| Posted by: dgrooves
- [454482113] Fri, Nov 08, 2002, 11:16
I got this idea from a thread (A new statistical look at TNSP production ) Mighty Geeks started last season. From that thread: " I have attempted to analyze the statistical performance of opposing defensive teams and apply that analysis to the average scores of several of the players I am looking at adding to my team. Like any mathematical approach to the game, the flaw is that nothing that ever happens is "average" on any given week. Nonetheless, I think it is useful to look at opponents when selecting players to add to your teams.
The actual method I used is fairly easy to understand, but difficult to explain, so please try to bear with me. First, I used a statistical source to capture the following stats for each defense, passing yards allowed, passing TDs, rushing yards allowed, and rushing TDs. I also computed NFL averages for these same stats. I could do the same for WR and TE yards and TDs, but I'm not yet sure that it is worth the effort. Then I took these average numbers and figured out how many TNSPs that would be worth per game. For instance, the average Defense gives up 232 passing yards and 1.4 passing TDs. This means an average net of 316 TNSPs. This formula does not take into account fumbles or interceptions. I think I like that, but I'm not sure yet. I then look at a particular Defense, such as Arizona and determine that they give up an average of 268 yards and 1.8 TDs. This results in an average TNSP of 376. I then convert this into a ratio of 1.19 and compute that any QB lucky enough to face the Arizona D will get 1.19 points for every point he usually gets. I then multiply the average TNSP/game for each QB by this factor and arrive at a predicted TNSP for each QB.
The next thing I do is perform the exact same analysis for the next three weeks to find players who have a nice cushy schedule coming up.
As a number cruncher from way back, I can assure you that these results will not come to pass, but they are interesting to look at sometimes. The more interesting stat for me is the three week outlook and I will try to paste my table for that as a reply. It might come out in HTML or it might not. I'll see what I can do."
I dont have access to the same data that he did, so I have instead used the TSNP allowed data that Goatlocker and RSF have been posting. Also, I have weighted all the players'/defenses' TSNPs scored and allowed. This adjusted average is 70% points per game over the player's/defense's last 4 games and 30% the player's/defense's overall average.
I have very little background in statistics so I am certainly open to suggestions and criticisms. Also, I want to reiterate that these numbers may seem like predictions, but it is highly unlikely that they will be correct in that sense. For example, last week's numbers had Travis Henry ahead of Mashall Faulk, but Faulk scored 542 and Henry only scored 136.
Week 10 |
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Jeff Garcia | 586 | Brian Griese | 448 | Daunte Culpepper | 371 | Steve Mcnair | 347 | Kerry Collins | 344 | Marc Bulger | 339 | Aaron Brooks | 337 | Tom Brady | 324 | Trent Green | 319 | David Carr | 310 | Brett Favre | 302 | Donovan McNabb | 266 | Chad Pennington | 261 | Rich Gannon | 235 | Drew Brees | 222 | Kurt Warner | 213 | Jeff Blake | 213 | Jake Plummer | 212 | Jay Fiedler | 209 | Chris Redman | 208 |
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Marshall Faulk | 534 | Priest Holmes | 515 | Ahman Green | 347 | LaDainian Tomlinson | 322 | Clinton Portis | 297 | Charlie Garner | 267 | Corey Dillon | 266 | Eddie George | 261 | Curtis Martin | 257 | Tiki Barber | 251 | Duce Staley | 251 | Ricky Williams | 246 | Shaun Alexander | 244 | Antowain Smith | 240 | James Stewart | 232 | Marcel Shipp | 222 | Michael Bennett | 220 | Deuce McAllister | 212 | Kenny Watson | 205 | Stephen Davis | 204 |
