Home/Road plus-minus splits

[overpass]

I've compiled the home/road splits in plus-minus of players since 1987-88.

Plus-minus is affected by the situations in which coaches play players. And the fact that home teams get last change means that coaches have to use players differently at home and on the road.

I'll post the numbers in a day or so. But before I post them, can I ask for some guesses from the bright minds here at HOH? Just to see what our intuition and experience as hockey fans comes up with, before seeing the numbers.

1. Which longtime players/stars since 1987-88 had the biggest positive differential between home plus-minus and road plus-minus?

2. Which longtime players/stars since 1987-88 had the smallest positive (or largest negative) differential between home plus-minus and road plus-minus?

I'm looking for guesses uninformed by the actual numbers here, so please don't look them up and post them.

Click to read more...

 

[tarheelhockey]

I'm going to guess that guys like Pronger, Chara and Stevens have the largest. Their coaches bent over backwards to get them matched up against the right opponents, so one would expect the home-road line change rules to have a greater impact on them. Their numbers should still be quite good, but perhaps less good.

Smallest? No idea. I bet it's somebody random.

 

[TheDevilMadeMe]

When did all the rinks become standard size? I would imagine that skilled forwards with small home arenas might have better plus/minuses on the road.

I want to agree with tarheel about shutdown defensemen, but I know at least the Devils would often purposely ice the puck to make a change if Stevens wasn't out there when they wanted him on the road. So I'm curious how different it could be.

 

[LeBlondeDemon10]

Coffey, Gretzky, Lemieux

Carbonneau, Stevens, Yzerman

 

[plusandminus]

I'm going to guess that guys like Pronger, Chara and Stevens have the largest. Their coaches bent over backwards to get them matched up against the right opponents, so one would expect the home-road line change rules to have a greater impact on them. Their numbers should still be quite good, but perhaps less good.

Smallest? No idea. I bet it's somebody random.

Players in general usually have better stats at home.

--Smallest (better stats on the road compared to home)
Thus, in order to have as good stats away as at home means that a player probably have had relatively hard matchups (or whatever) at home, while having easier on the road.

--Largest (better stats at home compared to on the road
The opposite ones obviously are this season's Ryan Nugent Hopkins, who at home may have played in a relatively sheltered environment, as opposed to on the road, and thus may have "easy" time. These players may need certain conditions to be met in order to shine, which can often only be fulfilled at home, where their coach can match them against the opponents that suits them best.

 

[reckoning]

I say Bourque and Lidstrom will have little or no difference between their home and road records. They play all situations regardless of where the game is.

I also guess that forwards will generally have a higher disparity than defencemen.

 

[Sadekuuro]

I say Bourque and Lidstrom will have little or no difference between their home and road records. They play all situations regardless of where the game is.

While I agree that this seems likely on the whole, this year Lidstrom is +22 at home and +1 on the road, reflecting the Wings' excellent home performances and their struggles on the road. But this kind of split is atypical for Detroit (and counterbalanced by last season, when they dominated on the road).

 

[overpass]

Here are the results for defencemen. I'll post forwards later since I haven't quite finished them.

There's still a fair bit of variation in these numbers, which makes it difficult to draw firm conclusions on any individual player. But maybe we can pick out some trends from the overall picture.

