The team grid system allows for quick and easy comparisons between teams. It is also the best foundational tool for managing a basketball team. For example, team grids allow managers, coaches, or anyone else to consider changes in players and in playing times that would improve the chances of winning playoff series and regular season games. At the same time, and just as importantly, team grids allow for quick flagging of coaching errors, some of which can be big enough to cost a team a playoff series or maybe a dozen regular season wins.
A depth chart shows you team policy regarding who starts and who are the backups and in what order for the five positions. The team grid is based on the depth chart style. However, players (other than players acquired during the season; see below) are placed into first squad, second squad, and third squad according to minutes played, not according to the latest ESPN or any other estimation of what the team policy is. Whoever has played the most minutes at a position is shown in the “1st Squad” whether or not that player starts at the position.
There is a notable exception to the rule for who goes in which squad. If a player has been acquired during the season and he is listed as the starter on the ESPN depth chart, he will be shown as first squad. Similarly, if a player acquired during the season is shown as the first backup to the starter in the depth chart he will be shown as second squad regardless of minutes. In other words, the depth chart prevails over minutes in the case of players acquired by trade during the season.
Just to the right of the “3rd Squad" you see two grey areas. From left to right the first one is for players who are probably or definitely out for much or for all of the series for some reason, usually due to injury.
The second grey shaded area is for players who could play but almost certainly will not play because they played fewer than 300 minutes during the regular season. The 300 minutes threshold is the minimum needed for a hidden defending adjustment and therefore is the minimum needed for a player to get a Real Player Rating. It also is being used here as the threshold for determining whether a player was essentially benched for the season. 300 minutes is less than four minutes a game, which is a very good dividing line for saying whether a player was benched for the season or not. You can get close to 300 minutes with just garbage time, so if you don't play at least 300 minutes, you are basically benched.
PLAYERS ACQUIRED BY TRADE
Players acquired by trade during the season who have played at least 300 minutes for their new team at the time when ratings for that team are done are treated on the grid as if they were on the team the entire season. The rating you see for them is for their new, current team minutes. The previous team rating is considered to be irrelevant for the grid.
Players acquired by trade during the season who have NOT played at least 300 minutes for their new team are either:
--Completely ignored and not shown on the grid if they did not play at least 300 minutes for the team they played for earlier in the season (regardless of whether they ever played at least 300 minutes in any year).
--They are shown as "more or less benched" if they did play at least 300 minutes for the previous team this season but not at least 300 minutes for the new, current team. The rating you see for them in the "more or less benched" column would have to be and is their rating on their previous team this season.
PLAYERS WHO HAVE NEVER PLAYED AT LEAST 300 MINUTES IN ANY SEASONThese players will not be listed even in the "benched for the season" column since no rating can be computed for them for any year and since, quite frankly, they are completely irrelevant for the playoff series at hand.
So players who are listed in the “more or less benched for the season” column are players who played at least 300 minutes during at least one NBA season. The Real Player Rating is shown for those players for the most recent year they played at least 300 minutes. What year that was is shown right next to their rating.
TEAM COMPARISONS USING THE GRID
First, you can compare specific players for any position. For example, you can see which team had the better starting point guard.
COMPARING TEAMS BY POSITION
By looking at the “Position Averages” column you can compare the two teams position by position. For each position, only the ratings of the first squad and of the second squad player are considered for the position average. And the rating of the first squad player at each position counts twice as much as the rating of the second squad player at each position. In other words, for each position the position average is two times the rating of the first squad player plus the rating of the second squad player divided by three.
If there is only one player who played 300 minutes or more at a position, there is a special rule that seeks to come up with a reasonable number for the position. 80% of that single player's rating is considered to be the position average. The 20% reduction is justified because of the fact that one or more players at other positions will have to fill out the position that has only one player (unless the single player plays almost the entire game which is pretty rare). Those other position players will obviously generally not be as valuable at the position as players dedicated to that position are.
