You can't draw that conclusion at all. I never said the most efficient player is the best offensive player. Nor can you say that the player that produces the most points is automatically the best offensive player. If you removed Yao from the team, that would force the role players to take a bigger role on the team (use more possessions), causing their efficiency to drop further, and the overall team efficiency would reduce significantly. Same thing (though, I'd imagine to a lesser extent) with McGrady. It's the combination of points produced, used possessions, and efficiency that you have to look at. Add a player that gets you 14.5 points/40 with 47% efficiency, he's simply not going to help an offense that much because of the lack of efficiency. I'd rather have a role player giving 12.3 points/40 with 59% efficiency. Because Hayes does not use up many possessions, that will require the other teammates on the floor to take on a slightly bigger role in the offense. Logically, one would conclude that their efficiency might decrease somewhat as a result. But if you look at the efficiency of the 5-man unit as a whole, is it reduced compared to when Howard is in there? I doubt it. For instance, last year with Hayes on the court, the team offensive efficiency was 105.3 points per 100 possessions. With Howard, it was a pathetic 100.3 points per 100 possessions. And keep in mind that Howard played a greater percentage of his minutes with Yao and Mcgrady on the court next to him. So, it's not like Hayes was benefitting more from them.
Maybe Yao can teach him to grow taller. Hayes is a great second stringer but will always get abused by first string PFs. That he has a place on this team, I absolutely agree. That is the second coming of Otis Thorpe, no.
The actual data tells a somewhat different story. It appears the tendency was for his performance to increase with more playing time.
There have been great defensive players in the past who weren't tall. Hayes a strong lower base, great timing, quick hands, and quick feet. The coach himself has said that he feel Hayes is our best low post defender (according to a poster who attended the breakfast0. Why assume he'd get "abused" by first string PFs to a greater extent than the slow, whithering-away Juwan Howard (the current "first-string" PF)? There are so many people making these definitive statements, "Hayes will never amount to anything", "Hayes will always be a bench player", "Hayes is lucky to be in the league" without any objective evidence to back it up. The guy played fantastic last season as a rookie. His coach in college called him a winner and an intangibles guy, and he's getting the same accolades at the NBA level. There's something special about Chuck, and I think he's going to demonstrate that to a lot of skeptics in the coming season. JVG willing.
That's a fair request. I will need a little time to research the 82games site to chart the matchups. I've never been particularly good at that -- I just watch games -- but I shall give it a shot. One other thing, though, I am not disparaging Hayes' abilities as a player. I am just saying they are limited.
May stats knowledge doesn't extend much past Excel, to be frank. I used the highest order polynomial trend line it offered, which I thought would fit the data the best. How would your interpret those data points?
Without gettting into detailed stats analysis, did you notice how your seemingly upward trend is mostly created by some extremely low playing minutes (which is quite meaningless) and one or two high playing time points?
That's a fair point. I included the high playing time points because the question is whether Hayes's production would decrease when he gets those kind of minutes. Admittedly, there's only 3 occasions or so where he played "heavy minutes", but he was pretty successful (relative to his average for the season) all three times. I think those points are relevant. As for the low playing time points, there were a lot of games in which JVG barely played Hayes at all, and he didn't produce well (per minute) in many of them. I think that's also relevant, to an extent, because people are arguing that Hayes is best in spurts of a couple minutes. Clearly, he needs more than a few minutes to get going. I'll try again, removing the bottom 5 games in playing time and the upper 5 games in playing time and see what it looks like. Thanks for the feedback. Edit: That's removing the top 5 and bottom 5 games in minutes played. I'll add that Hayes played very poorly in the bottom 5 games, and he played very well in the top 5 games, which I think is at least partially relevant.
To have at least something worth discussing, the first cut of the analysis I feel like should be: 1. Throw out games under 5 minutes played. 2. select a point that represent "regular/high playing time", say 22 minutes for Hayes. 2.5 get the mean and variance of the two seperated series. 3. Test see if his production in playing time more than 22 minutes any significantly higher/different than his average of playing under 22 minutes. that will be a start.