Player | GP | Home+/- | Road+/- | Diff+/- | Per-82 | EV% | PP% | SH%
Larry Murphy | 1064 | 158 | -20 | 178 | 14 | 40% | 66% | 31%
Phil Housley | 1113 | 62 | -118 | 180 | 13 | 39% | 87% | 11%
Paul Coffey | 877 | 78 | -55 | 133 | 12 | 44% | 80% | 26%
Jamie Macoun | 808 | 98 | -23 | 121 | 12 | 39% | 10% | 51%
Al MacInnis | 1126 | 236 | 72 | 164 | 12 | 40% | 87% | 43%
Tommy Albelin | 952 | 94 | -42 | 136 | 12 | 29% | 25% | 28%
Gerald Diduck | 827 | 99 | -16 | 115 | 11 | 32% | 16% | 34%
Fredrik Olausson | 950 | 52 | -77 | 129 | 11 | 33% | 62% | 23%
Brian Leetch | 1205 | 93 | -68 | 161 | 11 | 45% | 87% | 50%
Scott Stevens | 1250 | 243 | 78 | 165 | 11 | 42% | 38% | 62%
Alexei Zhitnik | 1085 | 41 | -94 | 135 | 10 | 38% | 55% | 37%
Jaroslav Spacek | 861 | 76 | -31 | 107 | 10 | 34% | 47% | 35%
Karlis Skrastins | 832 | 29 | -74 | 103 | 10 | 34% | 3% | 51%
Nicklas Lidstrom | 1539 | 318 | 134 | 184 | 10 | 40% | 72% | 52%
James Patrick | 1040 | 101 | -13 | 114 | 9 | 31% | 38% | 35%
Chris Chelios | 1453 | 252 | 93 | 159 | 9 | 38% | 51% | 59%
Pavel Kubina | 941 | 0 | -102 | 102 | 9 | 36% | 50% | 36%
Sylvain Cote | 1035 | 84 | -27 | 111 | 9 | 36% | 34% | 35%
Eric Desjardins | 1143 | 159 | 39 | 120 | 9 | 39% | 52% | 47%
Sergei Zubov | 1068 | 130 | 18 | 112 | 9 | 42% | 82% | 33%
Cory Sarich | 855 | 40 | -49 | 89 | 9 | 29% | 2% | 37%
Dave Manson | 1040 | 50 | -54 | 104 | 8 | 37% | 32% | 35%
Garry Galley | 974 | 55 | -41 | 96 | 8 | 34% | 51% | 31%
Grant Ledyard | 840 | 44 | -37 | 81 | 8 | 30% | 31% | 26%
Bret Hedican | 1039 | 38 | -61 | 99 | 8 | 35% | 23% | 34%
Petr Svoboda | 831 | 114 | 38 | 76 | 7 | 32% | 40% | 30%
Rob Blake | 1270 | 56 | -60 | 116 | 7 | 37% | 66% | 50%
Scott Hannan | 872 | 48 | -31 | 79 | 7 | 36% | 12% | 45%
Kevin Hatcher | 998 | 42 | -47 | 89 | 7 | 42% | 61% | 52%
Jassen Cullimore | 812 | 13 | -58 | 71 | 7 | 29% | 5% | 36%
Todd Gill | 921 | -7 | -87 | 80 | 7 | 34% | 25% | 30%
Wade Redden | 994 | 124 | 38 | 86 | 7 | 37% | 50% | 39%
Sergei Gonchar | 1098 | 66 | -28 | 94 | 7 | 39% | 76% | 21%
Patrice Brisebois | 1009 | 43 | -42 | 85 | 7 | 34% | 51% | 32%
Roman Hamrlik | 1350 | 27 | -86 | 113 | 7 | 39% | 57% | 36%
Sylvain Lefebvre | 945 | 93 | 15 | 78 | 7 | 33% | 8% | 43%
Don Sweeney | 1115 | 102 | 10 | 92 | 7 | 34% | 10% | 39%
Darryl Sydor | 1291 | 63 | -42 | 105 | 7 | 33% | 40% | 25%
Jyrki Lumme | 985 | 78 | -2 | 80 | 7 | 35% | 48% | 37%
Ken Daneyko | 1148 | 94 | 1 | 93 | 7 | 30% | 2% | 43%
Ulf Samuelsson | 881 | 107 | 36 | 71 | 7 | 35% | 16% | 43%
Adam Foote | 1154 | 96 | 3 | 93 | 7 | 36% | 17% | 52%
Scott Lachance | 819 | -5 | -71 | 66 | 7 | 34% | 15% | 42%
Stephane Quintal | 1037 | -3 | -86 | 83 | 7 | 36% | 13% | 41%
Murray Baron | 988 | 10 | -67 | 77 | 6 | 32% | 3% | 44%
Chris Phillips | 990 | 74 | 0 | 74 | 6 | 34% | 16% | 40%
Bryan Marchment | 926 | 49 | -18 | 67 | 6 | 34% | 5% | 25%
