Aggregate Recruiting Rankings (Rivals, Scout, 247, ESPN)

Submitted by turd ferguson on

I’m sorry to post again, but I think the improvements are significant enough – thanks to some intelligent feedback – to warrant a new posting.

Below is my attempt to aggregate the Rivals, Scout, 247, and ESPN rankings into a universal list.  The goal is to draw from all of the data available to create a single list that eliminates the need to juggle rankings, ratings, and stars from four different sites when comparing prospects.

First, though, I’ll describe the logic and process.

 

The Process

There are countless ways to do this, and none of them is perfect.  Importantly, even though I’m a Michigan fan, I never considered how this would look for Michigan before deciding how to do it.  I’m trying to make this as objective and sensible as possible given time and data constraints.

The first decision one has to make is whom to include.  In my first draft, I included only those who appeared in the top X lists for all four sites.  Others thought that requirement was too rigid, so I’ve relaxed it here.  The players appearing on this list appear in at least three of the four following lists: Rivals’ top 250, Scout’s top 300, 247’s top 247, and ESPN’s top 300.  This eliminates the “veto power” nature of the first rankings (and the related outlier worries), since two sites would have to leave out a prospect for him to be excluded. 

The next decision is how to rank those who make it.  The most straightforward way to do this is to take the average ranking for each prospect across the four sites.  In an ideal world, each site would rank every prospect so there would be no missing data.  That isn’t reality.  Therefore, I imputed rankings where they were missing.  Here’s how I did in for each site (this is boring if you aren't interested):

  • ESPN – ESPN actually makes this the easiest, because they just rank thousands of prospects.   Every ESPN ranking here reflects ESPN’s actual ranking.
  • Rivals – Rivals ranks its top 250 prospects and then gives elite prospects a star rating and a “Rivals rating” of 4.9 to 6.1.  Using those ratings – and especially the Rivals rating – I found the range within which a recruit must fall (rankings-wise) and gave him the middle value.  For example, Rivals has 222 guys rated a 5.8.  Of them, 163 appear in the Rivals 250 (and 59 do not).  That means that a prospect who receives a rating of 5.8 from Rivals but does not appear in the Rivals 250 must rank somewhere between 251 and 309.  For this prospect, I would impute a ranking of 280.
  • 247 – Exactly the same logic as with Rivals except that I had to trust them when they said, for example, that about 300 prospects are rated 90 or higher.  (They don’t let you sort by prospect rating.)
  • Scout – This one might seem unusual, but I think it’s actually pretty accurate.  Scout doesn’t have anything like a Rivals rating, but it ranks prospects at their positions.  For those outside of the top 300, I took their position ranking and imputed based on where ESPN had that ranked overall.  For example, Scout has Amos Leggett as its #22 cornerback.  ESPN has its #22 CB ranked #404 overall, so this is Leggett’s imputed Scout ranking. (There was an exception to this with two TEs that I can explain if anyone's interested.)

I hope that makes sense, and I’m happy to answer questions in the comments.  Please feel free to share feedback or point out errors.

Also, if one of these sites significantly changes its rankings in the next few days I’m going to kill someone.

 

