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Around SBN: This Week In GIFs

Defensive Score Sheet: Kentucky vs Georgia

Here is the defensive score sheet for Saturday's game against Georgia.  For an explanation of what this is, you can go here.  I revamped the sheets I use to keep track of what happens so in the future I should be better able to answer some of the questions people had last time, especially concerning the offense/defense matchups.  I won't have it for this game, but I might be able to do it for Ole Miss and should be able to do so for Florida.

The Georgia came presented a couple of challenges in determining how to classify shots due to the zone that was played in the first half.  I think this game in particular had a lot more shots where it wasn't obvious who the defender(s) should be (if any) so I'll be interested to know how this jives with what people saw and remember from the game.

Star-divide

To try and make things a bit easier to read and digest, I've separated UK's results into three different tables.  The full table for both UK and Georgia are at the end.  I also highlighted the largest number in each category, in green if high=good and in yellow if high=bad.  I'll stress again that these numbers do not by themselves mean that a player defended poorly- they're an accounting, not a judgment.

 

Kentucky
Shot Defense
Name Min Def Rb Blocks Forced Miss Def FGM FT Miss Def FTM
Doron Lamb 31 2
5 0.5

Terrence Jones 26 7 1 8.5 3 2 2
TEAM
0
6 2

DeAndre Liggins 36 2 1 4 2.5
4
Eloy Vargas 5 0 1 1 0.5

Josh Harrellson 30 7 2 6.5 4 3 4
Brandon Knight 40 4
3 5 1 1
Darius Miller 32 5
2 2.5 1 3








Tracked Totals


36 20 7 14
BoxScore
27 5 36 21 7 14

 

  • I've included the box score totals so you can see how they matchup.  Somehow I missed an UGA field goal, but otherwise the accuracy in the totals is pretty good.
  • Terrence Jones once again was a top performer in defending missed shots.  Harrellson was second and Georgia missed a number of shots that were open either by poor defense by Kentucky or good passing from Georgia (or both).
  • Lamb had a pretty solid game.  He didn't send anyone to the line and did a good job forcing misses.

 

Kentucky
Ball Handling
Name Min Steals F.TO Deflections
Doron Lamb 31
1
Terrence Jones 26 1 0.5 1
TEAM

3
DeAndre Liggins 36 2 4 7
Eloy Vargas 5


Josh Harrellson 30 3 1.5
Brandon Knight 40
3 1
Darius Miller 32

1





Tracked Totals

13 10
BoxScore
6 13

 

  • This just in.  DeAndre Liggins is really active defensively.  Liggins leads the team in deflections again and forced 4 turnovers.  Actually, he had a hand in 5 TO's, forcing 3 by himself and hooking up with a teammate a couple of times.
  • You'll notice that I have Josh with only 1.5 forced TOs despite his 3 steals.  One of his steals was split credit with another player.  The other was a case where the Georgia player basically just threw the ball right to him.  In that instance the only thing Josh did was happen to be standing in the right place at the right time, he didn't really do anything to "force" it, so I put that one in the "Team" category.
  • Liggins and Knight both had tie-ups that resulted in a jump ball where Georgia kept the ball.  I counted those as Deflections since they fall under the general idea of disrupting the offense.

 

Kentucky
Calculations
Name Min Stops Stop% %Tm Def. Poss Def Rtg
Doron Lamb 31 3.5 0.9 0.06 85.84
Terrence Jones 26 7.3 0.7 0.17 87.43
TEAM
4.5 0.7 0.1 87.43
DeAndre Liggins 36 6.3 0.6 0.16 89.55
Eloy Vargas 5 0.3 0.3 0.01 90.23
Josh Harrellson 30 7.9 0.6 0.2 90.33
Brandon Knight 40 6.4 0.5 0.18 91.64
Darius Miller 32 3.8 0.5 0.11 92.04






Tracked Totals
39.9 0.6 0.99 87.3
BoxScore
39.9 0.6 1 89.24

 

  • Here are the calculated metrics based on the previous two tables.  I didn't go into any detail on Defensive Rating last time, but you can think of it as sort of a basketball equivalent to ERA in baseball.  It's an estimate of the number of points that are scored against a player, scaled out to 100 possessions (in the same way ERA is scaled out to 9 innings).
  • Liggins' rating is basically "team average" which I thought was odd, but it's mostly due to the guys he sent to the line hitting all their free throws.
  • You can see that Josh was involved in fully 20% of the defensive plays and personally stopped them 60% of the time.  That tracks with the inside oriented approach Georgia used in the game.
  • When Lamb was directly involved in the defensive play, he ended it 90% of the time without the opponent scoring.  Unfortunately, he was only involved in about 6% of the plays.