Steve Duchesne | 1038 | 77 | 3 | 74 | 6 | 36% | 65% | 31%
Kimmo Timonen | 937 | 50 | -16 | 66 | 6 | 32% | 75% | 37%
Scott Niedermayer | 1263 | 127 | 40 | 87 | 6 | 39% | 64% | 40%
Aaron Ward | 839 | 8 | -49 | 57 | 6 | 31% | 4% | 37%
Robyn Regehr | 869 | 38 | -21 | 59 | 6 | 35% | 15% | 49%
Gary Suter | 997 | 96 | 29 | 67 | 6 | 37% | 81% | 31%
Greg de Vries | 878 | 41 | -18 | 59 | 6 | 35% | 6% | 31%
Mattias Norstrom | 903 | 34 | -26 | 60 | 5 | 33% | 8% | 49%
Adrian Aucoin | 1047 | 56 | -13 | 69 | 5 | 34% | 53% | 41%
Curtis Leschyshyn | 1033 | 8 | -60 | 68 | 5 | 32% | 17% | 37%
Derek Morris | 986 | 14 | -50 | 64 | 5 | 35% | 46% | 36%
Keith Carney | 1018 | 115 | 49 | 66 | 5 | 35% | 7% | 43%
Terry Carkner | 806 | 25 | -26 | 51 | 5 | 32% | 16% | 45%
Mathieu Schneider | 1289 | 73 | -7 | 80 | 5 | 37% | 69% | 31%
Ray Bourque | 1032 | 149 | 85 | 64 | 5 | 42% | 88% | 62%
Joe Reekie | 843 | 99 | 47 | 52 | 5 | 35% | 3% | 42%
Derian Hatcher | 1045 | 68 | 6 | 62 | 5 | 41% | 18% | 55%
Ed Jovanovski | 1062 | -6 | -69 | 63 | 5 | 38% | 46% | 25%
Calle Johansson | 1109 | 61 | -4 | 65 | 5 | 33% | 47% | 45%
Glen Wesley | 1457 | 74 | -8 | 82 | 5 | 32% | 39% | 43%
Brendan Witt | 890 | -21 | -70 | 49 | 5 | 32% | 1% | 47%
Tom Poti | 808 | 45 | 1 | 44 | 4 | 35% | 47% | 42%
Luke Richardson | 1417 | -22 | -97 | 75 | 4 | 31% | 3% | 38%
Craig Ludwig | 880 | 58 | 12 | 46 | 4 | 32% | 1% | 51%
Mattias Ohlund | 909 | 19 | -25 | 44 | 4 | 39% | 42% | 45%
Bob Rouse | 850 | -1 | -42 | 41 | 4 | 34% | 7% | 41%
Marc Bergevin | 994 | -11 | -56 | 45 | 4 | 30% | 5% | 44%
Bryan Mccabe | 1135 | 42 | -8 | 50 | 4 | 38% | 55% | 41%
Jason Smith | 1008 | 34 | -8 | 42 | 3 | 34% | 1% | 45%
Doug Bodger | 851 | 5 | -26 | 31 | 3 | 32% | 60% | 44%
Ruslan Salei | 917 | 3 | -28 | 31 | 3 | 35% | 20% | 39%
Jay Mckee | 802 | 41 | 14 | 27 | 3 | 31% | 5% | 47%
Hal Gill | 1034 | 37 | 5 | 32 | 3 | 32% | 0% | 50%
Sean O'Donnell | 1204 | 64 | 27 | 37 | 3 | 31% | 7% | 43%
Dave Ellett | 891 | -11 | -38 | 27 | 2 | 36% | 57% | 35%
Craig Rivet | 923 | 9 | -13 | 22 | 2 | 31% | 21% | 31%
Teppo Numminen | 1372 | 44 | 12 | 32 | 2 | 34% | 48% | 46%
Darius Kasparaitis | 863 | 28 | 11 | 17 | 2 | 32% | 5% | 38%
Chris Pronger | 1167 | 102 | 81 | 21 | 1 | 39% | 67% | 54%
Gord Murphy | 862 | -34 | -49 | 15 | 1 | 35% | 43% | 42%
Zdeno Chara | 968 | 79 | 64 | 15 | 1 | 40% | 42% | 52%
Tomas Kaberle | 947 | 14 | 4 | 10 | 1 | 37% | 69% | 35%
Sandis Ozolinsh | 875 | -18 | -26 | 8 | 1 | 41% | 68% | 19%
Sean Hill | 876 | -19 | -27 | 8 | 1 | 34% | 40% | 37%
Bill Houlder | 846 | 15 | 16 | -1 | 0 | 34% | 27% | 44%
Brian Rafalski | 833 | 88 | 90 | -2 | 0 | 38% | 67% | 22%
Lyle Odelein | 1056 | 5 | 24 | -19 | -1 | 33% | 16% | 27%
Eric Weinrich | 1157 | 15 | 41 | -26 | -2 | 36% | 34% | 37%
Total | 96137 | 5731 | -1371 | 7102 | 6 | 35% | 36% | 39%