The Product

rank name pos mean Rivals Scout 247 ESPN college
1 Dorial Green-Beckham WR 2 1 2 2 3  
2 Eddie Goldman DT 6 4 15 3 2  
3 Mario Edwards DE 6.25 2 8 14 1 Florida State
4 Stefon Diggs S 9.25 8 12 8 9  
5 D.J. Humphries OT 10.25 3 18 13 7  
6 Arik Armstead OT 10.5 23 1 1 17 USC
7 Andrus Peat OT 11 15 3 4 22  
7 John Theus OT 11 7 4 6 27  
9 Johnathan Gray RB 11.5 14 9 15 8 Texas
10 Shaq Thompson S 11.75 10 11 5 21  
11 Noah Spence DE 13.75 13 6 32 4  
12 Gunner Kiel QB 14.25 19 16 10 12  
13 Eddie Williams S 18 20 36 11 5 Alabama
14 Keith Marshall RB 18.25 55 5 7 6  
15 Malcom Brown DT 22.75 26 26 26 13 Texas
16 Kyle Murphy OT 23.5 28 27 9 30  
17 Rushel Shell RB 26.25 33 10 39 23  
18 Jessamen Dunker OT 27.5 49 22 25 14 Florida
19 Jameis Winston QB 28.25 52 30 16 15  
20 Ellis McCarthy DT 29 6 29 28 53  
21 Darius Hamilton DE 29.25 5 25 20 67  
22 Nelson Agholor S 31.25 9 53 22 41  
23 Joshua Garnett OG 32.25 22 24 40 43  
24 Cayleb Jones WR 39.25 21 23 93 20 Texas
24 Tracy Howard CB 39.25 25 55 58 19  
26 Noor Davis OLB 39.75 30 77 34 18 Stanford
27 Geno Smith CB 40.25 47 54 29 31  
28 Dante Fowler DE 41.75 11 39 43 74 Florida State
29 Yuri Wright CB 42 41 75 12 40  
30 Shaq Roland WR 43.5 63 17 48 46  
31 Chris Black WR 44 57 71 19 29  
32 Landon Collins S 45 17 59 53 51  
33 Aziz Shittu DT 47.5 12 41 49 88  
33 Jordan Jenkins DE 47.5 56 44 27 63  
35 Kennedy Estelle OT 47.75 35 43 65 48 Texas
36 Jonathan Taylor DT 48 36 66 46 44 Georgia
37 Ifeadi Odenigbo OLB 48.75 48 60 37 50  
38 Kwon Alexander OLB 49 77 34 69 16  
39 Jarron Jones DT 49.75 67 14 21 97 Penn State
40 Josh Harvey-Clemons OLB 50.5 39 78 61 24  
40 Trey Williams RB 50.5 24 20 24 134 Texas A&M
42 Thomas Johnson WR 56.5 50 87 54 35 Texas
43 Jabari Ruffin OLB 57.25 46 104 45 34 USC
44 Ronald Darby CB 57.5 64 32 64 70 Notre Dame
45 Jordan Simmons OG 57.75 45 31 70 85  
45 Kyle Kalis OT 57.75 18 21 52 140  
47 Dominique Wheeler WR 59.25 66 48 78 45  
48 Devin Fuller QB 60.75 37 150 17 39  
49 Chris Casher DE 61.5 83 57 96 10 Florida State
50 Durron Neal WR 65 32 61 105 62 Oklahoma
51 Tommy Schutt DT 65.5 29 47 51 135  
52 Eli Harold OLB 71.25 59 58 38 130  
53 Channing Ward DE 73 120 37 41 94  
54 Adolphus Washington DE 74.75 86 19 98 96  
54 Barry Sanders RB 74.75 121 50 50 78  
56 Ricky Parks TE 77.75 92 80 66 73 Auburn
57 Zach Banner OT 79.75 31 46 117 125  
58 Connor Brewer QB 80.5 123 117 56 26 Texas
59 Avery Johnson WR 80.75 43 83 155 42 LSU
60 Tee Shepard CB 83.5 51 49 145 89 Notre Dame
61 Carlos Watkins DT 84.5 76 91 30 141  
62 Jonathan Bullard DE 84.75 16 106 136 81  
63 Alex Ross RB 86.5 183 89 36 38 Oklahoma
64 Quay Evans DT 87.5 169 7 141 33  
65 Joel Caleb WR 89.5 44 210 55 49  
66 Davonte Neal WR 91 136 114 86 28  
67 Brock Stadnik OT 91.25 165 69 72 59 South Carolina
68 Torshiro Davis OLB 93.75 97 136 71 71 LSU
69 Travis Blanks S 94.25 27 124 215 11 Clemson
70 Erik Magnuson OT 96 34 96 85 169 Michigan
71 Zach Kline QB 96.25 40 128 157 60 California
72 Mario Pender RB 98 53 88 204 47 Florida State
73 T.J. Yeldon RB 98.5 58 105 110 121 Auburn
74 Brian Poole CB 99 75 42 143 136 Florida
75 Reggie Ragland MLB 102.75 217 35 47 112 Alabama
76 Jordan Diamond OT 103 209 40 60 103  
77 LaDarrell McNeil S 105.25 107 51 83 180  
78 Peter Jinkens OLB 106 101 101 166 56 Texas
79 Byron Marshall RB 108.25 90 118 135 90  
