacob TroubaD · SJS @ TOR | 1.80 | 53% | 27% | 12% | 21:33 | 5.4 | +3% | 1.5 · o −114 / u −114 | 1 |
| Will CuylleF · NYR vs ANA | 1.80 | 53% | 27% | 12% | 15:31PP 1:19 | 6.9 | +2% | 1.5 · o −145 / u +130 | 3 |
| Darnell NurseD · SJS @ TOR | 1.77 | 52% | 26% | 11% | 20:38 | 5.6 | +3% | 1.5 · o −154 / u +125 | 3 |
| Christian DvorakF · PHI vs COL | 1.75 | 51% | 26% | 11% | 18:47PP 1:30 | 5.3 | +1% | 1.5 · o +100 / u −114 | 1 |
| Gabe PerreaultF · NYR vs ANA | 1.75 | 51% | 26% | 11% | 16:40PP 1:33 | 5.9 | +2% | 1.5 · o −125 / u +105 | 4 |
| Alex KillornF · ANA @ NYR | 1.75 | 51% | 26% | 11% | 16:23PP 1:10 | 6.6 | −2% | 1.5 · o −128 / u +110 | 1 |
| Mason MarchmentF · SJS @ TOR | 1.72 | 51% | 25% | 11% | 15:53PP 1:15 | 5.9 | +3% | 1.5 · o −122 / u −105 | 4 |
| T.J. HughesF · COL @ PHI | 1.70 | 50% | 25% | 10% | 13:27PP 3:52 | 6.7 | +0% | 1.5 · o −118 / u −110 | 2 |
| Tyler ToffoliF · SJS @ TOR | 1.70 | 50% | 25% | 10% | 12:52PP 1:24 | 7.0 | +4% | 1.5 · o −149 / u +120 | 2 |
| Tommy NovakF · PIT @ UTA | 1.68 | 49% | 24% | 10% | 15:33PP 2:34 | 6.0 | −6% | 1.5 · o +109 / u −141 | 1 |
| Sam MalinskiD · COL @ PHI | 1.66 | 49% | 24% | 10% | 16:08 | 6.3 | +0% | – | 2 |
| Lawson CrouseF · UTA vs PIT | 1.66 | 49% | 24% | 9% | 16:22 | 6.7 | −1% | 1.5 · o −108 / u −120 | 1 |
| Gavin McKennaF · TOR vs SJS | 1.66 | 49% | 23% | 9% | 13:41PP 1:54 | 6.5 | +2% | 1.5 · o −139 / u +110 | 1 |
| MacKenzie WeegarD · UTA vs PIT | 1.64 | 48% | 23% | 9% | 23:13 | 4.8 | −2% | 1.5 · o −115 / u −110 | 3 |
| Brent BurnsD · COL @ PHI | 1.58 | 46% | 22% | 8% | 16:09 | 6.5 | +0% | – | 1 |
| Alexander WennbergF · SJS @ TOR | 1.56 | 46% | 21% | 8% | 20:15PP 3:39 | 3.7 | +3% | – | 0 |
| Sean CouturierF · PHI vs COL | 1.56 | 46% | 21% | 8% | 17:43 | 5.4 | +1% | – | 2 |
| Porter MartoneF · PHI vs COL | 1.55 | 45% | 21% | 8% | 13:38PP 2:17 | 5.5 | +1% | 1.5 · o −123 / u +115 | 1 |
| Easton CowanF · TOR vs SJS | 1.55 | 45% | 21% | 8% | 15:11 | 6.0 | +2% | 1.5 · o −118 / u −105 | 2 |
| Michael BuntingF · PHI vs COL | 1.54 | 45% | 21% | 8% | 12:14PP 2:12 | 7.1 | +1% | 1.5 · o −105 / u −120 | 1 |
| Barrett HaytonF · UTA vs PIT | 1.51 | 44% | 20% | 7% | 14:06 | 6.5 | −2% | 1.5 · o +102 / u −132 | 2 |
How the projections work
- 1. How often he shoots
- For each strength state (5-on-5, power play, shorthanded, other), we take the shooter's unblocked attempts per 60 minutes and the share of them that hit the net, from every game in roughly the last 14 months. Recent games count more (the weight halves every 8 months), and both numbers are shrunk toward the forward or defenseman average, so a hot week or a short history barely moves them. Missed shots recorded in a rink whose scorers log more misses than the league are scaled down using our arena scorer factors.