It's sorted by (Home plus-minus - road plus-minus)/(career games played)*82.

I've included EV%, PP%, and SH%, to help eyeball the table to see what types of players were more successful at home, or more successful on the road. They are estimates based on on-ice goals as a percentage of the team's goals on a per-game basis.

I originally ran these numbers because I checked Larry Murphy's splits and thought they looked high, but had no way to put it into perspective. It turns out that Murphy's home/road splits were pretty large.

Interesting to see Lidstrom with the largest absolute difference (at the moment when I ran the numbers, anyway) and near the top on a per-game basis.

Tarheelhockey guessed Pronger, Chara, and Stevens would have large differentials. Stevens did, Pronger and Chara didn't.

Leblondedemon10 named Coffey as someone who would have a large split. Correct.

Bourque and Lidstrom? Bourque's split was pretty average. Lidstrom's was large.

 

[TheDevilMadeMe]

I really don't know what can be interpreted from those numbers. The guys at the top are a mix of offensive defensemen, defensive defensemen, superstars, and bottom pairing defensemen.

Seems almost random.

Can you find a pattern in it?

 

[TheDevilMadeMe]

This may be helpful, but probably not - Tommy Albelin was Scott Stevens' even strength partner for a little while in the late 90s (though usually he was a bottom pairing guy).

 

[overpass]

I really don't know what can be interpreted from those numbers. The guys at the top are a mix of offensive defensemen, defensive defensemen, superstars, and bottom pairing defensemen.

Seems almost random.

Can you find a pattern in it?

Yeah, that's partly why I posted it here - and also why I asked for opinions before posting.

Some of it is random variation. The rest may come down to individual coaching strategies, which are difficult to find overall trends in.

There are a few offence-first guys at the top, in terms of being more successful at home. Murphy, Housley, Coffey. MacInnis (and his partner Macoun, who was not offence-first.) Olausson. Leetch.

But then why were Ozolinsh and Rafalski almost equally good on the road? Rafalski is especially strange, considering his most frequent partners have been Stevens and Lidstrom.

Pronger, Chara, and Gill doing almost as well on the road as at home may be a trend.

Correlations between the per-82 diff and some different numbers:
EV% - 0.21
PP% - 0.20
SH% - -0.08

Meaning that power play guys did slightly better at home and penalty killers did slightly worse at home, relative to each other.