Here are the full tables.  For Georgia's defense, they have 1 more TO forced than the box score and I think that came on a play where a UK player got a defensive rebound only to have it stripped by a Bulldog.  I counted it as a TO while the official scorer counted it as an offensive rebound by Georgia.  That's my best guess anyway.

 

Kentucky
Shot Defense Ball Handling Calculations
Name Min Def Rb Blks F.Miss Def FGM FT Miss Def FTM Stls F.TO Defl Stops Stop% %TmDPoss Def Rtg
Doron Lamb 31 2
5 0.5


1
3.5 0.9 0.06 85.84
Terrence Jones 26 7 1 8.5 3 2 2 1 0.5 1 7.3 0.7 0.17 87.43
TEAM
0
6 2


3
4.5 0.7 0.1 87.43
DeAndre Liggins 36 2 1 4 2.5
4 2 4 7 6.3 0.6 0.16 89.55
Eloy Vargas 5 0 1 1 0.5




0.3 0.3 0.01 90.23
Josh Harrellson 30 7 2 6.5 4 3 4 3 1.5
7.9 0.6 0.2 90.33
Brandon Knight 40 4
3 5 1 1
3 1 6.4 0.5 0.18 91.64
Darius Miller 32 5
2 2.5 1 3

1 3.8 0.5 0.11 92.04















Tracked Totals
36 20 7 14
13 10 39.9 0.6 0.99 87.3
BoxScore
27 5 36 21 7 14 6 13
39.9 0.6 1 89.24

 

 

Georgia
Shot Defense Ball Handling Calculations
Name Min Def Rb Blks F.Miss Def FGM FT Miss Def FTM Stls F.TO Defl Stops Stop% %TmDPoss Def Rtg
Gerald Robinson 37 3
6.5 2 1
2 2 1 6.2 0.8 0.12 93.2
Marcus Thornton 11 3 1 2 0.5

1 1
3.44 0.9 0.06 94.39
Jeremy Price 24 6


5 2

1 3.91 0.8 0.07 94.46
Trey Tompkins 29 9
4 3.5




6.59 0.7 0.15 95.47
Sherrard Brantley 9 0







0 0.0 0 98.5
Donte Williams 8 2
1.5 0.5
2


1.69 0.5 0.05 98.68
Chris Barnes 20 3

1
2


1.71 0.5 0.05 99.61
Travis Leslie 31 0
2 3 1 2 2 2
2.84 0.4 0.1 101.75
Dustin Ware 31 2
7 5.5 1 1

1 3.81 0.4 0.15 104.22
TEAM
1
6 6 1 7
5
7.87 0.5 0.25 104.34















Tracked Totals
29 22 9 16
10 3 38.06 0.6 1 98.12
BoxScore
29 1 29 22 9 16 5 9
37.06 0.6 0.99 98.5

 

Update (2-07-2011) I discovered an error in the calculations that affected the calculated values.  The correct tables are below.

 

Kentucky
Shot Defense Ball Handling Calculations
Name Min Def Rb Blks F.Miss Def FGM FT Miss Def FTM Stls F.TO Defl Stops DScPoss DPoss Stop% %TmDPoss Def Rtg
Terrence Jones 26 7 1 8.5 3 2 2 1 0.5 1 7.1 3.9 10.97 0.6 0.25 86.72
Josh Harrellson 30 7 2 6.5 4 3 4 3 1.5
7.4 5.8 13.18 0.6 0.26 91.46
Darius Miller 32 5
2 2.5 1 3

1 3.1 3.9 6.9 0.4 0.13 93.85
Brandon Knight 40 4
3 5 1 1
3 1 6.0 5.5 11.46 0.5 0.17 92.15
Doron Lamb 31 2
5 0.5


1
3.8 0.5 4.33 0.9 0.08 84.25
DeAndre Liggins 36 2 1 4 2.5
4 2 4 7 6.4 4.3 10.74 0.6 0.18 89.32
Eloy Vargas 5 0 1 1 0.5




0.4 0.5 0.89 0.4 0.11 93.18
TEAM 40 0
6 2


3
5.4 2.0 7.35 0.7 0.11 86.33

















Tracked Totals 200 27 5 36 20 7 14 6 13 10 39.5 26.3 65.8 0.6 0.2 89.25
BoxScore 200 27 5 36 21 7 14 6 13
39.5 27.3 66.82 0.6 0.2 89.6

















Georgia
Shot Defense Ball Handling Calculations
Name Min Def Rb Blks F.Miss Def FGM FT Miss Def FTM Stls F.TO Defl Stops DScPoss DPoss Stop% %TmDPoss Def Rtg
Trey Tompkins 29 9
4 3.5