80 Se'von Pittman DE 109.25 61 79 196 101 Michigan State
81 Germone Hopper WR 109.75 102 172 101 64 Clemson
82 Javonte Magee DT 110 127 81 44 188  
83 Terry Richardson CB 110.75 195 149 31 68 Michigan
84 Tyriq McCord DE 111 60 181 103 100  
85 Brian Nance OLB 113.75 73 125 67 190  
86 Avery Young OT 114.25 38 13 287* 119  
87 Dan Voltz OG 115 154 99 23 184 Wisconsin
87 Kendall Sanders CB 115 54 94 142 170 Oklahoma State
89 Devonte Fields DE 115.75 147 145 102 69 TCU
89 Kent Taylor TE 115.75 68 63 185 147  
91 Michael Starts OG 116.5 148 70 119 129 Texas Tech
92 Anthony Alford QB 117.25 105 230 35 99  
93 Justin Shanks DT 118.75 111 84 162 118  
94 Angelo Jean-Louis WR 119 113 223 88 52 Miami (FL)
95 Evan Boehm C 122 130 100 203 55 Missouri
96 Royce Jenkins-Stone MLB 123.25 87 115 174 117 Michigan
97 James Ross MLB 123.5 143 73 84 194 Michigan
98 Jordan Payton WR 124.25 96 56 199 146 USC
99 Derrick Woods WR 124.5 81 180 109 128  
100 Elijah Shumate S 124.75 112 93 76 218  
101 Brian Kimbrow RB 128.75 80 153 128 154  
102 Sterling Shepard WR 129.25 220 108 131 58 Oklahoma
103 Matt Davis QB 131.25 144 38 187 156 Texas A&M
104 Brionte Dunn RB 131.75 124 28 154 221 Ohio State-ish
105 Colin Thompson TE 133.75 197 95 160 83 Florida
105 Zeke Pike QB 133.75 72 33 18 412* Auburn
107 P.J. Williams S 134.5 173 127 124 114 Florida State
108 Dwayne Stanford WR 134.75 93 107 228 111  
109 Isaac Seumalo OG 135.5 175 168 134 65  
109 Jaquay Williams WR 135.5 94 116 173 159 Auburn
111 Bralon Addison WR 137 155 119 137 137 Texas A&M
112 Ronnie Stanley OT 140 149 76 62 273  
113 Sheldon Day DT 142.25 280* 65 80 144  
114 Deon Bush S 142.5 65 264 175 66  
114 Matt Jones RB 142.5 157 82 178 153 Florida
116 Kevon Seymour CB 143.75 85 193 132 165  
117 Jelani Hamilton DE 145 79 62 92 347* Miami (FL)
118 Alex Carter S 145.5 62 287 118 115 Stanford
119 Dillon Lee MLB 148 232 207 81 72 Alabama
120 Lorenzo Phillips OLB 149.5 146 199 111 142  
121 Vadal Alexander OG 151.25 280* 126 108 91  
122 Jalen Cope-Fitzpatrick TE 152 180 123 183 122  
123 Wayne Morgan S 155.75 139 270 33 181  
124 Paul Thurston OT 159.5 137 112 231 158 Nebraska
124 Timothy Cole OLB 159.5 99 151 129 259 Texas
126 Scott Starr MLB 160.75 110 186 106 241 USC
127 Korren Kirven DT 161.5 280* 194 63 109  
128 Marcus Maye S 162.75 128 195 120 208  
129 Cyrus Jones RB 165.25 224 250 150 37  
130 Denzel Devall DE 165.75 125 232 91 215  
131 Eugene Lewis WR 166.25 162 67 219 217  
132 Leonard Floyd DE 166.75 159 121 94 293 Georgia
133 Justin Thomas WR 168.75 205 217 82 171 Alabama
134 Reginald Davis WR 169.25 214 120 261* 82 Texas Tech
135 Amos Leggett CB 169.5 104 404* 75 95 Miami (FL)
136 Troy Hinds DE 170.75 215 72 114 282  
137 Greg Garmon RB 172.25 184 68 232 205  
138 Max Tuerk OT 172.5 103 243 287* 57 USC
139 Drae Bowles WR 173.25 109 300 182 102  
139 Leonard Williams DE 173.25 71 228 287* 107  
139 Vince Biegel OLB 173.25 95 218 214 166 Wisconsin
142 Faith Ekakitie DT 173.5 100 216 104 274  
142 J.J. Denman OT 173.5 242 111 181 160 Penn State
144 John Michael McGee C 173.75 82 169 210 234  
145 Camrhon Hughes OT 174.75 89 74 261* 275 Texas
146 Brandon Beaver CB 175.25 114 166 77 344*  
147 Quanzell Lambert MLB 178 117 204 127 264  
148 Kenyan Drake RB 180.5 280* 139 73 230 Alabama
149 Chris Muller OT 183.75 69 324* 100 242 Rutgers
150 Patrick Miller OT 184 199 222 113 202  
151 Keivarae Russell RB 185 106 152 42 440*  