 

[plusandminus]

If I remember right, power plays are more common for the home team. Thus, players that are used a lot on PP are unfavoured +/- wise, as they risk allowing more goals while playing PP at home than on the road. The opposite with players used much more on the PK than on the PP, who gets more PK time on the road, which is good for their stats +/- wise. (I'm not sure whether that is cancelled out by other factors, though. It seems as if it does, if I read the results right.)

Interesting listing, by the way. What data did you use? Was it season summaries or game by game data?

(And again, I hope it's known that the estimated ES%, PP% and SH% aren't very reliable. If I remember right, they are on average wrong by 6-7 percentage units, so 20 % may be 13 % or 27 %, or something closer to, or even farther away from, 20 %. If using them to rank defencemen players within a team based on on estimated ice time, they are often wrong too, if so usually by one spot but sometimes more. No harm meant, I just still think it would be better to mention it.)

 

[overpass]

If I remember right, power plays are more common for the home team. Thus, players that are used a lot on PP are unfavoured +/- wise, as they risk allowing more goals while playing PP at home than on the road. The opposite with players used much more on the PK than on the PP, who gets more PK time on the road, which is good for their stats +/- wise. (I'm not sure whether that is cancelled out by other factors, though. It seems as if it does, if I read the results right.)

Interesting listing, by the way. What data did you use? Was it season summaries or game by game data?

(And again, I hope it's known that the estimated ES%, PP% and SH% aren't very reliable. If I remember right, they are on average wrong by 6-7 percentage units, so 20 % may be 13 % or 27 %, or something closer to, or even farther away from, 20 %. If using them to rank defencemen players within a team based on on estimated ice time, they are often wrong too, if so usually by one spot but sometimes more. No harm meant, I just still think it would be better to mention it.)

The data is from hockey-reference.com's splits. It's easily available for each individual player, I just compiled the list.

Could you post a link to your work indicating that the estimated ES%, PP%, and SH% are wrong by an average of 6-7 percentage points? I think your statement is completely wrong. I've never seen you test those numbers on a career level in the past, only on a single season level.

 

[overpass]

Here's the forward data. The list isn't complete, I didn't get to running all the names. But it should give a pretty good idea of whether there is something there.