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Terrell Owens | 419 | Travis Taylor | 239 | Derrick Mason | 238 | Jimmy Smith | 220 | Tai Streets | 218 | Santana Moss | 212 | Curtis Conway | 201 | Ike Hilliard | 201 | Koren Robinson | 197 | David Patten | 194 | Hines Ward | 193 | Michael Lewis | 192 | Troy Brown | 190 | Joe Horn | 188 | Dante Hall | 188 | Ed Mccaffrey | 187 | Rod Smith | 183 | Marvin Harrison | 180 | Bobby Engram | 180 | Plaxico Burress | 178 |
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Philadelphia D | 321 | GreenBay D | 263 | Arizona D | 220 | NewOrleans D | 186 | NewEngland D | 182 | NYJets D | 181 | Tennessee D | 171 | Jacksonville D | 168 | St.Louis D | 150 | Denver D | 138 | Washington D | 131 | Baltimore D | 114 | Cincinnati D | 100 | NYGiants D | 95 | Seattle D | 92 | Minnesota D | 66 | Pittsburgh D | 56 | Chicago D | 54 | Indianapolis D | 50 | Miami D | 44 |
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Week 11 |
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Jeff Garcia | 571 | Drew Bledsoe | 482 | Brett Favre | 399 | Tom Brady | 363 | Donovan McNabb | 355 | Michael Vick | 351 | Rich Gannon | 340 | Trent Green | 323 | Brian Griese | 314 | Chad Pennington | 309 | Tommy Maddox | 302 | Aaron Brooks | 289 | Drew Brees | 277 | Marc Bulger | 275 | Shane Matthews | 255 | Brad Johnson | 250 | Mark Brunell | 248 | Kelly Holcomb | 247 | David Carr | 245 | Kerry Collins | 218 |
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Priest Holmes | 588 | Marshall Faulk | 503 | Corey Dillon | 357 | LaDainian Tomlinson | 353 | Clinton Portis | 332 | Deuce McAllister | 306 | Ahman Green | 295 | James Stewart | 294 | Charlie Garner | 294 | Travis Henry | 277 | Shaun Alexander | 274 | Fred Taylor | 264 | Tiki Barber | 248 | Antowain Smith | 245 | Duce Staley | 244 | Curtis Martin | 238 | Jamal Lewis | 233 | Garrison Hearst | 219 | Ricky Williams | 216 | Kevan Barlow | 207 |
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Peerless Price | 327 | Terrell Owens | 322 | Eric Moulds | 297 | Dennis Northcutt | 270 | Curtis Conway | 261 | Jimmy Smith | 253 | Marvin Harrison | 231 | Hines Ward | 226 | Santana Moss | 222 | Quincy Morgan | 219 | David Patten | 219 | Troy Brown | 214 | Donald Driver | 214 | Plaxico Burress | 209 | Derrick Mason | 206 | Michael Lewis | 205 | Joe Horn | 200 | Marty Booker | 197 | Bobby Shaw | 196 | Chad Johnson | 194 |
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TampaBay D | 491 | GreenBay D | 340 | Miami D | 281 | St.Louis D | 268 | Dallas D | 265 | Philadelphia D | 254 | Baltimore D | 202 | Jacksonville D | 180 | Denver D | 178 | Carolina D | 160 | Pittsburgh D | 160 | NYGiants D | 150 | Washington D | 136 | Indianapolis D | 133 | Cleveland D | 124 | Arizona D | 118 | NewEngland D | 108 | SanFrancisco D | 99 | NYJets D | 85 | Oakland D | 75 |
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Week 12 |
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Donovan McNabb | 403 | Tom Brady | 387 | Rich Gannon | 337 | Drew Bledsoe | 334 | Chad Pennington | 326 | David Carr | 319 | Kelly Holcomb | 304 | Jake Plummer | 303 | Aaron Brooks | 298 | Jay Fiedler | 294 | Kerry Collins | 293 | Jeff Blake | 273 | Jeff Garcia | 269 | Michael Vick | 267 | Trent Green | 267 | Chris Redman | 266 | Tim Couch | 265 | Daunte Culpepper | 264 | Brian Griese | 248 | Tommy Maddox | 237 |
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Priest Holmes | 601 | Deuce McAllister | 457 | Ahman Green | 415 | Marshall Faulk | 373 | Tiki Barber | 347 | LaDainian Tomlinson | 344 | James Stewart | 315 | Curtis Martin | 301 | Michael Bennett | 289 | Ricky Williams | 280 | Duce Staley | 278 | Travis Henry | 274 | Shaun Alexander | 268 | Clinton Portis | 257 | Charlie Garner | 237 | Edgerrin James | 230 | Moe Williams | 215 | Eddie George | 206 | Kenny Watson | 201 | Stephen Davis | 200 |
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Hines Ward | 293 | Michael Lewis | 286 | Joe Horn | 280 | Plaxico Burress | 270 | Peerless Price | 255 | David Patten | 248 | Troy Brown | 243 | Jerry Rice | 234 | Eric Moulds | 232 | Koren Robinson | 229 | Terrell Owens | 218 | Santana Moss | 214 | Bobby Engram | 209 | Dennis Northcutt | 202 | Ike Hilliard | 201 | Antwaan Randle-El | 196 | Marvin Harrison | 192 | Tim Brown | 191 | Derrick Mason | 190 | Jerry Porter | 187 |