4.45 3.5 7.95 0.6 0.12 98.62
Jeremy Price 24 6


5 2

1 1.61 0.9 2.51 0.6 0.04 97.84
Travis Leslie 31 0
2 3 1 2 2 2
3.49 3.9 7.39 0.5 0.11 100.79
Dustin Ware 31 2
7 5.5 1 1

1 5.34 6.0 11.29 0.5 0.17 101.98
Gerald Robinson 37 3
6.5 2 1
2 2 1 7.17 2.0 9.17 0.8 0.14 91.76
Marcus Thornton 11 3 1 2 0.5

1 1
2.95 0.5 3.45 0.9 0.05 95.12
Chris Barnes 20 3

1
2


0.56 1.9 2.46 0.2 0.04 101.3
Donte Williams 8 2
1.5 0.5
2


1.41 1.4 2.81 0.5 0.04 99.09
Sherrard Brantley 9 0







0 0.0 0 0.0 0 98.5
TEAM 40 1
6 6 1 7
5
9.45 9.2 18.6 0.5 0.28 102.02

















Tracked Totals
29 1 29 22 9 16 5 10 3 36.43 29.2 65.6 0.6 0.98 100.53
BoxScore 200 29 1 29 22 9 16 5 9
35.43 29.2 64.63 0.5 0.96 98.5

Comment 24 comments  |  0 recs  | 

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Gives Me A Headache

And 50 years ago I was a math major. But I read it, muchas gracias.

"I bring reason to your ears, and, in language as plain as ABC, hold up truth to your eyes." Thomas Paine, December 23, 1776

by Wild Weasel on Jan 30, 2011 6:16 PM EST via mobile reply actions  

Well, hopefully math isn't needed to understand most of it

I can see it with the calculations portion, but I’m trying to make that as intuitive as possible. The goal is to aid what we already look for in defense – forcing missed shots, forcing turnovers, being active – and trying to present a more complete picture of what happens in a game than what we get from just our own memory.

So for instance, if you watched the UGA game and thought the Bulldogs were scoring a lot against Knight, that would certainly seem to track with what I saw too. OTOH, if it seemed like Lamb wasn’t playing much defense, then I think there is reason to disagree as he did force some missed shots and didn’t send anyone to the line.

3 > 2, except for very large values of 2.

by JLeverenz on Jan 31, 2011 10:41 AM EST up reply actions  

The tie balls

are a half a turnover in a sense when the possessing team keeps the ball because the next time you get the ball.

I woke up feeling BLUE this morning. It's gonna be a great day.

by kywineman on Jan 30, 2011 7:06 PM EST reply actions  

Well, maybe

I can see that, but in terms of actually recording what happens, I think it fits better under deflection. There’s no guarantee that the next jump ball will result in a TO, or even that there will be a next jump ball at all.

3 > 2, except for very large values of 2.

by JLeverenz on Jan 31, 2011 10:25 AM EST up reply actions  

Thanks JL

I must admit I don’t understand all of it yet, but it will grow on me. I appreciate all the time you invest to capture, analyze, and present the data.

by jdogblue on Jan 30, 2011 9:34 PM EST reply actions  

Honestly, I don't understand it all either

Recording defense this way is a fairly new idea and it hasn’t been done very much, so I think it is going to be a while before we really know how to read these in the same way we know how to read a typical box score.

One of the reasons for posting these on ASoB is that I hope the thoughtful, intelligent, insightful members will collectively be able to figure out some things about what gets recorded.

3 > 2, except for very large values of 2.

by JLeverenz on Jan 31, 2011 10:28 AM EST up reply actions  

Those adjectives

Leave me out! ’-) Unless FUN is thoughtful?!? j/k
But I do realize and appreciate the effort you put into this JLev. I see it as pioneer-like. Love our intelligent members.

Blue... there is no other color to Bleed !!!

by a2d2 on Jan 31, 2011 11:16 AM EST up reply actions  

Well, those adjectives were meant to be inclusive, not exclusive

I think everybody here has something they can contribute! But even if it is something like “I thought Liggins was the best defender, but here he is middle of the pack” I think there is value in discussing the observations during a game that lead to that conclusion and comparing it to what I write down.

3 > 2, except for very large values of 2.

by JLeverenz on Jan 31, 2011 1:01 PM EST up reply actions  

They are inclusive JLev

I was only kidding.

Blue... there is no other color to Bleed !!!

by a2d2 on Jan 31, 2011 1:17 PM EST up reply actions  

I know, I got the j/k

But I’m going to keep pushing for people to offer up their opinions because that’s what makes it interesting.

I’m glad that people appreciate the effort and I know that trying to understand everything can be a bit daunting when the only time you see it is in one of these posts, but what I really want to try and spark is some debate as to whether these counts are matching up with what everyone else is seeing during the game.