Real Player Ratings vary by position because ultimately some positions are on average more important for winning the Quest than others. We don’t have exact numbers yet but here is a rough estimate of how League average ratings will vary by position:
Point Guard .780
Center .750
Power Forward .720
Small Forward .650
Shooting Guard .600
And again we don't have exact numbers yet, but we already know that, approximately, playoff team ratings, at least for the teams that win the first round, which would be eight teams, average out to about .800. The very best teams will have ratings averaging even higher than that. So ideally, and once again with the reminder that teams can and will vary radically from the position pattern shown here, here is a prototypical, "average" round two level NBA playoff team by position and by RPR:
Point Guard .900
Center .875
Power Forward .825
Small Forward .700
Shooting Guard .700
Again for emphasis: in reality many playoff teams will have at least one position where the average RPR of the two players who play it the most is greater than .900. And many playoff teams will have at least one position where the average of the top two players at the position is substantially less than .700.
But Championship teams will seldom have any position where the best two players average below .700 and they sometimes will feature two positions where the average of the top two players is greater than .900.
THE SUPERSTAR COMBO GUARD STRATEGY
Sometimes the shooting guard is so good that he is effectively also the point guard to some extent and he has a much higher rating than other shooting guards and perhaps a higher rating than other point guards. Kobe Bryant and the Los Angeles Lakers are a very good example. The overall 2-guard League average Real Player Rating is about .575 in the regular and .700 for the final eight teams. Kobe Bryant, of course, is well over 1.000.
One reason why having a superstar 2-guard who can take responsibility for keeping the ball moving and for being a playmaker is a very good strategy for winning the Quest is that you eliminate the common problem of leaving the 2-guard position as a weak spot in your overall lineup. In other words it is a very good way of optimizing your overall lineup, provided that the "real" point guard understands and can work with the strategy correctly.
If the "real" point guard does not understand the strategy and / or he disagrees with it, the drawback will be that to the extent you play that real point guard at the same time as your combo guard at the shooting guard position, you may have a player even less useful than a straight up mediocre 2-guard, in which case the strategy has backfired. There are several wrong ways and only a very few right ways to deploy the superstar combo guard strategy. There have been and will in the future be more Quest Reports on this very important subject.
By looking at the squad averages row you can see what the average rating of the players in that squad is for each team. By comparing the first squad with the second squad, you can see how much of a drop off there is between them. Since most of the players in the first squad are starters, this is approximately equivalent to comparing the starters and the bench. The bigger the drop off, the more minutes the starters should be playing.
SQUAD AND OVERALL TEAM AVERAGES
You can also of course compare the squad averages of the two teams. If you do, you will be essentially comparing the starters as a whole and the non-starters as a whole of the two teams, although keep in mind a team may have graduated one or two second squad players to starter for the playoffs.
Finally, notice that there is a “Team Average” at the lower left for each team. This is two times the first squad average plus the second squad average divided by three. In other words, this is a weighted average of the top two squads, with the first squad counted twice and the second squad counted once, which roughly corresponds to typical playing time patterns. Players in the third squad, the injured players, and the benched players are not counted in the team average.
You can put substantial stock but not a very large amount of stock in the team average number because there are still often going to be in the second squad a player with a very low rating from time to time. How much such players play in the playoffs is dependent on how strapped the team is at the position and on how dumb the coaching is.
LOW RATING PLAYERS IN THE PLAYOFFS
Often, especially on the best coached teams and on the primary contenders, a second squad player with a relatively low rating will be strategically benched during the playoffs. In general, players with ratings below .600 should play sparingly in the playoffs or not at all. Players with ratings below .500 should generally not play in the playoffs at all for any reason.
So there is a fairly large statistical error going on with the overall team average. But if you see that there is a big difference of about .050 or more in the team averages, that would tell you that the higher team is clearly more talented than the lower.
Friday, April 23, 2010
Friday, April 16, 2010
[Historical and Non-Current] User Guide for Real Team Ratings Reports Updated as of April 2010
IMPORTANT NOTICE: THIS IS A NON CURRENT, LEGACY USER GUIDE THAT WILL EVENTUALLY BE DELETED. AN UPDATED AND CURRENT GUIDE IS LOCATED HERE.