151 Orlando Thomas CB 185 119 269 133 219 Texas
153 Camren Williams OLB 185.25 243 138 116 244 Penn State
154 Ty Darlington C 186 118 241 287* 98  
155 D.J. Foster RB 186.5 74 200 287* 185  
156 Aaron Burbridge WR 189.25 134 90 229 304*  
156 Ken Ekanem DE 189.25 185 191 159 222  
158 Ishmael Adams CB 191.5 98 253 201 214  
159 Curtis Riser OG 192.5 244 220 123 183 Texas
159 Marvin Bracy WR 192.5 245 177 238 110  
161 Joshua Perry OLB 194.75 131 231 235 182 Ohio State
162 Taylor McNamara TE 196.5 84 302* 144 256 Arizona
163 Chris Wormley DE 198.75 452* 113 57 173  
164 Raphael Kirby OLB 199 126 233 287* 150 Miami (FL)
165 Greg McMullen DE 202 88 183 140 397* Nebraska
166 Tyler Hayes OLB 203.75 452* 122 115 126 Alabama
167 Cyler Miles QB 204 160 272 138 246 Washington
168 Deaysean Rippy OLB 205.5 247 103 146 326*  
169 Dalvon Stuckey DT 207.25 207 171 184 267 Florida State
169 Omari Phillips OT 207.25 225 258 233 113 Florida
171 Jordan Watkins DE 207.75 171 142 163 355*  
172 Joe Bolden OLB 211 167 238 287* 152 Michigan
173 Ronnie Feist OLB 211.75 204 251 261* 131 LSU
174 Sean Price TE 219.75 190 301* 164 224  
175 Freddie Tagaloa OT 220.25 206 219 188 268  
176 Mike Davis RB 220.75 122 234 198 329* Florida
177 Kaiwan Lewis MLB 221 280* 158 240 206  
178 Jaleel Johnson DT 223.25 140 203 261* 289  
179 Nick James DT 223.75 452* 110 107 226  
180 Michael Barton OLB 226 280* 182 205 237 California
181 Beniquez Brown OLB 227 452* 134 195 127  
182 Martin Aiken DE 227.5 189 97 243 381*  
183 Paul Boyette DT 227.75 168 224 323* 196 Texas
184 Michael Moore DE 229.25 176 286 125 330* Virginia
185 Jeremi Powell OLB 229.5 218 275 170 255 Florida
186 Warren Ball RB 230 212 52 206 450* Ohio State
187 Reggie Daniels S 231.5 280* 154 208 284  
188 Adam Bisnowaty OT 234.75 177 302* 202 258  
189 Shane Callahan OT 235.25 191 173 323* 254 Auburn
190 Jonathan Williams RB 238 170 209 246 327* Missouri
191 Chad Voytik QB 242.5 153 277 368* 172  
191 Deontay McManus WR 242.5 108 247 139 476*  
191 Mike Madaras OT 242.5 230 260 287* 193 Maryland
194 Evan Baylis TE 242.75 280* 189 225 277 Oregon
195 Bart Houston QB 246.25 452* 160 197 176 Wisconsin
196 Jordan Diggs S 248.25 280* 268 158 287  
197 Deion Bonner S 252.5 452* 176 153 229  
198 Lacy Westbrook OG 255.75 213 137 186 487*  
199 Trevor Knight QB 264.75 228 274 261* 296 Texas A&M
200 Amara Darboh WR 268.75 194 161 148 572*  
201 Jody Fuller WR 272.75 210 543* 152 186  
202 Malcolm Lewis WR 274 164 596* 193 143  
203 Armani Reeves CB 274.25 187 144 59 707*  
204 Darreus Rogers WR 280.75 172 135 74 742* USC
205 Zac Brooks WR 282.5 174 278 126 552*  
206 Tom Strobel DE 284 231 211 169 525* Michigan
207 Quinteze Williams DE 285.25 452* 279 190 220 Florida
208 Bryce Treggs WR 288 133 102 230 687*  
209 Gabriel Marks CB 289.5 166 239 172 581*  
210 Ondre Pipkins DT 295 246 175 149 610*  
211 Kyle Dodson OT 302.25 152 187 192 678* Wisconsin
212 Brandon Fanaika OG 308.5 202 257 213 562*  
213 Edward Pope S 319.5 193 280 218 587* TCU
214 Quinshad Davis WR 321 250 292 234 508*  
215 Leonte Carroo WR 326.25 211 86 245 763*  
216 Deontay Greenberry WR 331.5 115 244 209 758* Notre Dame
217 Michael Richardson DE 371.25 756* 294 226 209 Texas A&M
218 Kwontie Moore MLB 383.25 116 1054* 97 266 Virginia
219 Germain Ifedi OG 384 756* 285 242 253 Missouri
*imputed              



