FanPost

A "Clutch Player" Defined - How do the Kings Players Stack up?

I recently posted about our prospects at Small Forward and a tangent ensued whether Cisco was more of a clutch player than his current King's peers. I was challenged that my word choice was merely an opinion without any statistical back up and despite a few trying to corroborate my assessment, no conclusion was reached. Since this accidental anecdote conjured more questions than answers, I felt it would be beneficial to cover this topic specifically. After the break I will define what is meant by "clutch", provide some background on what stats are associated with clutch performances and then see how our current Kings players stack up against the rest of the league.

Clutch is defined (as it relates to sports) as, "an extremely important or crucial moment of a game". A clutch player is one who "has done or accomplished (the above) in a critical situation and who is dependable in crucial situations.

I think we can all safely conclude that a player who is brought into a game with the game on the line is typically done so because they are dependable and those that perform under those conditions are considered clutch players. Think a Closer in baseball or the player who inbounds the ball in basketball with a few seconds left in the game or more importantly, the player who takes the last shot of a game.

Admittedly, statistical analysis is spotty on fully segregating clutch performance due in part to the nature of team sports. This varies from sport to sport. Football can easily chart an interception but an open receiver gets no stat for being open if the ball is never thrown his way or a lineman who successfully blocks his man gets no credit except from his line coach on film day. While baseball protects its pitchers from unearned runs when his performance is exceptional but due to an error by his fielder a run scores, basketball doesn't track how an offensive scheme is drawn up to avoid an exceptional defender in the low post.

At best statistical analysis can only tell part of the story. With that said there are a few statistically areas that have been leveraged to give visibility to how a player's contribution leads to their team winning and how clutch a player and their performance is. I will share a few that are meaningful to me.

Win Shares

Win Shares estimate the number of team wins based upon the contribution of a player. While its definition is simple its derivation is rather convoluted. Dean Oliver wrote a book entitled Basketball on Paper where among other things these formulas are fully described. Win Shares combines both Offensive Win Shares and Defensive Win Shares where the individual's offensive and defensive contributions translate into their team's wins. Offensive Win Shares factor individual players points produced and team's offensive possessions. Conversely Defensive Win Shares is based on Defensive Rating or points allowed per 100 defensive possessions. Finally you can evaluate Win Shares per 48 minutes where the league average is .100.

Calculating Offensive Win Shares:  (This can be done for all players back to the 1973-1974 season. For prior years where some stats weren't tracked go to Basketball Reference for the additional calculations needed.)

  1. Calculate points produced for each player.
  2. Calculate offensive possessions for each player
  3. Calculate marginal offense for each player. Marginal offense is equal to (points produced) - 0.92 * (league points per possession) * (offensive possessions).
  4. Calculate marginal points per win. Marginal points per win reduces to 0.32 * (league points per game) * ((team pace) / (league pace)).
  5. Credit Offensive Win Shares to the players. Offensive Win Shares are credited using the following formula: (marginal offense) / (marginal points per win).

Calculating Defensive Win Shares:  (This can be done for all players back to the 1977-1978 season. For prior years where some stats weren't tracked go to Basketball Reference for the additional calculations needed.)

  1. Calculate the Defensive Rating for each player.
  2. Calculate marginal defense for each player. Marginal defense is equal to (player minutes played / team minutes played) * (team defensive possessions) * (1.08 * (league points per possession) - ((Defensive Rating) / 100)). Note that this formula may produce a negative result for some players.
  3. Calculate marginal points per win. Marginal points per win reduces to 0.32 * (league points per game) * ((team pace) / (league pace)).
  4. Credit Defensive Win Shares to the players. Defensive Win Shares are credited using the following formula: (marginal defense) / (marginal points per win).

Compare these two scenarios:

Player 1 of Team A scores 5 of his team's 14 points and has 3 of his team's 10 rebounds over an 8 minute stretch but has 3 turnovers and two fouls and his counterpart on opposing Team B scores 9 of his team's 20 points and has 4 of his team's 11 rebounds while committing 1 turnover and 1 foul.