USER GUIDE FOR REAL TEAM RATINGS REPORTS
UPDATED AS OF APRIL 16 2010
INTRODUCTION
Of all the popular American sports Leagues, the NBA is the one where the better team is most likely to avoid being upset in the playoffs. Therefore, the RTR system can be used to gain knowledge of which team is most likely to win playoff series. It can also be used to determine whether how good various players played led to an upset or not, and to get a general idea of how much better or worse than expected teams played in playoff series.
The Real Team Ratings (RTR) is NOT simply a system that shows how well the teams are doing in the regular season. Instead, it is a rating system designed to reveal the capability of winning playoff games and series of each team.
The original and continuing foundation of RTR is defensive and offensive efficiency. The second most important factor and a big enough factor to be considered part of the foundation is the ability of teams to win games against the better and the best teams.
On top of these most important foundational factors, there are three other factors. First, the Real Team Ratings system was substantially improved in April 2010 with the advent of a new factor that reflects recent performance (in about the last two months). This gets at several previously ignored items that will help determine who will win and lose in the playoffs; see below for details.
The two other, smaller factors are the defense overweight adjustment and the pace over weight adjustment. History has shown that teams with great defenses and teams with slower paces have a little easier time winning Championships than the reverse. Every little bit of easier counts.
In general, factors that sometimes impact winning are NOT included; only factors that always or at least almost always impact winning are included.
RTR can be approximately used to predict who will win playoff series. However, there are of course factors not included in the RTR simply because their impact can not be known until the playoffs are played.
One factor not included can sometimes be huge and can easily flip a series: late regular season and during the playoffs injuries. The new recent games factor partially accounts for injuries that occurred in February and March and injuries occurring before then were already and remain largely covered by RTR. But injuries that occur starting around the 25th of March or later remain mostly unaccounted for by RTR. Among factors not included in RTR that always impact winning playoff games, recent injuries is by far the biggest one.
The ratings are calculated for all teams, even though 14 of the 30 NBA teams do not qualify for the playoffs. Even though they will not be playing any playoff games, the ratings for the lower teams nevertheless give an accurate measure of how well those teams would most likely do if they were in the playoffs. So for those lottery teams, RTR is an interesting hypothetical.
THE NEXT IMPROVEMENT
RTR will be tweaked further in the future as necessary, although we think the new April 2010 version is getting close to “almost perfect”. There is a proposal to include a small adjustment for coaching, based on the annual Real Coach Ratings, which themselves were substantially improved in 2009. Any new coaching adjustment will be small since coaching is already reflected in all of the other factors, but a small adjustment to reflect playoff experience and playoff performance of coaches appears to be warranted and is on the drawing board.
HISTORY OF REAL TEAM RATINGS
Quite honestly this system has had a more rocky development path than most other systems here at Quest for the Ring. There were several major changes to the system historically. For example, in 2009, the RTR rating system was much improved from prior versions. It was improved to make absolutely certain that you can predict the outcome of the playoffs in advance as accurately as possible. All crucial factors except for home court advantage, the injury situation, and coaching in the playoffs versus the regular season were now included and weighted very carefully. See below for how to adjust RTR scores for the first and second of these three items.
The biggest and most important improvement for 2009 and beyond was the introduction of points for wins over and points subtracted for losses to the top sixteen teams (which would be the playoff teams themselves.)
SUMMARY
The RTR system is a combination of net efficiency (net points per 100 possessions), the wins and losses versus playoff bound teams and especially versus the top ten teams, recent performance, the relatively small defensive overweight adjustment, and the very small pace adjustment. Each of these is now described in detail.
THE FIVE FACTORS USED FOR REAL TEAM RATINGS
1. NET EFFICIENCY
Offensive efficiency minus Defensive efficiency equals net efficiency. Offensive efficiency is points scored per 100 possessions. Defensive efficiency is points scored per 100 possessions. A weight of 3.0 is applied to net efficiency in the RTR formula which reflects how crucial this is.