This is all I could find. I'm still looking for the matchup stats on primary PFs. On Court / Off Court stats Many stats are shown on a 'per 48 minute' basis Stat ON Court OFF Court Net Minutes 534 3425 13% Offense: Pts per 100 Poss. 105.3 102.5 +2.8 Defense: Pts per 100 Poss. 96.2 106.3 -10.1 Net Points per 100 Possessions +9.1 -3.8 +12.9 Points Scored 1011 6377 -5366 Points Allowed 930 6591 -5661 Net Points +81 -214 +295 Effective FG% 46.1% 47.2% -1.2% Effective FG% Allowed 45.5% 47.5% -2.0% Assisted Field Goals 54% 58% -4% Assisted FG% Allowed 60% 60% +0% Own Shots Blocked 7% 5% +2% Shots Blocked 4% 5% -1% Rebounding Offensive Rebounding 31.7% 27.6% +4.2% Defensive Rebounding 74.2% 71.3% +3.0% Total Rebounding 53.0% 49.4% +3.6% Stats Free Throws Made 17 18 -1 Free Throws Attempted 23 24 -1 Free Throws Made by Opp. 19 18 -1 Free Throws Attempted by Opp. 27 25 -2 Turnovers, on Offense 12 14 +2 Turnovers, on Defense 16 12 +4 Net Turnovers 4 -2 -6 Fouls Committed 24 22 -2 Fouls, Drawn 19 20 -1 Net Fouls -5 -2 +3 Charles Hayes Houston Rockets 2005-2006 NBA Season Player Stats | 5-Man Units | By Position | On/Off Court | Clutch Play Top Five-Man Floor Units # Unit Min Off Def +/- W L Win% 1 Alston-Wesley-McGrady-Hayes-Howard 43 81 79 +2 3 4 42.8 2 Alston-Head-Wesley-Hayes-Howard 28 61 46 +15 3 2 60.0 3 Alston-Head-Bogans-Hayes-Howard 24 49 47 +2 2 4 33.3 4 Alston-Head-Bogans-Hayes-Ming 21 43 22 +21 4 0 100 5 Alston-Wesley-McGrady-Hayes-Baxter 20 54 27 +27 4 0 100 6 Alston-Head-Wesley-Hayes-Swift 19 35 36 -1 1 2 33.3 7 Alston-Head-Wesley-Hayes-Baxter 18 45 33 +12 3 1 75.0 8 Alston-Head-Bogans-Hayes-Swift 18 25 35 -10 1 3 25.0 9 Alston-Head-Bowen-Hayes-Swift 17 33 36 -3 1 3 25.0 10 Alston-Wesley-McGrady-Hayes-Mutombo 12 22 25 -3 1 3 25.0 Top Five-Man Floor Units, Details # Unit eFG eFGA FTA Close dClose Reb T/O 1 Alston-Wesley-McGrady-Hayes-Howard .436 .472 +2 23% 28% 115% -1% 2 Alston-Head-Wesley-Hayes-Howard .482 .397 -10 36% 28% 102% +13% 3 Alston-Head-Bogans-Hayes-Howard .443 .500 0 43% 24% 118% +13% 4 Alston-Head-Bogans-Hayes-Ming .461 .323 +8 47% 26% 113% +20% 5 Alston-Wesley-McGrady-Hayes-Baxter .577 .259 -3 23% 45% 100% +21% 6 Alston-Head-Wesley-Hayes-Swift .463 .371 -10 37% 35% 94% -17% 7 Alston-Head-Wesley-Hayes-Baxter .650 .543 -4 37% 30% 128% +6% 8 Alston-Head-Bogans-Hayes-Swift .328 .422 -1 25% 25% 112% -2% 9 Alston-Head-Bowen-Hayes-Swift .580 .577 -1 40% 42% 92% +3% 10 Alston-Wesley-McGrady-Hayes-Mutombo .406 .477 +6 6% 23% 90% -10% Legend: • Min = the total minutes the unit was on the floor. • Off = the points scored by the unit. • Def = the points allowed by the unit. • +/- = the team net points for the unit. • W = number of games a unit outscored its opponents while on the court. • L = number of games a unit was outscored by its opponents while on the court. • Win% = the winning percentage for the unit based on Wins versus Losses. • eFG = the effective shooting percentage, adjusted for the value of 3-point shots. • eFGA = the effective shooting percentage allowed to opponents. • FTA = net free throw attempts. • Close = the percentage of shots taken from close range. • dClose = the percentage of opponents' shots taken from close range. • Reb = the rebound percentage for the unit, based on chances. • T/O = the net turnover percentage for the unit based on opponent turnovers minus unit turnovers. CLUTCH STATISTICS (4th quarter or overtime, less than 