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Category: Analysis Concepts

11/28/17

About Basketball Per-Minute Statistics and the Player Contribution Measure
and Basketball Actuality News Video in our Thursday's Basketball Statistics Referred Concepts

Basketball Statistics Referred Concepts:
About Basketball Per-Minute Statistics and the Player Contribution Measure

Basketball Statistics Analysis Referred Concepts
Per-minute Statistics: "... Per minute stats are a good manner to compare players within a team, seeing how a player off the bench might fare compared to the player in front of him in the rotation, but we must be careful about players who scarcely play - Jackie Butler may have averaged 96 points per 48 in the 5 minutes he played for the Knicks last year, but very doubtful he could have achieved it.

Also, we must be careful comparing players from one team to another. For example, the season Steve Nash averaged 16.1 assists per 48 while Tony Parker averaged just 8.6 - a large part of the reason for that is the pace and style Phoenix plays gave Nash more opportunities than Parker.

Per-48 Stats is not meant to be a projection of what a player would average if he played 48 minutes per game. Keep in mind that it is simply an expression of per-minute stats.

They are expressed as per-48 so that the resulting averages are easy to deal with: "23 points per 48 minutes" is easier to read and understand than ' 0,479 points per minute '; ..."

Players are not so happy 'playing their minutes' on the bench... but here Shack O'neill, Kobe Bryant and Derek Fisher plays their 'special' connection between them... inbounds and outbounds ! In this picture from Lipstick Alley presented by eBA Stats Basketball Statistics Analysis
Photograph: Lipstick Alley

Player Contribution Measure: "... Time played is a parameter not used with frequency in player's valuation although it is included in the box stats.

To relate player's valuation with his minutes played will give us his "efficiency", degree of cooperation into the team and with his teammates, interesting factor for the coach, the player and the game analyst.

The team's 'efficiency' per minute is obtained by dividing the valuation points, taken from the statistics, by the possible play minutes ( 40 or 48 ) and the mean of player's efficiency per minute by dividing newly by 200 or 240 ( total minutes played by 5 players on the court ).

The result compared with the player's individual ( valuation / minutes played ) and multiplied by his minutes in play will give us his efficiency or degree of cooperation over or under the team's mean.

From the moment that you can have only five players on the floor at one time, which invariably leads to some players seeing more action than others, how can you measure the contribution of players who play less and thus have fewer points, rebounds, and so on, than the starters?

The eBA Annual Basketball Statistics Clinic uses the per-minute stat to measure a player's value in terms of any other raw data stat for players with a low range of minutes played.
Say that one player scores eight points in a game, however, plays only eight minutes.

His per-minute scoring average is one point per minute, which extrapolated to a 40-minute game, would be 40 points per game.

But, actually, nobody in the NBA, WNBA or Euroleague, for that matter - averages 40 points per game. Suddenly, those eight points looks more impressive.

Although coaches find the per-minute stat helpful in evaluating players, but it has its limitations. Longer time periods belongs surely to the best players, and shorter time periods may yield misleading stats. ..."

"... Imagine a player that scores a three-pointer in his first minute of play and then sat out the rest of the game. Does anyone truly believe that he would've scored 144 points (3 x 48) in that game had he played the 48 minutes ? ..."

By Professor

Excerpts of a discussion at the eBA Annual Basketball Statistics Clinic



Read More at eBA CLINICS ONLINE, search "per minute statistics" in this blog and consult the Chapter "Time Played Analysis" at the eBA Basketball Statistics Analysis System.

This topic is resumed in the eBA Basketball Statistics Creative Analysis System and at the eBA Encyclopedia.

'Basketball Statistics Tracking Referred Concepts'
is a Series of Notes edited edited regularly !

To Read ALL the Articles in this Series, click here: Categories > Analysis Concepts




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11/14/17

About the Basketball Statistics and the Offensive Rebounding Percentage
and Basketball Actuality News Video in our Thursday's Basketball Statistics Referred Concepts

Basketball Statistics Referred Concepts:
About the Basketball Statistics and the Offensive Rebounding Percentage

Basketball Statistics Analysis Referred Concepts
In the circumstance that a team does miss a shot, it can prolong its possession and give itself an additional chance to score by rebounding its own misses.

Scoring this points are called "second chance points".