- 2. How much he will play
- Projected 5-on-5 time is a weighted average of his last 10 games, with the latest counting most. Power-play time is his share of his team's recent PP minutes times the PP time we expect tonight: the average of his team's recent PP time and the opponent's recent shorthanded time. The lineup is whoever dressed in the team's last game, or the forecast lineup when our matchup forecast has one.
- 3. Who he will face
- Every skater gets a 5-on-5 shot-suppression rating from a ridge regression on line changes (RAPM-style): unblocked attempts against while he is on the ice, adjusted for his teammates, the opponents and home ice, with every rating pulled toward zero. A shooter's matchup factor averages the opposing skaters' ratings, weighted by the minutes he is expected to share with each. Those minutes come from the matchup forecast (which knows the home coach has last change) when it is available; otherwise from each opponent's projected 5-on-5 time.
- 4. Power play and venue
- Power-play shots are scaled by the opponent's shots allowed per 60 while shorthanded, shrunk toward the league rate. Home teams shoot a little more at 5-on-5; the home and road split comes from the same regression.
- 5. From an average to a probability
- Shots in one game spread out more than a simple Poisson count, because ice time and role move from night to night. We use a negative binomial distribution whose extra spread was fit on last season's out-of-sample projections, then read off P(2+), P(3+) and P(4+) shots.
Last fit Oct 20: 1,534 games, 998 skaters rated.
How accurate is it?
Held-out test: Oct 7, 2025 – Apr 16, 2026
Every game in the test season was projected using only data from before that day, the way the live model works. Lineups were the players who dressed; ice time was projected, not known. Shots on goal are the official count (shootout attempts excluded), arena scorer factors came from the previous season, and the spread of the distribution was fit on the previous season. Lower log-loss is better. The live model scored 1.5332 against 1.5441 for a shots-per-game baseline given the same distribution (mean squared error 1.723 vs 1.757). Defender matchup ratings improved on the team-level adjustment by +0.00026 nats per projection (95% interval +0.00001 to +0.00053, resampling whole games); mean squared error 1.724 → 1.723. The gain also showed up in the tuning season. It is a real but very small effect. Even with perfect knowledge of who played against whom, the gain would be 0.0000: ice time and the shooter's own volume dominate.
| Model | Projections | Log-loss | Mean sq. error | Correlation |
|---|---|---|---|---|
| Shots per game, last 12 months | 47,230 | 1.5441 | 1.757 | 0.441 |
| Shooter rate × projected ice time | 47,230 | 1.5352 | 1.730 | 0.455 |
| + opponent team 5v5 and penalty kill | 47,230 | 1.5335 | 1.724 | 0.458 |
| + defender ratings by expected matchup (live model) | 47,230 | 1.5332 | 1.723 | 0.458 |
| Hindsight: actual matchups (upper bound, not usable) | 47,230 | 1.5332 | 1.723 | 0.458 |
Show as a table
| Line | Bin | n | Projected | Observed |
|---|---|---|---|---|
| 2+ SOG | 0–10% | 169 | 7.7% | 9.5% |
| 2+ SOG | 10–20% | 3,633 | 16.6% | 16.2% |
| 2+ SOG | 20–30% | 8,907 | 25.3% | 22.9% |
| 2+ SOG | 30–40% | 9,632 | 34.9% | 32.8% |
| 2+ SOG | 40–50% | 8,016 | 44.8% | 43.5% |
| 2+ SOG | 50–60% | 6,692 | 55.0% | 54.5% |
| 2+ SOG | 60–70% | 5,722 | 64.6% | 64.7% |
| 2+ SOG | 70–80% | 3,375 | 74.5% | 74.8% |
| 2+ SOG | 80–90% | 1,067 | 83.0% | 84.7% |
| 2+ SOG | 90–100% | 17 | 90.9% | 100.0% |
| 3+ SOG | 0–10% | 11,961 | 6.5% | 5.9% |
| 3+ SOG | 10–20% | 13,994 | 14.6% | 13.7% |
| 3+ SOG | 20–30% | 8,264 | 24.6% | 23.8% |
| 3+ SOG | 30–40% | 6,282 | 34.8% | 35.5% |
| 3+ SOG | 40–50% | 3,719 | 44.6% | 44.1% |
| 3+ SOG | 50–60% | 2,071 | 54.7% | 56.7% |
| 3+ SOG | 60–70% | 826 | 63.6% | 66.7% |
| 3+ SOG | 70–80% | 112 | 73.1% | 72.3% |
| 3+ SOG | 80–90% | 1 | 80.2% | 0.0% |
| 4+ SOG | 0–10% | 30,086 | 4.1% | 3.8% |
| 4+ SOG | 10–20% | 9,863 | 14.5% | 14.8% |
| 4+ SOG | 20–30% | 4,442 | 24.3% | 24.4% |
| 4+ SOG | 30–40% | 2,020 | 34.6% | 34.6% |
| 4+ SOG | 40–50% | 695 | 43.7% | 44.7% |
| 4+ SOG | 50–60% | 116 | 53.6% | 57.8% |
| 4+ SOG | 60–70% | 8 | 61.8% | 75.0% |
This season so far
3,616 projections across 106 games through Oct 20: 1.54 expected SOG per skater against 1.54 actual.