5 minutes left, neither team ahead by more than 5 points) Floor Time statistics Min Net Pts Off Def Net48 W L Win% 18% 0 84.8 84.8 0.0 3 3 50.0% These stats represent how the team performed in clutch situations while the player was on the floor. The Net48 number shows the average +/- net points over a full game. Scoring By FG. FGA FG% eFG% Ast'd Blk'd FTM Pts 48 Min 2.8 5.6 .500 .500 50% 25% 2.8 8.3 Shooting Details Shot selection Shot Att. eFG% Ast'd Blk'd Pts Jump 25% 1.000 100% 0% 0.2 Close 50% .000 0% 50% 0.0 Dunk 25% 1.000 0% 0% 0.2 Tips 0% .000 0% 0% 0.0 Inside 75% .333 0% 33% 0.2 Shot clock usage Secs. Att. eFG% Ast'd Blk'd Pts 0-10 75% .333 0% 33% 0.2 11-15 0% .000 0% 0% 0.0 16-20 25% 1.000 100% 0% 0.2 21+ 0% .000 0% 0% 0.0 Crunch 50% .500 50% 0% 0.2 Free Throw Shooting and Foul Drawing FTM FTA FT% FTA48 PTS48 FGA Fouled DrawF 2 4 50.0 5.6 2.8 6 2 33.3% FGA includes the number of shooting fouls drawn. Passing Stats 3-Pt Assists Jump Assists Close Assists Dunk Assists Total Assists Passing T/O's Assist/ Bad Pass Passing Rating AST48 0 0 0 0 0 0 0.0 -2.8 0.0 Rebounding Off Rebounds Off. Reb Chances Off. Reb Pct Team Off Reb% Def Rebounds Def. Reb Chances Def. Reb Pct Team Def Reb% Player Rating Team FT Rating 5 31 16.1% 35.5% 9 35 25.7% 71.4% 41.8 106.9 Shot Blocking Jump Blocks Close Blocks Dunk Blocks Jump Pct Close Pct Dunk Pct All Blocks BLK48 Block Pct Shoot Fouls Blocks/ Foul Block Rating 0 1 0 0% 13% 0% 1 1.4 1.9% 2 0.50 6.7 Turnovers and Ball Handling Offensive Fouls Bad Passes Ball Handling Turnovers Other Turnovers 'Hands' Rating 1 1 0 0 -1.2 Player Stats | 5-Man Units | By Position | On/Off Court | Clutch Play Player Floor Time Stats by Position Position Min Net Pts Off Def Net48 W L Win% PG SG SF 0% -1 0.0 1440.0 -1440.0 0 1 0% PF 13% +78 90.1 82.9 7.2 26 11 70% C 0% +3 132.2 117.6 14.7 3 2 60% Min represents the percentage of the team's total minutes the player was at that position. W and L are not adjusted in this instance by quality of opponent while at that position in a game. Player 48-Minute Production by Position Position FGA eFG% FTA iFG Reb Ast T/O Blk PF Pts PER* PG SG SF 0.0 0.000 0.0 0% %1440.0 0.0 0.0 0.0 0.0 0.0 0.0 PF 9.3 0.559 4.1 86% 15.8 1.2 1.1 1.3 6.9 13.1 19.1 C 14.7 0.667 0.0 100% 29.4 4.9 0.0 0.0 4.9 19.6 31.1 Opponent Counterpart 48-Minute Production Position FGA eFG% FTA iFG Reb Ast T/O Blk PF Pts PER* PG SG SF 0.0 0.000 0.0 0% 0.0 0.0 0.0 0.0 0.0 0.0 0.0 PF 14.7 0.412 6.0 27% 11.4 3.1 3.3 1.6 4.7 15.6 13.3 C 14.7 0.667 0.0 0% 4.9 0.0 0.0 0.0 4.9 19.6 15.0 Net 48-Minute Production by Position Position FGA eFG% FTA iFG Reb Ast T/O Blk PF Pts PER* PG SG SF +0.0 +0.000 +0.0 +0% %+1440.0 +0.0 +0.0 +0.0 +0.0 +0.0 +0.0 PF -5.3 +0.146 -1.8 +59% +4.4 -1.9 +2.2 -0.3 -2.2 -2.5 +5.8 C +0.0 +0.000 +0.0 +100% +24.5 +4.9 +0.0 +0.0 +0.0 +0.0 +16.1 Notes: the PER is a complicated single number rating developed by John Hollinger and used extensively in his excellent Pro Basketball Prospectus books. The league average PER is set to 15, but for this view the comparison between a player's production and the opponent production at the position is the focus. At a glance you can tell whether there has been a net positive or negative overall contribution while playing that position. eFG% is the effective field goal percentage, adjusted for three point shots, while iFG represents the percentage of shots taken from inside/close to the hoop.