Player 2 of Team A scores 3 of his team's 14 points and 2 of his team's 11 rebounds over an 8 minute stretch has 1 turnover and 1 foul and his counterpart on opposing Team B scores 5 of his teams 12 points and has 3 of his team's 9 rebounds while committing 2 turnovers and 2 fouls.

Summary - If you just looked at the individual stats you would see Player 1 with 5 pts, 3 rbs, versus Player 2 with 3 pts, 2 rbs. On a 40 minute basis this looks like 25 points 15 rebounds versus 15 points and 10 rebounds. Over a season it could be easy to lose sight of the bigger picture:  Player 1's contribution leads to losses and Player 2's contribution leads to wins. A person's Win Share stats are highly pertinent when you consider how valuable a player's performance is.

As for the Kings Here are the top 5 based on Win Share for last season:

Beno Udrih - 5.5

Tyreke Evans - 5.4

Jason Thompson - 4.0

Omri Casspi  - 2.5

Carl Landry - 2.3

Here are the top 5 based on W/48 for last season (league avg. is .100):

Beno Udrih - .107

Carl Landry - 1.05

Tyreke Evans - .097

Jason Thompson - .081

Francisco Garcia - .081

Personal Efficiency Rating

The Personal Efficiency Rating or PER is another effective way to determine how clutch a player is to his team. The PER sums up all a player's positive accomplishments, subtracts the negative accomplishments, and returns a per-minute rating of a player's performance. To calculate the unadjusted PER (uPER) use the following calculations:

uPER = (1 / Minutes Played) *
[ 3P
+ (2/3) * AST
+ (2 - factor * (team_AST / team_FG)) * FG
+ (FT *0.5 * (1 + (1 - (team_AST / team_FG)) + (2/3) * (team_AST / team_FG)))
- VOP * TOV
- VOP * DRB% * (FGA - FG)
- VOP * 0.44 * (0.44 + (0.56 * DRB%)) * (FTA - FT)
+ VOP * (1 - DRB%) * (TRB - ORB)
+ VOP * DRB% * ORB
+ VOP * STL
+ VOP * DRB% * BLK
- PF * ((lg_FT / lg_PF) - 0.44 * (lg_FTA / lg_PF) * VOP) ]

The following is how you translate/calculate a few of the combined comprehensive stats in the above:

factor = (2 / 3) - (0.5 * (lg_AST / lg_FG)) / (2 * (lg_FG / lg_FT))
VOP = lg_PTS / (lg_FGA - lg_ORB + lg_TOV + 0.44 * lg_FTA)
DRB% = (lg_TRB - lg_ORB) / lg_TRB

I won't bother to explain how to calculate it fully other than recommend you read John Hollinger's notes as it is quite complicated and only fellow Mensae would revel in the explanation on how someone's PER is derived. Furthermore, if you try to evaluate player's PERs before offensive rebounds, steals, 3 pointers, etc. were tracked, you would have to introduce additional math into the calculations and if you could you probably aren't reading this blog, probably don't even watch sports and consider Disquisitiones Arithmeticae to be bathroom reading. Piece of cyclotomic polynomials you say, well  CBS just called to ask if you would like to appear on the "Big Bang Theory" this Fall.

All you really need to know about PER is that the league average is 15 and the best all time career PER average belongs to Michael Jordan at 27.91 with the best active player being Labron James at 26.86. Oscar Robinson was the best King of all time at #19 with 23.17 followed by Chris Webber at 45th with 20.94. Tyreke led the Kings last year with 18.2. On the current Kings Roster, only Carl Landry (16) and Beno Udrih (15.7) are above the league average.

Summary - The more good things a player does while on the floor versus bad things, then the more valuable the player is--especially at the end of the game when every possession counts.

Clutch Stats

Clutch Stats are stats that occur during the 4th quarter or overtime of a game, with less than 5 minutes left and neither team ahead by more than 5 points. 82 Games does a very detailed job of analyzing player performance across a myriad statistical categories overall versus during "Clutch Time". Below are a handful I think are valuable to use. I will then use Omri Casspi's stats during Clutch Time over last season to give you an idea how the differed from his overall numbers.

eFG% - Averaging both 2 point and 3 point shots attempted versus made to derive the effective Field Goal Percentage during Clutch Time.