Player | GP | Home+/- | Road+/- | Diff+/- | Per-82 | EV% | PP% | SH%
Player | GP | Home+/- | Road+/- | Diff+/- | Per-82 | EV% | PP% | SH%
Mario Lemieux | 700 | 161 | -18 | 179 | 21 | 45% | 94% | 34%
Wayne Gretzky | 855 | 71 | -65 | 136 | 13 | 44% | 79% | 28%
Luc Robitaille | 1352 | 146 | -56 | 202 | 12 | 33% | 59% | 4%
Bryan Smolinski | 1056 | 95 | -49 | 144 | 11 | 30% | 37% | 23%
Doug Gilmour | 1162 | 141 | -13 | 154 | 11 | 35% | 64% | 34%
Daniel Alfredsson | 1056 | 138 | 0 | 138 | 11 | 34% | 70% | 20%
Gary Roberts | 1192 | 188 | 35 | 153 | 11 | 31% | 38% | 11%
Claude Lemieux | 1120 | 81 | -61 | 142 | 10 | 29% | 46% | 13%
Miroslav Satan | 1050 | 75 | -55 | 130 | 10 | 31% | 53% | 16%
Theoren Fleury | 1084 | 137 | 8 | 129 | 10 | 36% | 64% | 24%
Sergei Fedorov | 1249 | 204 | 57 | 147 | 10 | 32% | 58% | 31%
Doug Weight | 1238 | 42 | -100 | 142 | 9 | 31% | 68% | 9%
Joe Sakic | 1378 | 87 | -57 | 144 | 9 | 38% | 79% | 25%
Paul Kariya | 989 | 67 | -36 | 103 | 9 | 38% | 78% | 16%
Martin Straka | 954 | 83 | -16 | 99 | 9 | 33% | 48% | 15%
Mike Modano | 1499 | 133 | -19 | 152 | 8 | 33% | 62% | 25%
Brian Rolston | 1186 | 90 | -30 | 120 | 8 | 26% | 49% | 31%
Mark Recchi | 1652 | 82 | -82 | 164 | 8 | 35% | 65% | 17%
Jaromir Jagr | 1273 | 202 | 83 | 119 | 8 | 41% | 68% | 8%
Martin Gelinas | 1273 | 84 | -32 | 116 | 7 | 27% | 19% | 12%
Peter Bondra | 1081 | 86 | -12 | 98 | 7 | 33% | 56% | 14%
Alexander Mogilny | 990 | 85 | -4 | 89 | 7 | 35% | 60% | 13%
Kirk Muller | 1113 | 4 | -92 | 96 | 7 | 30% | 42% | 28%
Bill Guerin | 1263 | 79 | -28 | 107 | 7 | 30% | 51% | 3%
Ryan Smyth | 1069 | 32 | -58 | 90 | 7 | 33% | 62% | 11%
Trevor Linden | 1382 | 26 | -90 | 116 | 7 | 28% | 46% | 33%
Jason Arnott | 1172 | 89 | -9 | 98 | 7 | 33% | 59% | 5%
Ray Whitney | 1147 | 4 | -91 | 95 | 7 | 31% | 64% | 6%
Vyacheslav Kozlov | 1182 | 96 | 0 | 96 | 7 | 29% | 45% | 8%
Dave Andreychuk | 1297 | 58 | -47 | 105 | 7 | 28% | 62% | 14%
Brett Hull | 1264 | 63 | -39 | 102 | 7 | 37% | 71% | 16%
Guy Carbonneau | 923 | 91 | 17 | 74 | 7 | 24% | 4% | 50%
Mats Sundin | 1346 | 90 | -17 | 107 | 7 | 35% | 64% | 24%
Ray Ferraro | 1058 | -11 | -93 | 82 | 6 | 31% | 42% | 1%
Scott Young | 1181 | 25 | -65 | 90 | 6 | 26% | 52% | 15%
Adam Oates | 1223 | 76 | -17 | 93 | 6 | 39% | 76% | 29%
Pierre Turgeon | 1294 | 117 | 22 | 95 | 6 | 33% | 62% | 12%
Geoff Sanderson | 1104 | -11 | -89 | 78 | 6 | 28% | 43% | 7%
Patrick Marleau | 1077 | 52 | -22 | 74 | 6 | 33% | 51% | 13%
Mark Messier | 1186 | 83 | 4 | 79 | 5 | 35% | 63% | 44%