In the eBA Basketball Statistics Creative Analysis System we use the following formula for this statistic:

Oreb% =
Offensive Rebounds / (Offensive Rebounds + Opponent's Defensive Rebounds)

In this way, we only measure how many rebounds our team catches based on what's obtainable. We use this method instead of another, by example, "team offensive rebounds per game" which will give us "a good offensive rebound team" when a team that shoots 30% and probably catches a lot of offensive rebounds, whether they're a good rebounding team or not.

Applying Oreb%, we're looking at a ratio of how many rebounds our team grabbed compared to how many were accessible.

Rebound rate (RbR)=
(Total Rebs * (Team MP / 5)) / (MP * (Team Total Rebs + Opp Ttotal Rebs)) * 100

Rebound rate is an estimate of the percentage of missed shots a player rebounded while he was on the floor.



Offensive rebounding percentage is a very utilitarian statistic in determining the worth of players. But the eBA Basketball Statistics Creative Analysis System states that the number of total offensive rebounds can be useful, but it isn't as accurate as the OR% ~ offensive rebounding percentage.
To come upon a player or team's offensive rebounding percentage from the data of a box score, you must:

Specify the range of your calculations: it is possible to apply the offensive rebounding percentage to examine and note the similarities or differences of multiple teams or multiple players; nevertheless, you need to do these calculations individually. Look for and gather a series of players or a series of teams to assess the similarities and calculate each series one by one.

• Find at the box score the statistics necessary for supply the offensive rebounding percentage calculations: the number of offensive rebounds, the number of team offensive rebounds and the number of defensive rebounds by the opponent.

* Determine the sum together of the number of team offensive rebounds plus the number of defensive rebounds the opposing team grabbed. This arithmetic addition of these two numbers is known as the total number of rebounds available.

• Perform a division with the number of offensive rebounds, from the player o the team, depending on what you are calculating, by the total number of rebounds available. The quantity obtained by calculation is the OR% ~ offensive rebounding percentage for the team or player.

• Keep on these calculations as many times as necessary. Once you have done a set of these calculations, only now you have the right data to start comparing the players or teams and detect which players or teams are the best at recovering offensive rebounds.

Excerpt of my Exposition about "The Basketball Rebounds Analysis"
in the current Basketball Statistics eBA Clinics.





Read More in this blog and consult the Chapter eBA Basketball Team Defense Analysis.

This topic is resumed in the eBA Basketball Statistics Creative Analysis System and at the eBA Encyclopedia.

'Basketball Statistics Tracking Referred Concepts'
is a Series of Notes edited regularly !

To Read ALL the Articles in this Series, click here: Categories > Analysis Concepts




Your comments are Welcomed ! ... by means of eBA InterMail English or just here !

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10/11/17

Statistician's Digest: Basketball Registering Statistics Case Studies

Basketball Statistician's Digest:
eBA sketball Statistics Case Study: About Basketball Rebounds

Basketball Statistics eBA Case Study
Different Situations in a Basketball Rebound... Case Study

"... A missed shot comes off the rim and bounces along the floor. A1 is in position to pick up the ball, but B5 gains control. However, B5 fouls A1...

• case a) before either can touch the ball, or
• case b) as B5 is the first to touch the ball, or
• case c) after B5 is first to gain control of the ball, or
• case d) after A1 is first to touch the ball.

What is the statistical registration according to the eBA Basketball Statistics Analysis System in each one of the given situations, including the type of the registration ( forced or unforced TO; good or bad foul; close, long, disputed or undisputed rebound, etc.) ... ?"

Conclusion:
eBA System Statistics Fundamentals:
A player should be credited with a rebound only if the player earned that rebound before the ball was dead. What happened after the ball became dead and what would have happened if the ball had not become dead might be different.

The statistician should not attempt to decide what would have happened, but should decide only what did happen. However, if there is doubt about player control, the statistician may assume that there was control.

Sometimes there is doubt about whether a player has gained control of the ball before a certain act takes place. In such cases, the statistician should use the following guidelines.
• (a) If the statistician feels there was a possibility of player control, then the play shall be treated as though there was player control.
• (b) If the statistician feels there definitely was not a possibility of player control, then it shall be treated as though there was no player control.

Different Situations in a Basketball Rebound
Photograph from Red Box Pictures

eBA Basketball Statistical Tracking:

• In (a) the ball became dead when the foul was committed. Charge B5 with a BAD Personal Foul and credit Team A with a LONG UNDISPUTED Dead-ball Offensive Rebound.

• In (b) if B5 gained control before the foul, the official will have indicated that the foul was a player-control foul and B5 would be credited with an individual LONG DISPUTED Defensive Rebound and charged with a FORCED Turnover.