Sure. Here's the results: Code: [B]Game Score per 40 minutes (PER approximation):[/B] [COLOR=Navy]MPG games minutes mean stdeva weighted_avg[/COLOR] [22, ) 9 236 13.5 5.75 14.0 [5,21] 22 278 12.6 9.7 12.8 Hayes was more consistent with the high playing time series (as expected), and his performance, per minute, was better as well.
durvasa, Maybe what this shows is that when Chuck Hayes plays well, the coach leaves him in the game longer than he does when Chuck struggles in a game (due to unfavorable matchup or orther factors)? That said... Chuck Hayes seems to be a Daryl Morey kind of guy. Player pair stats: http://www.82games.com/0506/0506HOUP.HTM Look at the Chuck Hayes vertical column, pretty much everybody (except Mutombo and Swift) plays better with Chuck in the game. Now this data has a fair amount of noise in it, but Morey has used it in an article before. I remember when Van Gundy said that Morey had some stats info that's helpful for coaching, not just GM work. Perhaps a part of that info is the pure awesomeness that is Chuck Hayes. Morey's comment yesterday is consistent witht that guess.
Good point. He got the extra minutes because he was playing well that night ...not the other way around. I just don't buy these heavy statistical analysis.
That's a fair point, with regards to individual statistical production, per minute. Maybe that would explain it. Or maybe not. But it certainly wouldn't explain Hayes's positive impact on the team's performance, overall. Look at the W and L columns in the following table: <table><tr bgcolor="#33cc33"> <td><center><b><font size="-1">Player</font></b></center></td> <td><center><b><font size="-1">Min</font></b></center></td> <td><center><b><font size="-1">+/-</font></b></center></td> <td><center><b><font size="-1">Off</font></b></center></td> <td><center><b><font size="-1">Def</font></b></center></td> <td><center><b><font size="-1">Net48</font></b></center></td> <td><center><b><font size="-1">W</font></b></center></td> <td><center><b><font size="-1">L</font></b></center></td> <td><center><b><font size="-1">Win%</font></b></center></td> </tr> <tr bgcolor="#ffffff"> <td><font size="-1">Ming</font></td> <td align="right"><font size="-1"> 49% </font></td> <td align="right"><font size="-1">+86 </font></td> <td align="right"><font size="-1"> 92.7 </font></td> <td align="right"><font size="-1"> 90.6 </font></td> <td align="right"><font size="-1"> +2.1 </font></td> <td align="right"><font size="-1"> 29 </font></td> <td align="right"><font size="-1"> 27 </font></td> <td><center><font size="-1">51.8</font></center></td> </tr> <tr bgcolor="#f0f0df"> <td><font size="-1">Hayes</font></td> <td align="right"><font size="-1"> 13% </font></td> <td align="right"><font size="-1">+81 </font></td> <td align="right"><font size="-1"> 90.9 </font></td> <td align="right"><font size="-1"> 83.6 </font></td> <td align="right"><font size="-1"> +7.3 </font></td> <td align="right"><font size="-1"> 26 </font></td> <td align="right"><font size="-1"> 11 </font></td> <td><center><font size="-1">70.3</font></center></td> </tr> <tr bgcolor="#ffffff"> <td><font size="-1">McGrady</font></td> <td align="right"><font size="-1"> 44% </font></td> <td align="right"><font size="-1">+62 </font></td> <td align="right"><font size="-1"> 94.1 </font></td> <td align="right"><font size="-1"> 92.4 </font></td> <td align="right"><font size="-1"> +1.7 </font></td> <td align="right"><font size="-1"> 25 </font></td> <td align="right"><font size="-1"> 19 </font></td> <td><center><font size="-1">56.8</font></center></td> </tr> <tr bgcolor="#f0f0df"> <td><font size="-1">Baxter</font></td> <td align="right"><font size="-1"> 