Shayne Corson | 1098 | 54 | -17 | 71 | 5 | 31% | 46% | 27%
Joe Thornton | 995 | 106 | 42 | 64 | 5 | 36% | 66% | 11%
Brendan Shanahan | 1524 | 124 | 27 | 97 | 5 | 32% | 59% | 14%
Peter Forsberg | 708 | 141 | 97 | 44 | 5 | 36% | 70% | 22%
Steve Yzerman | 1223 | 159 | 85 | 74 | 5 | 36% | 67% | 42%
Ron Francis | 1313 | 60 | -17 | 77 | 5 | 34% | 71% | 27%
Alexei Kovalev | 1302 | 23 | -53 | 76 | 5 | 33% | 57% | 11%
Michal Handzus | 844 | 36 | -13 | 49 | 5 | 26% | 32% | 41%
Stu Barnes | 1136 | 20 | -44 | 64 | 5 | 28% | 34% | 27%
Pavel Datsyuk | 706 | 123 | 84 | 39 | 5 | 33% | 55% | 13%
Andrew Brunette | 1032 | -9 | -66 | 57 | 5 | 28% | 61% | 1%
Todd Marchant | 1195 | 23 | -43 | 66 | 5 | 24% | 13% | 47%
Scott Mellanby | 1358 | 16 | -59 | 75 | 5 | 27% | 45% | 3%
Keith Tkachuk | 1201 | 49 | -16 | 65 | 4 | 35% | 65% | 8%
John Leclair | 967 | 128 | 76 | 52 | 4 | 35% | 53% | 1%
Vincent Lecavalier | 978 | -31 | -81 | 50 | 4 | 35% | 63% | 10%
Joe Nieuwendyk | 1248 | 108 | 47 | 61 | 4 | 31% | 55% | 9%
Vincent Damphousse | 1298 | 39 | -24 | 63 | 4 | 32% | 58% | 20%
Steve Thomas | 1074 | 50 | -2 | 52 | 4 | 31% | 42% | 3%
Todd Bertuzzi | 1060 | 10 | -41 | 51 | 4 | 33% | 48% | 1%
Jarome Iginla | 1106 | 56 | 3 | 53 | 4 | 38% | 64% | 13%
Teemu Selanne | 1259 | 80 | 23 | 57 | 4 | 36% | 74% | 5%
Rod Brind'Amour | 1484 | 14 | -53 | 67 | 4 | 33% | 50% | 45%
Bobby Holik | 1314 | 87 | 28 | 59 | 4 | 26% | 32% | 8%
Glen Murray | 1009 | 29 | -15 | 44 | 4 | 33% | 39% | 10%
Markus Naslund | 1117 | 27 | -21 | 48 | 4 | 30% | 50% | 5%
Cliff Ronning | 1095 | 46 | 0 | 46 | 3 | 26% | 59% | 1%
Tony Amonte | 1174 | 72 | 24 | 48 | 3 | 32% | 50% | 21%
Radek Dvorak | 1118 | 17 | -23 | 40 | 3 | 28% | 19% | 26%
Owen Nolan | 1200 | 1 | -41 | 42 | 3 | 30% | 47% | 23%
Rick Tocchet | 931 | 40 | 8 | 32 | 3 | 34% | 56% | 7%
Dave Reid | 869 | 41 | 12 | 29 | 3 | 20% | 5% | 37%
Pat Verbeek | 1111 | 42 | 6 | 36 | 3 | 31% | 55% | 5%
Mike Peca | 864 | 45 | 21 | 24 | 2 | 27% | 32% | 44%
Shane Doan | 1165 | 3 | -26 | 29 | 2 | 31% | 46% | 11%
Alexei Yashin | 850 | -31 | -52 | 21 | 2 | 36% | 68% | 9%
Rob Niedermayer | 1153 | -48 | -75 | 27 | 2 | 26% | 29% | 28%
Adam Graves | 1152 | 0 | -25 | 25 | 2 | 29% | 35% | 27%
Kris Draper | 1157 | 46 | 26 | 20 | 1 | 20% | 2% | 34%
Jeremy Roenick | 1363 | 87 | 66 | 21 | 1 | 32% | 60% | 19%
Stephane Yelle | 991 | 10 | -3 | 13 | 1 | 19% | 5% | 41%
Craig Conroy | 1009 | 55 | 43 | 12 | 1 | 27% | 22% | 40%
Eric Lindros | 760 | 112 | 103 | 9 | 1 | 42% | 68% | 14%
Jay Pandolfo | 819 | 2 | 4 | -2 | 0 | 21% | 2% | 49%