3 > 2, except for very large values of 2.

by JLeverenz on Jan 31, 2011 2:34 PM EST up reply actions  

The only problem

with trying to match your system with real game observations has already been pointed out. When we are watching the game it is subjective observation vs objective such as watching replays once the game is over. When its close or something negative is happening to UK, the weight of remembered observation goes to those moments with the most impact like a steal, turn over or a blocked shot. Those memories are the ones that leave us with our game impression rather than the nuts and bolts of good defense.

I woke up feeling BLUE this morning. It's gonna be a great day.

by kywineman on Jan 31, 2011 5:01 PM EST up reply actions  

It would take

more concentration than I am able to muster these days.

I woke up feeling BLUE this morning. It's gonna be a great day.

by kywineman on Jan 31, 2011 8:22 PM EST up reply actions  

I'm thinking more of a wisdom of crowds approach

If 4 people think Jones had a bad defensive game and 3 people think he had a good game, then between them they would ideally be able to come up with 7-8 instances or specific impressions that could then by compared to what I come up with.

That would give us a better idea of exactly what these sheets do and do not tell us about an individual defensive effort. Clearly we aren’t going to know everything about defense with something like this, but I think we can know a bit more.

3 > 2, except for very large values of 2.

by JLeverenz on Feb 1, 2011 12:46 PM EST up reply actions  

You have my vote

I think it’s fascinating, never bothered with stats before other than boxscore and play by play.
I always looked at nonball movement, rebound positioning, ect. Now I am hooked and can’t get enough. I appreciate every thing you do.

"SPORTS"--Not interested----"CATS"--Pull up a chair,I've got all night.

by kydamcat on Feb 1, 2011 6:27 PM EST up reply actions  

Thanks Ken

3 > 2, except for very large values of 2.

by JLeverenz on Jan 31, 2011 10:41 AM EST up reply actions  

Great work yet again

Excellent job compiling all of this, JL.

One question regarding these tables: is there a way to somehow indicate what’s a good/bad rating? I.e. for a given column, higher numbers are better, another column lower is better? That way it will be easier for those of us who are, shall we say, less mathematically inclined (such as myself), to better grasp what we are reading? It wouldn’t really require more work every time, just tacking on a “legend” if you will, indicating what we should be looking for.

Just a thought. I admire the effort it takes to record and translate all this. Want to make sure that more people can benefit from what you’ve painstakingly done.

by wildcatfaninexile on Jan 31, 2011 9:03 AM EST reply actions  

Clarification

That extra line I was talking about really only applies to some of the “calculations” columns. I think we can all pretty easily tell that getting 7 steals or a dozen deflections is a good thing…. I hope…haha!

by wildcatfaninexile on Jan 31, 2011 9:07 AM EST up reply actions  

Sure

Stops: this is the number of time an individual does something that ends the opponent’s offense without any points scored of any kind. This is what you want your defense to do, so higher is better.

Stop%: this is a ratio of the number of stops a player gets compared to the total number of times they are involved in a play that ends the offensive possession. That includes both when the opponent scores and when they do not score, so higher is better.

%TmDPoss: Each game consists of some number of possessions by each team, so there are X number of times when that team is on defense. This is the percentage of those X times that a player is involved with ending the possession. This one doesn’t really have a “good” or “bad” associated with it, but in general we want our best defensive players to be involved in the most number of possessions, so you can think of it that way.

Def Rtg: As I mentioned above, you can think of this in the same way as ERA in baseball – lower is better because this is essentially the number of points a defensive player allows the other team to score.

3 > 2, except for very large values of 2.

by JLeverenz on Jan 31, 2011 10:35 AM EST up reply actions  

Great stuff!

Wonderful, wonderful breakdown. Thanks for taking the time and sharing!

by Ed R on Jan 31, 2011 10:23 AM EST reply actions  

Thanks! Glad you like it!

3 > 2, except for very large values of 2.

by JLeverenz on Jan 31, 2011 10:35 AM EST up reply actions  

This thing is growing on me, JL...

I’m starting to wish I had all the calculations for it – especially the weighting for each stat in the overall rating to better understand why my impressions of the game don’t quite align with individual players’ ratings. I’m sure much of that is viewing bias/emotional investment while watching the game, but I imagine the originator’s weightings on various defensive skills and my own are also varied.

by dshnarw on Jan 31, 2011 7:56 PM EST reply actions  

I'll post the formulas in the next sheet

I am with you – I like to know how calculations are arrived at and what goes into them. I’ll post the formulas along with a brief explanation for some of the parts that Oliver wrote about in his book.

Glad to hear it’s growing on you!

3 > 2, except for very large values of 2.

by JLeverenz on Feb 1, 2011 12:47 PM EST up reply actions  

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