Casspi Overall - 50.3%

Casspi Clutch - 52.1%

FT% - Percentage of Free Throws made versus attempted during Clutch Time.

Casspi Overall - 67.2%

Casspi Clutch - 50%

Rebounding Player Rating (RPR) - The total of offensive rebounds versus opportunities + the total defensive rebounds versus opportunities during Clutch Time.

Casspi Overall - 18.3%

Casspi Clutch - 17.5%

Hands Rating (HR) - How well you avoid offensive fouls, ball handling turnovers or bad passes during Clutch Time.

Casspi Overall - 9.9

Casspi Clutch - 5.0

Summary - The more frequently your shots fall and the more time you get a rebound on both ends of the floor and the more often you don't turn the ball over the better you are when the game is on the line. In Casspi's case he overall is a little better shooting the ball, worse at the stripe and makes more mistakes with the rock when the game is on the line.

Revisiting the Debate

In my previous post I used the term clutch to describe Cisco in comparison to the other Small Forwards currently on our Roster. Now while I have reviewed stats at 82games.com before I never paid attention to the section they have called Clutch Stats. My opinion of Cisco's dependability came from his Win Share and W/48 ratings as well as personal recollection of him being on the floor more often than not in late game situations.

After reviewing the analysis here is a quick breakdown on our SFs when you consider their PER, Win Share & W/48 based on a career average:

Omri Casspi - PER = 13.0 WS = 2.5 W/48 = .063

Francisco Garcia PER = 13.1 (10.3 + 15.1) WS = 2.32 W/48 = .075 (.06 as a rookie)

Donte Greene PER = 9.6 (5.2 + 11.6) WS = .4 W/48 = .007

Antoine Wright PER = 7.9 (.7 + 9.0) WS avg = .64 W/48 = .027

Here is how they compare using a handful of Clutch Stats (eFG%, FT%, RPR, HR).

Omri Casspi - .521, .500, 17.5%, 5.0

Francisco Garcia - .389, 1.00, 13.0%, 2.0 ('09 = .586, .750, 12.5%, 20.6)

Donte Greene - .556, .000, 18.3%, 8.6

Antoine Wright - .565, .875, 12.0%, 13.9

When you look at all of these stats a few observations come forward. As a rookie, Omri's PER and WS numbers make him our logical starting SF. When you consider who is best when the game is on the line, it gets a little murky.

Offensively, Francisco's '09 numbers ('10 data sample is really too small with only 575 minutes) suggest he is your best scoring and ball handler in the group followed by surprisingly Antoine Wright (Go A&W Root Beer!).

Defensively, Donte and Omri are going to get you a rebound, althought surprisingly Francisco blocks the most shots in the group.

I don't think this debate will be easily settled, but I stand by original statement that Francisco Garcia is your most clutch player while giving the most minutes to Omri Casspi.

How Does Our Best Match Up

It should come as no surprise that Tyreke was our go to guy last season when the games were on the line. Here are his numbers:

Overall / Clutch

effective Field Goal Percentage - 47.3% / 42.6%

Made Free Throw Percentage - 74.8% / 69.0%

Passing Rating - 8.8 / 9.0

Rebound Rating - 14.7 / 18

Hands Rating - 18.0 - 20.6

Compare him to LeBron James last season:

Overall / Clutch

effective Field Goal Percentage - 54.5% / 55.0%

Made Free Throw Percentage - 76.7% / 80.5%

Passing Rating - 14.7 / 10.2

Rebound Rating - 19.5 / 32.2

Hands Rating - 30.3 - 23.7

 

LeBron's shooting and rebounding just jump to an unreal level when the game is on the line. To get a real sense of where our Kings match up go to the leader board for Clutch Time Stats at 82 Games.

It is interesting that while the Kings current roster is not well represented, Sam Dalembert is the Clutch Time Rebounding Leader at 22.

In conclusion, when you add up these different ways you start to see there are a few relevant ways to track a player on determine how Clutch they genuinely are.

I hope this helps and am curious if others out there have other types of data they too think are relevant to clutch performance.

(This is a FanPost from a member of the Sactown Royalty community. The views expressed come from the member, and not Sactown Royalty staff.)

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