Frozen Tool Forensics: Home Sweet Home

Chris Kane

2022-03-18

When considering fantasy, I have never put much weight into home ice advantage. Not because I believe it doesn't exist, it clearly does, home teams have a better winning percentage on average. There are literal rules embedded in the game that support the home team (on line changes, faceoffs), plus all of the unquantified factors of sleeping in your own bed, familiar routines and the support of the crowd (hopefully). That doesn't even take into account the unconscious biases that see home teams get more power-plays and scorekeeper effects that tend to boost the home team's shot, hit, and block counts.

All things being equal, it makes sense that a player's fantasy value might be higher at home with a greater potential for power-plays and slightly inflated counting stats. That being said, I have never really found that "all things are equal" and in the examples where I really might use this information (sit/start decisions, short streams etc.) I find that the massive randomness inherent in hockey seems to have a much larger impact than the home-ice advantage.

Thanks to the guys over on Keeping Karlsson, I was recently alerted to the curious case of Samuel Bennett. He has played 27 games at home and 23 games away this season. As of March 16, he has 28 points at home (an 85 full season pace), and eight points in away games (for a 30 point pace). He is shooting 4.22 times per game at home, and 2.52 times when away and is putting up .24 power-play points per game at home (about 20 points full season), and .043 power-play points per game at home (about a 3.5-point pace). This was wild to me – a huge home/away difference that seems really to fly in the face of the small effects we might otherwise see.

So that got me wondering, are there other examples of this this season?

It should come as no surprise to anyone that over at Frozen Tools you can pretty easily search for these splits. Pick your time period and you can grab the Home/Away report and it will give you all players’ production (goals, assists, points, power-play goals and points, shots, hits, and penalty minutes) at home and away. For the purposes of this article, I exported the report, selected a few columns to focus on (points, power-play points, and shots), and put them at a per-game level for easy comparison.

On average, and not shockingly, players perform better in these categories at home. The list included some 800 players so the per-game numbers end up being pretty small, but the difference is clear. NHL players on average put up .071 shots per game more at home, score .0325 points at home, and .018 power-play points. League wide, those are pretty small impacts: about seven shots, three and a half points, and one and a half power-play points. Most leagues though don't cover 800 players, closer to maybe 250. Based on those 250 likely rostered players we are talking about an average difference of about .1 points per game, .05 power-play points, and .13 shots per game. That means if all 82 games were played at home, players on average would see eight more points, four more power-play points and about 11 more shots than if they were all away games.

Okay that's great and all, but who is the best at home? Well, there are actually 20 players who are scoring at a .5 points per game rate or better (that means if all 82 games were at home these players would be scoring at least 40 points better than if all the games were away) but here are the top five.

  Home Away Change
NameTeamGPPTS/PPPP/GSOG/G GPPTS/PPPP/GSOG/G Δ PTS/PΔ PPP/GΔ SOG/G
MAX PACIORETTYVGK111.640.454.73 180.610.2223.00 1.030.231.73
MARK STONEVGK161.380.251.94 120.500.0001.83 0.880.250.10
JADEN SCHWARTZSEA161.060.192.69 180.220.0002.61 0.840.190.08
SAM BENNETTFLA271.040.264.22 230.350.0432.52 0.690.221.70
KIRILL KAPRIZOVMIN241.630.294.08 331.030.3333.21 0.59-0.040.87

The above table contains players per game rates for points, power-play points, and shots for home games, away games, and then the difference between the two. For all of the tables, players have had to have at least five games both at home and away.

We can see that Max Pacioretty has been operating at a full point-per-game rate higher at home. He, plus Jaden Schwartz, and Mark Stone are somewhat exceptions here as they have played fewer games than most of the other players with a lot of injury time. And what do you know? There is Sam Bennett – he leads players who haven't lost significant time to injury. It was a bit of a surprise to see Kirill Kaprizov here, but then again, I haven't really been following the Wild closely enough to have strong expectations.

Given there tend to be more power-play opportunities at home, it shouldn't be much of a surprise that players tend to score more power-play points (and therefore points) at home. Like with total points there are 20 players who are scoring more than .25 power-play points better at home (that is a 20 power-point full season difference).