A final note about ESPN

Several commenters in my previous diary expressed that they’d like to see these rankings without ESPN.  I don’t think there’s enough reason or evidence to dismiss ESPN entirely.  However, for those who are interested, here’s how some recruits would rank among the above prospects if ESPN were excluded:  Kalis (23), Washington (55), Magnuson (57), Ross (76), Dunn (79), Diamond (82), Richardson (104), Jenkins-Stone (106), Stanford (123), Burbridge (131), Pipkins (169), Strobel (181), Wormley (183), Bolden (201).  Of course, the list of prospects included would change if ESPN were ignored altogether.

Comments

Hardware Sushi

June 23rd, 2011 at 5:37 PM ^

Good work, Turd. I would greatly appreciate that breakdown as well. If I were choosing a favorite poo, you'd be in my top three, behind Mr. Hankey and in front of Bono (he can't be #2 again).

Winnie is an obvious OSU cooler pooper, what with his scarlet shirts and redneck temperment, and him & all his autograph-for-honey schemes will come out soon enough.

wlubd

June 23rd, 2011 at 4:48 PM ^

Really nice. Only recommendation I might have which I've seen others use when doing this is to not use the actual overall rank for kids outside the top whatever for that site. Reasoning behind that is just that you've already ensured these guys are in 3 of the 4 rankings so only one of the sites is going to be an outlier, you could chalk that up to just poor scouting by that site.

For example, Kwontie Moore is 218th but has overall ranks of 97, 116, 266 and 1054(!). He's getting dragged way down because of that last number but since that one seems to be the outlier, it could be discarded.

Since Scout ranks the most with 300, I'd recommend that anyone with a rank higher then that just be scored at 301 for that site. It would largely eliminate that outlying score which isn't really being considered anyway since they need to appear on 3 of the 4 lists.

Just my 2 cents. Love this though. Eliminates most of the biases across different sites.

 

turd ferguson

June 23rd, 2011 at 5:02 PM ^

This is one of the many ways to impute data.  In truth, though, I don't like it as much.

With a small number of data points (four), I think you have to be careful about dumping data.  That's especially true if some of these sites are looking to the others for guidance (meaning that we really wouldn't have four independent data points).

More generally, I think it's important information that Site X really dislikes a certain recruit.  If you give everyone a 301 or 350 or something, you lose all of that information.  My preference is to incorporate everything you have, doing the best job you can with available data to pinpoint a ranking.  Kwontie Moore is particularly unusual because Scout thinks so little of him that he didn't make their MLB rankings at all.  My view is that this is relevant information (especially b/c Scout feels so strongly about that that it's willing to be an outlier).  Other views might be reasonable, too.

turtleboy

June 23rd, 2011 at 5:24 PM ^

hammered by ESPN. Reeves would be well within the top 150 but ESPN gave him a 700 something which is near twice his other 3 scores combined. Like the Soviet judge at the Olympics.

Edit:Kieth Marshall has the 2nd biggest outlier after Zeke Pike. The Rivals 55 rating more than triples his average from 6 to 18.25, whereas Zekes ESPN outlier makes his average 3.262 times greater than the other 3 services consensus.

turtleboy

June 23rd, 2011 at 4:54 PM ^

It's strange to see where they actually agree on anybody. It feels like Scout and 247 rate guys as Sophomores and leave it that way for a while, and Rivals and ESPN rate kids as Juniors, but they all change down the road. Some of the outliers are just funny. Magnuson 34th to Rivals, 169th to ESPN. TRich 31st to 247, 195th to Rivals. The top 15 are funny to see just how much they disagree. Reminds me of the Keystone Cops in their clumsy dilligence. Pipkins numbers are going to skyrocket his senior year, lol.

MI Expat NY

June 23rd, 2011 at 4:51 PM ^

Nice work.  This is probably the best way to get a sense of how a recruiting class stacks up.