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Atlanta D | 395 | GreenBay D | 301 | Detroit D | 268 | Pittsburgh D | 248 | St.Louis D | 226 | Jacksonville D | 216 | Dallas D | 209 | Denver D | 206 | Tennessee D | 177 | Arizona D | 171 | Miami D | 169 | NYGiants D | 161 | NewEngland D | 97 | Washington D | 95 | NYJets D | 87 | Oakland D | 85 | Baltimore D | 73 | SanFrancisco D | 73 | KansasCity D | 72 | NewOrleans D | 70 |
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Next 3 Weeks |
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Jeff Garcia | 1426 | 475 | Tom Brady | 1074 | 358 | Donovan McNabb | 1024 | 341 | Brian Griese | 1010 | 336 | Aaron Brooks | 924 | 308 | Rich Gannon | 912 | 304 | Trent Green | 909 | 303 | Chad Pennington | 896 | 298 | David Carr | 874 | 291 | Kerry Collins | 855 | 285 | Marc Bulger | 822 | 274 | Drew Bledsoe | 816 | 408 | Michael Vick | 808 | 269 | Daunte Culpepper | 808 | 269 | Brett Favre | 777 | 259 | Steve Mcnair | 749 | 249 | Tommy Maddox | 729 | 243 | Drew Brees | 723 | 241 | Jake Plummer | 672 | 224 | Jeff Blake | 669 | 223 |
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Priest Holmes | 1704 | 568 | Marshall Faulk | 1410 | 470 | Ahman Green | 1057 | 352 | LaDainian Tomlinson | 1019 | 339 | Deuce McAllister | 975 | 325 | Clinton Portis | 886 | 295 | Tiki Barber | 846 | 282 | James Stewart | 841 | 280 | Corey Dillon | 811 | 270 | Charlie Garner | 798 | 266 | Curtis Martin | 796 | 265 | Shaun Alexander | 786 | 262 | Duce Staley | 773 | 257 | Ricky Williams | 742 | 247 | Michael Bennett | 710 | 236 | Antowain Smith | 665 | 221 | Fred Taylor | 641 | 213 | Eddie George | 612 | 204 | Jamal Lewis | 601 | 200 | Kenny Watson | 589 | 196 |
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Terrell Owens | 959 | 319 | Hines Ward | 712 | 237 | Michael Lewis | 683 | 227 | Joe Horn | 668 | 222 | David Patten | 661 | 220 | Plaxico Burress | 657 | 219 | Jimmy Smith | 655 | 218 | Santana Moss | 648 | 216 | Troy Brown | 647 | 215 | Curtis Conway | 643 | 214 | Derrick Mason | 634 | 211 | Marvin Harrison | 603 | 201 | Peerless Price | 582 | 291 | Travis Taylor | 580 | 193 | Ike Hilliard | 576 | 192 | Koren Robinson | 553 | 184 | Marty Booker | 539 | 179 | Jerry Rice | 537 | 179 | Chad Johnson | 532 | 177 | Eric Moulds | 529 | 264 |
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GreenBay D | 904 | 301 | St.Louis D | 644 | 214 | Jacksonville D | 564 | 188 | Philadelphia D | 522 | 174 | Denver D | 522 | 174 | Arizona D | 509 | 169 | Miami D | 494 | 164 | TampaBay D | 491 | 245 | Dallas D | 474 | 237 | Pittsburgh D | 464 | 154 | NYGiants D | 406 | 135 | Baltimore D | 389 | 129 | NewEngland D | 387 | 129 | Washington D | 362 | 120 | Tennessee D | 355 | 118 | NYJets D | 353 | 117 | Atlanta D | 349 | 116 | Detroit D | 307 | 102 | NewOrleans D | 277 | 92 | Indianapolis D | 216 | 72 |
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| 1 | Sludge Sustainer
ID: 566332517 Fri, Nov 08, 2002, 12:08
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A good start, but it does not take into account the quality of the past defenses an offensive player has gone up against. For example, if a QB has played soft defenses all year, then his average TSNP per game is an inflated estimate of what his average performance would be versus the "average" defense.
An alternative approach: For each offensive player, build a regression model with TSNP as the dependent variable and the defensive statistics as the independent variables (i.e. Passing yards allowed, passing TDs, rushing yards allowed, and rushing TDs. This also allows you to throw in things like interceptions, fumble recoveries, sacks, home/away, etc. Have to be careful in your selection of the independent variables not to have too many.)
Drawback? Pain-in-the-ass because you have to do this for each offensive player.