 

[plusandminus]

Could you post a link to your work indicating that the estimated ES%, PP%, and SH% are wrong by an average of 6-7 percentage points? I think your statement is completely wrong. I've never seen you test those numbers on a career level in the past, only on a single season level.

Yes, I did it for a single seasons. I can post the results later.

Let's say a player factually plays SH 40 % of the time the team plays SH. Being on ice for 34 % of the SHGA indicate he has done better than team average, while being on ice for 46 % of the SHGA, indicates he's done worse than team average. To me that makes difference. According to your stats, the "worse than team average player" will be awarded with "46 %", while the "better than team average player" will be punished down to "34 %".


If combining more than one season, I think the error margins will be smaller. I can look into it later, if I have the data.
(I think I'm still missing situational seasonal icetimes and GF GA for players. For some sad reason, it seems factual seasonal player data for ESGF, ESGA, PPGF, PPGA, SHGF, SHGA is not to be found, and I don't like to make assumptions/estimations if can be avoided. I now use game by game data, from HSP and hockeydb combined with data from nhl.com. (I do want game by game data anyway, as I want to be able to distinguish EN situations from non-EN situtations, as well as see details as well as how combinations of players did when playing together.) It takes time and energy to get it into my database and then even more to correct errors and double check things.)

To get back to your percentages... Wouldn't it be great to know just how reliable they are? Wouldn't it be good to perhaps find ways to fine tune methods used for calculating them and other stats? Your frequent mention of "easy" and "hard" icetimes is one example, where it is being assumed that players with high SH percentages play against more difficult opposition (when playing SH) than those with low percentages. On the other hand, they probably also play with the best available teammates, which may in the overall context cancel things out. ?
Your tables with percentages and R-On / R-Off are pretty frequently used here on the board, and seem to be used to draw conclusions about players. I feel the need to sometimes point out some things about them. Even though it probably isn't appreciated here, I do think my intentions are good.

 

[plusandminus]

Forsberg leads all forwards on +/- on the road. Yzerman 2nd and Datsyuk 3rd.
Edit: I missed Eric Lindros, who is 1 st, followed by Forsberg, Yzerman and Datsyuk.

Any thoughts regarding "Sakic vs Forsberg"? Did Sakic seem to have gotten easier minutes? (I personally don't make that conclusion, as I think other things may affect the numbers too.)

 

[tarheelhockey]

Forsberg leads all forwards on +/- on the road. Yzerman 2nd and Datsyuk 3rd.

Any thoughts regarding "Sakic vs Forsberg"? Did Sakic seem to have gotten easier minutes? (I personally don't make that conclusion, as I think other things may affect the numbers too.)

All other things equal, wouldn't this actually mean that Forsberg was getting the easier matchups?

 

[overpass]

Forsberg leads all forwards on +/- on the road. Yzerman 2nd and Datsyuk 3rd.

Any thoughts regarding "Sakic vs Forsberg"? Did Sakic seem to have gotten easier minutes? (I personally don't make that conclusion, as I think other things may affect the numbers too.)

Actually, Eric Lindros was first in road plus-minus.

Regarding Sakic vs Forsberg, I think it is at least a piece of evidence in favour of Forsberg. It isn't conclusive, of course. Like you say there may be other things going on beyond matchups. Coaches can still control offensive/defensive zone faceoffs, linemates, etc.

 

[Roy S]

As it is, Lidstrom has the best +- on the road of the listed defenseman, even with his relatively large split. That is still very impressive. Bourque might have had a larger split in his younger days, but we don't have that data.

 

[overpass]

Coffey, Gretzky, Lemieux

Excellent guess!

Lemieux's splits were surprisingly large. Could it have been that travel took more of a toll on him than most players? Or was it the different matchups and coaching strategies?

 

[MadLuke]

Excellent guess!

Lemieux's splits were surprisingly large. Could it have been that travel took more of a toll on him than most players? Or was it the different matchups and coaching strategies?

Receiving team's and coaches of those type of players, have a matchup and strategy against them and it's easier to play specific player's when they are on the ice at home, because you have the last change up.

Also team's tend to have more penalty called for them at home (referee influenced by the crowd maybe), and this could me even more true for star's player. Maybe defensive team could abuse more the superstar's when they are on the road.

 

[LeBlondeDemon10]

Excellent guess!

Lemieux's splits were surprisingly large. Could it have been that travel took more of a toll on him than most players? Or was it the different matchups and coaching strategies?

The only theory I have is that those forwards or combination of forwards (I think we would need to look at line mates too) that typically do not back-check, get burned more on the road than at home. This goes for offensive defensemen too. This would be a result of the line match ups as offensive lines on the road would be playing against the home teams top checking line. Do checking lines score more at home? Maybe.