One note, as much as I wish it weren't true, Pittman did commit to MSU.

rockydude

June 23rd, 2011 at 5:02 PM ^

Appreciate the time that you must have put in to do this. This gives me lots of new stuff to ponder. Heaven forbid that there is a hair that goes unsplit or a pebble that remains unturned . . . 

PS - love the Bri"onte Dunn commitment area - "Ohio Statish" . . . . 

Mr Mackey

June 23rd, 2011 at 4:54 PM ^

Question - how does Marshall have rankings of 5, 6, 7, and 55?! That's one serious outlier.

Also, it might be nice to bold or italicize recruits of interest. I'm lazy, and I was only really interested in finding recruits that we're going after or that we have. 

I like this a lot though, nice job.

EDIT: I realize you did bold the commits, but I'm talking about targets, too.

Gary_B

June 23rd, 2011 at 4:56 PM ^

Given 219 players, each team from a BCS conference, assuming all teams are on equal ground (they aren't, I know) should average 3.42 players from this list. Texas has 12 and doesn't have to leave the state to recruit. Must be nice.

turtleboy

June 23rd, 2011 at 5:03 PM ^

For the most part you see a general consensus from Rivals, Scout, and 247. ESPN almost has a monopoly on outliers. Running down the list you see ESPN differ greatly from the other 3, for years I thought I was just imagining it. 

turd ferguson

June 23rd, 2011 at 5:21 PM ^

Interesting idea, but my own view is that this, too, drops too much information.  I made a similar point above, but we're working with limited data points for each observation, and I tend to think that the outliers tell us something important.  Basically, these are the prospects for which a site feels so strongly that a recruit is over/underrated that it's willing to go on a limb. 

Zeke Pike offers an interesting example.  His rankings are 72, 33, 18, and 412.  The 412 comes from ESPN and is its actual ranking (i.e. not really imputed).  If we were to take the median, Pike would have a 52.5, which should easily place him in the top 50.  Maybe ESPN's crazy and that's the right thing to do, but the fact that they dislike him that much seems relevant to me.  His current ranking of #105 feels more appropriate.

DeuceInTheDeuce

June 23rd, 2011 at 6:41 PM ^

No information is "dropped" when using median; the data still exists.  The idea is to use the method that best estimates a true average. When outliers are rampant (e.g. salaries, home values) median is typically a better average than mean.  The Pike example was cherry-picked, as CW has his stock dropping. Pipkins makes an easy in-kind counterpoint. Regardless, I applaud your effort and hope you provide us with future updates. 

turd ferguson

June 23rd, 2011 at 7:13 PM ^

Technically, I guess you're right that medians don't "drop" data, but they definitely lose some of the nuance.  Mat articulated this well below, but I'll use a real player.  I'm not cherry-picking this based on a trend; the numbers just illustrate the point well.

Take Devin Fuller.  He's ranked #17, #37, #39, and #150 by the recruiting services.  Scout has him at #150, which clearly reflects some uncertainty about him as a prospect (since they're willing to publicly be much more down on him).

The median of Fuller's rankings would be 38.  It wouldn't change at all whether Scout ranked him at #38, #150, or as a one-star player.  My view is that it's a mistake not to incorporate that information.  If Fuller committed to Michigan tomorrow, I would note Scout's reservations in my mind, not just write them off as an outlier.

If there were 100 recruiting services here, I would completely agree.  (This, by the way, would bring us closer to your salary & home value situations.)  Hell, maybe one of them would rank a top 10 recruit at #80,000 because the kid slept with the guy's mom.  We don't have enough data points to make that a good idea, though. 

miCHIganman1

June 23rd, 2011 at 5:04 PM ^

Thanks for posting this. I hope this ranking system actually catches on around this blog.
<br>
<br>While we're talking about great user created content, does anyone know what became of the recruiting map that was posted about a month ago? I thought that was also a great idea and took a bit of work. Would love to see an updated version of that.

UMaD

June 23rd, 2011 at 5:57 PM ^

I know theres still some quibbling about how much the outliers should affect the rankings, but removing the veto thing is the biggest fix you could make in that regard.

I agree with you about the median/mean issue - cutting out information with so few sources is highly debateable.

Here's a few ideas for taking these rankings up a notch if you want to take it further:

1.   Add an average star ranking.  Star rankings are something everyone's familiar with so if a guy is 3.25 or 3.75 stars, we'll all know what that means.

2.  Run the same (or similar) process for position specific rankings.

3.  Quantify unanimity of the services.  It would be pretty simple to calculate a number and then covert it into something digestable for non-technical folks "e.g., high level of agreement, moderate, low"

If you do all this I think you could have a pretty popular link and maybe even a blogpage that might get enough hits to give you some pocket change. The key would be to make it easily digestable.  Just a thought...