7% </font></td> <td align="right"><font size="-1">+30 </font></td> <td align="right"><font size="-1"> 94.9 </font></td> <td align="right"><font size="-1"> 89.8 </font></td> <td align="right"><font size="-1"> +5.2 </font></td> <td align="right"><font size="-1"> 11 </font></td> <td align="right"><font size="-1"> 11 </font></td> <td><center><font size="-1">50.0</font></center></td> </tr> <tr bgcolor="#ffffff"> <td><font size="-1">Norris</font></td> <td align="right"><font size="-1"> 6% </font></td> <td align="right"><font size="-1">+29 </font></td> <td align="right"><font size="-1"> 91.1 </font></td> <td align="right"><font size="-1"> 85.3 </font></td> <td align="right"><font size="-1"> +5.8 </font></td> <td align="right"><font size="-1"> 16 </font></td> <td align="right"><font size="-1"> 11 </font></td> <td><center><font size="-1">59.3</font></center></td> </tr> <tr bgcolor="#f0f0df"> <td><font size="-1">Graham</font></td> <td align="right"><font size="-1"> 0% </font></td> <td align="right"><font size="-1">+2 </font></td> <td align="right"><font size="-1">103.5 </font></td> <td align="right"><font size="-1">100.9 </font></td> <td align="right"><font size="-1"> +2.6 </font></td> <td align="right"><font size="-1"> 3 </font></td> <td align="right"><font size="-1"> 2 </font></td> <td><center><font size="-1">60.0</font></center></td> </tr> <tr bgcolor="#ffffff"> <td><font size="-1">Lampe</font></td> <td align="right"><font size="-1"> 0% </font></td> <td align="right"><font size="-1">+2 </font></td> <td align="right"><font size="-1"> 86.9 </font></td> <td align="right"><font size="-1"> 79.0 </font></td> <td align="right"><font size="-1"> +7.9 </font></td> <td align="right"><font size="-1"> 2 </font></td> <td align="right"><font size="-1"> 1 </font></td> <td><center><font size="-1">66.7</font></center></td> </tr> <tr bgcolor="#f0f0df"> <td><font size="-1">Davis</font></td> <td align="right"><font size="-1"> 0% </font></td> <td align="right"><font size="-1">0 </font></td> <td align="right"><font size="-1"> 0.0 </font></td> <td align="right"><font size="-1"> 0.0 </font></td> <td align="right"><font size="-1"> +0.0 </font></td> <td align="right"><font size="-1"> 0 </font></td> <td align="right"><font size="-1"> 0 </font></td> <td><center><font size="-1">0.0</font></center></td> </tr> <tr bgcolor="#ffffff"> <td><font size="-1">Lucas</font></td> <td align="right"><font size="-1"> 2% </font></td> <td align="right"><font size="-1">-6 </font></td> <td align="right"><font size="-1"> 85.8 </font></td> <td align="right"><font size="-1"> 88.5 </font></td> <td align="right"><font size="-1"> -2.7 </font></td> <td align="right"><font size="-1"> 3 </font></td> <td align="right"><font size="-1"> 8 </font></td> <td><center><font size="-1">27.3</font></center></td> </tr> <tr bgcolor="#f0f0df"> <td><font size="-1">Anderson</font></td> <td align="right"><font size="-1"> 14% </font></td> <td align="right"><font size="-1">-13 </font></td> <td align="right"><font size="-1"> 89.7 </font></td> <td align="right"><font size="-1"> 90.8 </font></td> <td align="right"><font size="-1"> -1.1 </font></td> <td align="right"><font size="-1"> 9 </font></td> <td align="right"><font size="-1"> 11 </font></td> <td><center><font size="-1">45.0</font></center></td> </tr> <tr bgcolor="#ffffff"> <td><font size="-1">Brunson</font></td> <td align="right"><font size="-1"> 5% </font></td> <td align="right"><font size="-1">-20 </font></td> <td align="right"><font size="-1"> 86.4 </font></td> <td align="right"><font size="-1"> 90.9 </font></td> <td align="right"><font size="-1"> -4.5 </font></td> <td align="right"><font size="-1"> 10 </font></td> <td align="right"><font size="-1"> 