If there is no indication of player control, then credit Team A with a LONG DISPUTED Dead-ball Offensive Rebound.

• In (c) credit B5 with an individual LONG DISPUTED Def Rebound and charge him or her with an UNFORCED turnover

• In (d) if the statistician thinks that A1 possibly had control before the foul, credit A1 with an individual LONG DISPUTED Off Rebound.

If the statistician thinks that A1 definitely did not have control, credit Team A with a LONG UNDISPUTED Dead-ball Offensive Rebound.

Find another basketball statistics case studies from the eBA Basketball Statistics Analysis System at the eBA Encyclopedia > Case Studies





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09/25/17

Basketball Statistics Referred Concepts: Statistics Lies, Uses and Misuses of Statistical Graphs

Basketball Statistics Referred Concepts:
Reflections about Statistics Lies, Uses and Misuses of Statistical Graphics

Basketball Statistics Analysis Referred Concepts
At the last weekly meeting of the concluded eBA Basketball Statistics Tracking Annual Clinic we were discussing the topic of the statistics lies which was initiated by the exposition "Statistics & Statisticians" at eBA ONLINE.

Here is the opinion of Paul H. Kvam and Joel Sokol from their work "Teaching Statistics with Sports Examples":

Statistical lies are most frequently committed in graphical form, where the eyes can be more easily deceived by spurious trends suggested in a picture. A common abuse is manipulating scales on charts and graphs by truncating, censoring or transforming the axis values.

The next figure shows two different charts showing an increase in average attendance at NCAA Women's Soccer games between 1998 and 2003. The first (blue)chart  is the default Microsoft Excel chart; many statistical software packages, in fact, will restrict both axes to a small set of values that contains the data, which helps the reader focus on chart differences more clearly. However, it also removes the scale of difference from the picture, which has potential to mislead readers who pay little attention to the axis labels.

Average Attendance at NCAA

Average Attendance at NCAA

Two different charts showing average attendance
at NCAA Women's Soccer (season) matches

The reader's sense of proportion can be manipulated further with image-based charts, which are standard in sports publications. As an example, the figure below graphs the season wins for the New England Patriots using clip-art in place of vertical bars.

Season Wins for the New England Patriots

Regular season wins for the New England Patriots, 2002-2003

While the height of the football icons corresponds to the information the graph is meant to communicate, the size of the footballs does not; the Patriots improved 56% in wins between 2002 and 2003, but the increase in area of the football icons is over 140%.

By Profesor

This post was extracted from an exposition by Prof. Roberto Azar in the
Statistics Tracking Clinics in eBA ONLINE

Read More at eBA Encyclopedia, search "statistics lies" in this blog and consult the eBA Basketball Statistics Analysis System.

This topic is resumed in the eBA Basketball Statistics Analysis System and at the eBA Encyclopedia.

'Basketball Registering Stats Referred Concepts'
is a Series of Notes edited Regularly Every Month !

To Read ALL the Articles in this Series, click here: Categories > Analysis Concepts


Actuality News
Experience the FIBA EuroBasket 2017 | Tournament Wrap Up

Experience the FIBA EuroBasket 2017 | Tournament Wrap Up






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About the Basketball
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Open Letter About LinkedIn

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Game Pace & TO Ratios
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Basketball Game Analyst
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About Basketball Scouters & Statisticians

Modern Basketball Assist-Turnover
Ratio Levels

The Statistical Decision Limit
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Basketball Rebounds
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Statistics Never Tell
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Basketball Starters and Substitutes

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Libro de las jugadas
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Estudio Observacional
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Mike Krzyzewski
Gregg Marshall
Greg McDermott
Dave Paulsen
Bill Self
Pat Summitt
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# 1 ~

All Access Kentucky
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The National Championship
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with John Calipari


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Coaching
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Hot Hand:
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Dr. Chris Stankovich:
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Lo MEJOR del 2012 !
hasta Diciembre 31, 2012

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# 2 ~
La Pirámide del Éxito:
Construyendo bloques
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Básquetbol Escolar:
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• 2 ~ Acceso Total a las Prácticas del Seleccionado de los EE.UU. 7-pack DVD
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2-Pack DVD con el
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• 4 ~ Acceso Total a las Prácticas de Baloncesto
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• 5 ~ Acceso Total a las Prácticas de la Universidad Temple
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con Fran Dunphy






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