 

JohnnyV123

June 23rd, 2011 at 5:57 PM ^

Like I said on your other diary I really like what you've done but as a few other mentioned those outlier rankings really bother me and affect the standings too much.

When you see one recruiting site disagreeing on a player by 400-900 ranks something is going wrong.

What do you define as an outlier? On the small scale looking at someone like Keith Marshall at #14 the 4 sites have him at 55, 5, 7, 6 which if you call the 55 an outlier would bring him into the top 3.

But then that one rank doesn't look as off when you have Amara Darboh at 194, 161, 148, 572 (outlier of 378 spots) the already mentioned Kwontie Moore 116 1054 97 266 (outlier of 788 spots) or Leonte Caroo 211 86 245 763 (outlier of 552 spots).

This is why a median would work well as was suggested above.

UMaD

June 23rd, 2011 at 6:38 PM ^

If one guy gets ranks of 6, 8, 10, and 170 why would you rank him the same as a guy who gets ranks of 7, 7, 9, 9?

The median is the same.  But they shouldn't be viewed as equivalent.

By tossing out the 170 you're ignoring the fact that one site has serious doubts about a guy, while there is unanimity in opinon of the other. 

There's many many examples where throwing out the top and bottom values (half the infomration you have) leads to misleading results.

DeuceInTheDeuce

June 23rd, 2011 at 6:56 PM ^

First, your calculation isn't correct. Second, the aim is to develop a reasonable estimate for the next credible data point.  Assume this next data point is provided by Lemming (I know, I know), using your made up player above, which is a better guess at Lemming's ranking of that player, 48.5 (mean) or 8 (median)? Given the type of data, most statisticians would argue the latter.

UMaD

June 23rd, 2011 at 11:58 PM ^

You're not trying to guess what another recruiting analyst would do, you're trying to aggregate what various sites think about someone.  Throwing out opinions doesn't do that well.

I realize that median is generally superior to mean, but in this case (when you want to include all opinions, including the outliers) its not. 

At the very least, if you're going to rate by the median you'd want to add an uncertainity value.

And yes, you're right that my math would be different, but you got my point.

bacon

June 23rd, 2011 at 6:51 PM ^

I really like your analyses.  I'd like to see these rankings account for the ranking of a player within his position group (complicated by the fact that some players aren't ranked the same in all positions).  There has to be a factor that could correct for situations where some positions are just naturally ranked lower, but where having the top player at a given position should reflect favorably on the school the player goes to.

Hill.FootballR…

June 23rd, 2011 at 10:46 PM ^

Thanks this is some great info I really like what you did and agree that a median would be less informative. I am a majoring in engineering and one major thing i have learned is that when you has less than 10 independent data points you should not disclude any or rely on anything but the mean. With this said I think you could get extremely creative by considering a way to include the median as 1/5 of the data points. By doing this you would then calculate the median for each player, make a separate column for it like you have for Rivals, Scouts, 247 and ESPN and include that number to give you your mean. this would make a player ranked 7,7,9,9 ranked much better than a 7,7,9,200 but would make a player with a major outlier like Marshall and players mentioned above less of a factor. I also like the star rankings average that would be cool as mentioned above and the idea for individual positions but I know how much time this takes. What you have is excellent and everyone will always have an opinion to what is wrong with your way of combining stats so don't worry too much about those who don't appreciate everything you did.

With all of this said I would like to post a diary of some information I created last Friday but I am having trouble inserting an excel spreadsheet like this from my computer. Can someone tell me how to upload a table like this to mgoblog?

 

Picktown GoBlue

June 24th, 2011 at 12:37 AM ^

and i can certainly understand your plea for no quick changes in the sites' ratings.  Tried pulling the data to run some scenarios myself, got pretty decent formulae for extracting info from the webpages, but then ran into the fact that for too many of the guys, they do not use standard spellings of their names, so there's a ton of manual work involved to build up this kind of calculation.  Bravo!

Agree on your position of using mean vs. median; for a player with rankings from all 4 sites, the median is going to be mathematically equivalent to dropping the highest and lowest and averaging the remaining two (and thus eliminates too much useful data).

SKIP TO MY BLUE

June 24th, 2011 at 4:12 PM ^

Funny how each site has the rankings flipped for Ross & Stone which makes them each top prospects even though you may not know it by looking at only one site.