12 </font></td> <td><center><font size="-1">45.5</font></center></td> </tr> <tr bgcolor="#f0f0df"> <td><font size="-1">Frahm</font></td> <td align="right"><font size="-1"> 2% </font></td> <td align="right"><font size="-1">-23 </font></td> <td align="right"><font size="-1"> 94.7 </font></td> <td align="right"><font size="-1">104.2 </font></td> <td align="right"><font size="-1"> -9.5 </font></td> <td align="right"><font size="-1"> 1 </font></td> <td align="right"><font size="-1"> 7 </font></td> <td><center><font size="-1">12.5</font></center></td> </tr> <tr bgcolor="#ffffff"> <td><font size="-1">Head</font></td> <td align="right"><font size="-1"> 58% </font></td> <td align="right"><font size="-1">-35 </font></td> <td align="right"><font size="-1"> 88.7 </font></td> <td align="right"><font size="-1"> 89.4 </font></td> <td align="right"><font size="-1"> -0.7 </font></td> <td align="right"><font size="-1"> 30 </font></td> <td align="right"><font size="-1"> 47 </font></td> <td><center><font size="-1">39.0</font></center></td> </tr> <tr bgcolor="#f0f0df"> <td><font size="-1">Barry</font></td> <td align="right"><font size="-1"> 8% </font></td> <td align="right"><font size="-1">-45 </font></td> <td align="right"><font size="-1"> 91.3 </font></td> <td align="right"><font size="-1"> 97.6 </font></td> <td align="right"><font size="-1"> -6.3 </font></td> <td align="right"><font size="-1"> 7 </font></td> <td align="right"><font size="-1"> 12 </font></td> <td><center><font size="-1">36.8</font></center></td> </tr> <tr bgcolor="#ffffff"> <td><font size="-1">Bogans</font></td> <td align="right"><font size="-1"> 26% </font></td> <td align="right"><font size="-1">-61 </font></td> <td align="right"><font size="-1"> 88.8 </font></td> <td align="right"><font size="-1"> 91.6 </font></td> <td align="right"><font size="-1"> -2.8 </font></td> <td align="right"><font size="-1"> 14 </font></td> <td align="right"><font size="-1"> 19 </font></td> <td><center><font size="-1">42.4</font></center></td> </tr> <tr bgcolor="#f0f0df"> <td><font size="-1">Wesley</font></td> <td align="right"><font size="-1"> 59% </font></td> <td align="right"><font size="-1">-81 </font></td> <td align="right"><font size="-1"> 90.4 </font></td> <td align="right"><font size="-1"> 92.1 </font></td> <td align="right"><font size="-1"> -1.6 </font></td> <td align="right"><font size="-1"> 30 </font></td> <td align="right"><font size="-1"> 37 </font></td> <td><center><font size="-1">44.8</font></center></td> </tr> <tr bgcolor="#ffffff"> <td><font size="-1">Alston</font></td> <td align="right"><font size="-1"> 61% </font></td> <td align="right"><font size="-1">-85 </font></td> <td align="right"><font size="-1"> 90.3 </font></td> <td align="right"><font size="-1"> 92.0 </font></td> <td align="right"><font size="-1"> -1.7 </font></td> <td align="right"><font size="-1"> 28 </font></td> <td align="right"><font size="-1"> 35 </font></td> <td><center><font size="-1">44.4</font></center></td> </tr> <tr bgcolor="#f0f0df"> <td><font size="-1">Mutombo</font></td> <td align="right"><font size="-1"> 24% </font></td> <td align="right"><font size="-1">-88 </font></td> <td align="right"><font size="-1"> 84.1 </font></td> <td align="right"><font size="-1"> 88.5 </font></td> <td align="right"><font size="-1"> -4.4 </font></td> <td align="right"><font size="-1"> 25 </font></td> <td align="right"><font size="-1"> 38 </font></td> <td><center><font size="-1">39.7</font></center></td> </tr> <tr bgcolor="#ffffff"> <td><font size="-1">Bowen</font></td> <td align="right"><font size="-1"> 16% </font></td> <td align="right"><font size="-1">-111 </font></td> <td align="right"><font size="-1"> 82.8 </font></td> <td align="right"><font size="-1"> 91.0 </font></td> <td align="right"><font size="-1"> -8.2 </font></td> <td align="right"><font size="-1"> 18 </font></td> <td align="right"><font size="-1"> 40 </font></td> <td><center><font size="-1">31.0</font></center></td> </tr> <tr bgcolor="#f0f0df"> <td><font size="-1">Swift</font></td> <td align="right"><font size="-1"> 33% </font></td> <td align="right"><font size="-1">-133 </font></td> <td align="right"><font size="-1"> 86.5 </font></td> <td align="right"><font size="-1"> 91.3 </font></td> <td align="right"><font size="-1"> -4.8 </font></td> <td align="right"><font size="-1"> 24 </font></td> <td align="right"><font size="-1"> 39 </font></td> <td><center><font size="-1">38.1</font></center></td> </tr> <tr bgcolor="#ffffff"> <td><font size="-1">Howard</font></td> <td align="right"><font size="-1"> 63% </font></td> <td align="right"><font size="-1">-256 </font></td> <td align="right"><font size="-1"> 87.8 </font></td> <td align="right"><font size="-1"> 92.7 </font></td> <td align="right"><font size="-1"> -4.8 </font></td> <td align="right"><font size="-1"> 27 </font></td> <td align="right"><font size="-1"> 52 </font></td> <td><center><font size="-1">34.2</font></center></td> </tr> </table> W stands for number of games in which Rockets outscored the opponent while the player was on the court. L stands for numbers of games in which the opponent outscored the Rockets while the player was on the court. Hayes fairs unbelievably well here. If Hayes actually "struggled" in a lot of games where he didn't see many minutes, how could this be explained? Yeah, maybe from an individual statistical standpoint he struggled with few minutes (which in turn impacted his playing time), but the fact still remains that the team as a whole usually played well while he was on the court, even on a game to game basis.
Good job. It's not suprising that his number is slightly higher the longer he played, since he's more likely to be played more when he did well. The more surprising thing is that the difference isn't bigger. as of now, these improvements are not "significant", so to speak. With that said, it does look to me CH can prob handle 16-20 minutes a game with expected production. Out of curiosity, what kind of game did CH get his most playing time? (end of season? against who? etc. ) BTW, I would prob hire you for research assistant. You are fast and quite good.
Perhaps not. But there certainly isn't much proof that Hayes will struggle with more minutes, which everyone is assuming as a given. Thanks. Here's the info for the 22 minutes and above games: Code: [COLOR=Navy]Date Opp MP GS/40[/COLOR] 1/20/2006 CHI 33 20.2 4/19/2006 SAS 30 20.7 1/25/2006 CHA 28 18.3 1/27/2006 MIN 27 13.3 4/17/2006 DEN 25 5.4 4/12/2006 MIN 24 16.7 1/29/2006 MIA 23 10.4 2/11/2006 UTA 23 7.1 4/4/2006 SEA 23 9.0
You just can't prove it, either way. I think it's probably a bit of both. And even if his per-minute production decreases with more minutes (which I agree is quite possible), it has a LONG WAY to decrease till it reaches the substandard levels of Juwan Howard. Hayes posted an 18.0 PER on the season, while Howard had a 12.5 PER. If Hayes's PER reduces to, say, 14.0 or 15.0, he's still more statistically productive than Juwan (who's PER has been slipping for the last 3 years). Additionally, Hayes brings more intangibles to the floor -- he contributes in so many ways that don't show up in a box score. So, even in the remote possibility that his PER dips all the way down to Juwan's level, he's still a better option and will do more to help the team win because of all the other things he brings to the table.