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| 2 | walk Leader
ID: 338441813 Fri, Nov 08, 2002, 12:52
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Wow, made my selections prior to seeing this thread, and had a high degree of correspondence:
Garcia, Griese, Faulk, Holmes Owens, and Green Bay are all on my team. Now let's see if past performance is a predictor of future performance (it sure is when it comes to human behavior!).
Clearly, a team with some offensive stars playing KC makes it to the top...
- (dr.) walk
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| 3 | dgrooves
ID: 23105812 Fri, Nov 08, 2002, 13:29
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Sludge: I am planning to adjust the players' averages based on past opponents, but I just havent had enough time to do so. Hopefully I will have it done by the time next week rolls around. I was thinking of calculationg the average of the multipliers of the opponents the player has played, then dividing the player's weighted average by it. For example, say a QB has played teams with multipliers of 1.06, 1.2, and .86 and is averaging 306 TSNPs per game. The average of these is 1.04, meaning this QB has, on average, played easy defenses, compared to the league average. The player's TSNPs per game should thus be decreased by .961, the inverse of 1.04. So instead of averaging 306 TSNPs, he would average 294 TSNPs. Is this the best way to account for schedule strength, so to speak?
I am unable to do the regression analysis because I am not using the independent variables you mention. I am using the data GoatLocker and RSF are providing.
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| 4 | Sludge Sustainer
ID: 566332517 Fri, Nov 08, 2002, 14:34
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dgrooves -
Is the method you mentioned the best way to account for the strength of the defenses a player has gone against? Probably not. It would be very difficult to impossible to know what the best way of doing it is. Only skimming over what you proposed, I would say that it's an improvement, though.
As to your statement that you can't use the variables I mentioned: Yes you can, and yes you are. In fact, I copied and pasted the four variables from your initial message. I simply state that you can also use the additional ones I mentioned.
In fact, a better way to do the regression would be to use TSNP as the dependent variable and both offensive statistics and defensive statistics for the independent variables. In this case, a different model would have to be built for each position, which is not unreasonable. At the very least it's much more reasonable than a different model for each individual player. The first type I mentioned suffers from a lack of data, which gives it less predictive power. The second type I just mentioned won't suffer from a lack of data, but it won't take into account an individual's ability to excel against a particular type of defense. Damned if you do, damned if you don't.
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| 5 | dgrooves
ID: 454482113 Fri, Nov 08, 2002, 15:33
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Sludge:
No, I cant use those variables. Please re-read my initial message. What you think I wrote was actually written by Mighty Geeks, as I say in that post. He was using the yardage, interception, etc numbers when he did this analysis last year. I dont have access to that data; I am instead using the TSNP allowed data from GL and RSF.
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| 6 | Kyle
ID: 381043820 Fri, Nov 08, 2002, 22:13
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I am just wondering why Farve's numbers are down these next three weeks? Ahman will make his numbers a little lower but Ahman catches the majority of Farve's completions
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| 7 | root88
ID: 359101014 Sat, Nov 09, 2002, 02:50
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I used Mighty Geeks info to help me out last year and it worked very well for me. Of course it's not a predection, but it can open your eyes to something you might miss schedulewise, or if you are stuck between two players this info could push you over the edge.
Thanks dgrooves.
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| 8 | dgrooves
ID: 454482113 Sat, Nov 09, 2002, 10:56
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Kyle, I dont see any problems with Farve's numbers. He is "predicted" to score more points than his average in Weeks 10 and 11 (Det and Min). In Week 12 he is playing the best defense in football, Tampa Bay. This means he will likely score less points than he is averaging.
Also keep in mind that I am using weighted average TSNPs per game. Farve is averaging 299 points per game during the entire season, but only 276 points over his last for games.
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| 9 | Bandos
ID: 39112921 Sat, Nov 09, 2002, 21:53
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Very fun to look at. Helpful too! Thanks.
Just a few interesting observations... Why am I holding Porter when M. Lewis is out there?
Carr and Fatpepper with better week 10 games than McNabb? wow!
Where is Driver?
Guess you gotta have Faulk and Holmes - the leaders won't (hall and Battery judging by their trade/bye situation)
Ward, Ward, Ward....is Tommy Maddox that good? Or is Ward.
How about Moulds andice next week. How about any WR vs. KAN every week. Holy crap.
Thanks again for the brain workout.
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| 10 | Kyle
ID: 239312618 Sun, Nov 10, 2002, 21:13
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Thanks for explanation D-grooves. I know who to start week 12 between Farve and Greise. I just don't know why farve wouldn't even crack the list that week. Then again u are the statistion (i can't spell).
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