Show as a table
| Line | Bin | n | Projected | Observed |
|---|---|---|---|---|
| 2+ SOG | 0–10% | 22 | 8.7% | 0.0% |
| 2+ SOG | 10–20% | 246 | 16.4% | 17.5% |
| 2+ SOG | 20–30% | 677 | 25.3% | 21.7% |
| 2+ SOG | 30–40% | 825 | 34.7% | 35.9% |
| 2+ SOG | 40–50% | 641 | 44.8% | 48.0% |
| 2+ SOG | 50–60% | 523 | 54.7% | 50.9% |
| 2+ SOG | 60–70% | 397 | 65.0% | 63.7% |
| 2+ SOG | 70–80% | 223 | 74.1% | 78.0% |
| 2+ SOG | 80–90% | 62 | 82.2% | 79.0% |
| 3+ SOG | 0–10% | 868 | 6.5% | 6.8% |
| 3+ SOG | 10–20% | 1,181 | 14.3% | 14.2% |
| 3+ SOG | 20–30% | 683 | 24.6% | 24.7% |
| 3+ SOG | 30–40% | 422 | 34.7% | 31.8% |
| 3+ SOG | 40–50% | 290 | 44.5% | 46.9% |
| 3+ SOG | 50–60% | 120 | 54.8% | 55.8% |
| 3+ SOG | 60–70% | 51 | 63.0% | 72.5% |
| 3+ SOG | 70–80% | 1 | 71.1% | 0.0% |
| 4+ SOG | 0–10% | 2,390 | 4.1% | 4.4% |
| 4+ SOG | 10–20% | 709 | 14.1% | 12.7% |
| 4+ SOG | 20–30% | 365 | 24.2% | 23.6% |
| 4+ SOG | 30–40% | 108 | 35.3% | 41.7% |
| 4+ SOG | 40–50% | 43 | 43.1% | 51.2% |
| 4+ SOG | 50–60% | 1 | 51.9% | 0.0% |
FAQ
How are NHL shots on goal projections calculated?
Expected SOG = projected ice time at each strength × the shooter's shrunk shots-per-60 at that strength × a matchup factor. The matchup factor comes from the shot-suppression ratings of the opposing skaters he is expected to face at 5-on-5, and from the opponent's penalty kill on the power play. The probabilities come from a negative binomial distribution fit on last season.
Are these betting picks?
No. These are model projections, not bets. The table shows the sportsbook shots line and best prices from up to five US books for context. Since we started logging our projections against those lines before each game (October 2026), the books have been about as accurate as the model on shots on goal, which is not an edge once the bookmaker margin is paid. A 60% projection still misses four times in ten, and the calibration section shows how the probabilities have held up.
How accurate are the projections?
We test the model the way it is used: for every game of a full held-out season, it only sees data from before that day. The methodology section on this page shows the log-loss against a simple shots-per-game baseline and a calibration chart. When we say 40%, it should happen about 40% of the time.
Is this the same SOG number as the daily projections table?
Yes. Tonight's shots on goal and time on ice in the daily fantasy projections table come from this model, so a skater shows the same expected SOG on both pages. On the first graded nights of the season it beat the provider projection it replaced on squared error, log-loss and correlation with actual shots.
Does the opposing defense pair really matter?
Somewhat, and less than ice time and the shooter's own volume. The page reports how much the matchup factor improves accuracy over a team-level adjustment, and how repeatable the defender ratings are from one half of the games to the other. Most matchup factors land between 0.9 and 1.1.
When do the projections update?
Overnight, after the previous night's games, and again during the day as lineups settle. Players who did not dress in their team's last game are left out until they do, so check confirmed lines before puck drop.
Why is a player I expected missing?
The lineup comes from the team's most recent game (or the matchup forecast when it has one). A player returning from injury or a healthy scratch is not projected until he dresses again.