  Home Away Change
NameTeamGPPTS/PPPP/GSOG/G GPPTS/PPPP/GSOG/G Δ PTS/PΔ PPP/GΔ SOG/G
BRYAN RUSTPIT201.450.703.60 190.950.2112.89 0.500.490.71
BRAD MARCHANDBOS251.200.683.08 241.170.2923.54 0.030.39-0.46
SIDNEY CROSBYPIT231.300.652.91 261.120.2692.88 0.190.380.03
VINNI LETTIERIANA90.560.441.78 120.250.0831.75 0.310.360.03
RASMUS DAHLINBUF310.710.422.23 270.560.0742.19 0.150.350.04
EVANDER KANEEDM90.890.334.22 120.670.0002.67 0.220.331.56

Vinni Lettieri and Evander Kane have low game count, but Bryan Rust is a pretty interesting name here. Rust has been a pretty boom or bust player this season. I don't mean that he has disappeared for long periods of time, just that he has had a number of big games with 16 multipoint games in his 39 games. That includes several multi-point power-play games – most of which happen to be at home.

On the shot level we have 19 players who are putting up more than one shot per game better at home.

  Home Away Change
NameTeamGPPTS/PPPP/GSOG/G GPPTS/PPPP/GSOG/G Δ PTS/PΔ PPP/GΔ SOG/G
NATHAN MACKINNONCOL201.400.406.25 261.350.5383.81 0.05-0.142.44
ALEX BARRE-BOULETT.B70.570.142.00 90.220.0000.22 0.350.141.78
MAX PACIORETTYVGK111.640.454.73 180.610.2223.00 1.030.231.73
SAM BENNETTFLA271.040.264.22 230.350.0432.52 0.690.221.70
TYLER JOHNSONCHI70.140.002.14 70.290.2860.57 -0.14-0.291.57
EVANDER KANEEDM90.890.334.22 120.670.0002.67 0.220.331.56

This list contains some familiar names, and maybe it isn't that surprising. Pacioretty, Bennett and Kane are here and on the other lists for points and power-play points respectively. Nathan MacKinnon, though – almost two and a half shots per game better at home (6.25 total!) There are plenty of players who don't even get 2.5 shots per game.

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As I stated above, so much of the game-by-game production is random. It is hard to know whether this is all just observed correlation and happenstance or if this is something reasonably predictive. To better answer that we would need to track specific players over time and see if they are repeatedly better than average in one location. At this stage though maybe game location could be your sit/start tie breaker for players like Bennett, Kaprizov, Pacioretty, Rust and Kane.

Just for fun though – here are the players who are better at away games. There are many fewer of them, and it seems a bit more likely that these just represent noise rather than trends.

  Home Away Change
NameTeamGPPTS/PPPP/GSOG/G GPPTS/PPPP/GSOG/G Δ PTS/PΔ PPP/GΔ SOG/G
MICHAEL BUNTINGTOR300.500.071.90 301.070.0672.40 -0.570.00-0.50
JAKE GUENTZELPIT280.820.393.46 271.370.2593.52 -0.550.13-0.05
JAKE BEANCBJ240.130.041.17 210.620.0481.62 -0.49-0.01-0.45
T.J. OSHIEWSH140.500.211.21 130.920.3082.00 -0.42-0.09-0.79
PIERRE ENGVALLTOR300.200.031.93 260.620.0772.08 -0.42-0.04-0.14

And here are players who have been shooting better during away games.

  Home Away Change
NameTeamGPPTS/PPPP/GSOG/G GPPTS/PPPP/GSOG/G Δ PTS/PΔ PPP/GΔ SOG/G
DANIEL SPRONGWSH240.170.001.46 200.450.0002.95 -0.280.00-1.49
MITCHELL MARNERTOR271.220.372.44 241.290.2503.63 -0.070.12-1.18
PHILIPPE MYERSNSH110.090.000.36 150.130.0001.53 -0.040.00-1.17
MIKHAIL SERGACHEVT.B260.420.121.27 290.690.1032.38 -0.270.01-1.11
JACK EICHELVGK60.670.173.17 80.630.2504.25 0.04-0.08-1.08

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2 Comments

  1. Dobber 2022-03-18 at 12:44

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