 

96 Royce Jenkins-Stone MLB 123.25 87 115 174 117 Michigan
97 James Ross MLB 123.5 143 73 84 194 Michigan

Tacopants

July 4th, 2011 at 2:15 AM ^

 

I don't think that much granularity really will make the difference.  What does it mean to be the #251 overall or the #291 overall?  More precisely, since recruits are ranked by position, does it matter that much if you're the 40th TE or the 45th TE?  I would say no.

As an easy rule of thumb, I figure that anybody that makes a 150/250/300 list is heavily scouted and most sites assign them the 5/4 stars.  Beyond that, it's hard to tell within the sea of 3 stars who is there on ability and who is there because they didn't camp/late bloomer/play for a small terrible team etc.  There is a consensus at the top with the 5 star/high 4 star level (as in, he's really good!), followed by a steep level of variation.  This is to be expected, as obviously the rankings are subjective.  You don't know why the #20 CB is ranked 200th but the #21 CB is ranked 240th.  is that sign of a huge gap in talent?  Or is it because the guy who was in charge of scouting the 21st CB didn't speak up, or didn't have enough influence? You're trying to get very granular on a flawed set of data.

To look at the variability, just take your matrix and look at standard deviations.

  • For prospects 1-10, the average standard deviation is 6.  Not great, but not too bad
  • For prospects 1-25, the average standard deviation is 12.  (16 for 11-25)
  • For prospects 1-50, we're up to 20.  (28 for 26-50)
  • For prospects 51-100, the average standard deviation is 54 spots.
  • For prospects 101-200, the average standard deviation is 83 spots
  • For the remaining 20 prospects, the average deviation is 233 spots.
  • As a whole, from 101-220, the deviation was at 107.

Taking a quick look at those numbers, there seems to be a consensus among the top 50 or so athletes.  I don't feel like running the numbers, but I bet you can find a significant difference within the deviations of players between 1-50 and any other set of 50 players.  Once you move past the top 50, the recruiting sites start disagreeing much more on individual placement.

So again, I think we're trying to reinvent the wheel here.  Without each scout scouting all 1500 3*+ players, I don't think you're ever going to get a great ranking system beyond player #50 or so.

Some other fun things:

  • Dropping ESPN doesn't have a huge impact to variances.  They do go down (as to be expected if you remove 25% of a data set), but not to the point where you could really call out ESPN for being too crazy
  • Your player with the most disagreement is Kwontie Moore (#218) with a whopping 453 as a standard deviation.  Thanks a lot, Scout.
  • Your player outside the top 100 that has the lowest deviation is Bralon Addison #111 ranked here.  The sites agree, he's somewhere around the #137th best player in the nation.  No site has him ranked above #119.
  • Meawhile the player in the top 100 that has the most deviation is Travis Blanks, #69 at 95 positons.  This is due to two services ranking him in the top 30, one at 124, and 24/7 has him at 215.
  • A total of 15 prospects on your list rank better by aggregate than they did on any of the 4 lists. 

turd ferguson

July 4th, 2011 at 7:00 PM ^

Lots of fun stuff in here.  Thanks for the response.

The one point on which we most clearly agree:  these rankings aren't great past #200 (for those last 20 guys or so).  Initially, I dropped them and called it a top 200, but I figured that someone would get irritated by that and want to decide for him/herself what to make of the last 20. 

More generally, I also agree that there's a decent amount of variation across the sites.  I disagree, however, that this is reason to give up on aggregated rankings.  The fact that there's variation across the sites is exactly why it's useful to aggregate like this.  If there were general agreement, then it wouldn't be hard to figure out who's where.  In general, too, we should believe that a recruit who's ranked #251 is more highly regarded than one who's ranked #291.  It's true that those are difficult judgments for the sites to make, but on average, I see no reason not to assume that the recruiting service generally likes a player who's ranked a little higher more than one who's ranked a little lower.

On another note, I really like those points at the bottom of your post, and you hit on something that I think is important.  You said that 15 recruits ranked better in aggregate than in any individual ranking.  Part of the reason that I think this type of aggregation is useful is a trick that numbers play on people.  When I look at a recruit who's ranked, say, #95, #100, #100, and #105, I might be tempted to say that he's roughly the 100th most highly regarded recruit.  That's not true.  He's actually #75.  This is hard to see without aggregated rankings.

(I just noticed that you stuck this in the original post, too -- thanks for that -- so I'll post my response there as well.)