2. WINS OVER AND LOSSES TO PLAYOFF TEAMS AND TO THE BEST TEN TEAMS
Each team's win-loss record is accessed for games it played against the top sixteen teams and, separately, for games it played against the top ten teams. These two records are added together, which has the effect of double weighting wins and losses versus top ten teams while leaving wins and losses versus the 11th through the 16th best teams single weighted.
Next the winning percentage of the wins and losses combined as just explained is calculated to three decimal points (for example, .558). Next the difference between each team’s winning percentage and a base of .360 is calculated and then this difference is multiplied by 90 to achieve the desired correlation with the net efficiency factor or in other words to achieve the desired weight within RTR. As an example, for the team with a winning percentage of .558, the factor added to RTR is (.558-.360) X 90 = 17.82.
The base of .360 is approximately the actual threshold between playoff and non-playoff teams.
The wins and losses versus top teams factor is correlated so that the sixteen playoff teams get from it on average 90% of the RTR points they get from the net efficiency factor.
Note that the use of the winning percentage as opposed to raw wins and losses almost completely corrects for different number of games played by teams against top teams.
This factor, wins over and losses to playoff teams, is the key 2009 improvement over the very early versions of RTR and helped to clearly establish Real Team Ratings as the most accurate playoff predictor possible. By counting in the overall formula actual wins and losses in games between the likely playoff teams, you have gone in a straight line directly to evidence for the question we are out to answer: how good are the teams really going to be in the playoffs, according to everything known now?
3. MOST RECENT DEVELOPMENTS AS SHOWN BY RECENT GAMES
The Real Team Ratings system was substantially improved in April 2010 with the arrival of a new factor that reflects recent performance (in about the last two months). This gets at several previously largely ignored items that help determine who will win and lose in the playoffs.
The key features and attributes of the most recent developments factor are:
-Functionally it over weights the most recent performance, from the most recent 25 games.
-It factors in momentum and morale going into the playoffs.
-It factors in coaching strategies and tactics that have finally produced good (or bad) results just in time for the playoffs. In other words, it substantially though roughly reflects the likelihood that coaching strategies and tactics will work or not in the playoffs
-It factors in the performance of new players acquired for the stretch run of the regular season and for the playoffs.
-It substantially but indirectly and inexactly reflects the current injury situation of teams. It especially factors in injuries that have occurred within the last couple of months or so and that may be carrying over into the playoffs. In other words, this factor is extremely useful for correcting RTR for injuries that occurred in February and March.
-The last five games of the Regular Season are ignored due to playoff coaches resting key players and due to other distortions. So the final Real Team Ratings for a season will cover from the 53rd game of a team through and including the 77th game of a team, while games 78 through 82 are ignored.
LIMITATIONS OF THE MOST RECENT DEVELOPMENTS FACTOR
Injuries that occurred in the last few days of March or in April are not much corrected for by this new factor. Moreover, injuries occurring during the playoffs themselves remain completely outside of the RTR system. Finally, when one or more players were injured and unavailable in February / March but are completely ready to go for the playoffs, the new factor may inadvertently distort the rating of the team downward.
For these and other reasons, the "Manual Injury Adjustment" is being maintained, although it has been completely overhauled. See below for details.
4. DEFENSIVE OVERWEIGHT ADJUSTMENT
The teams are sorted by defensive efficiency. Then, using a range from 5.8 to -5.8, points are assigned, in equal increments of 0.4, to each team in order of how it ranks in defensive efficiency. Specifically, the team with the best defensive efficiency (fewest points allowed per 100 possessions) is given 5.8 points, the second most defensively efficient team gets 5.4 points, the third most defensively efficient team gets 5.0 points, and so on, until the least defensively efficient team gets minus 5.8 points.
It is well known that, for the playoffs, how well a team can defend is generally somewhat more important than during the regular season. This factor answers the need to overweight defending in order to get accurate playoff projections. The adjustment gives an increase or a decrease in every team's rating in accordance with how each team ranks in defensive efficiency in the NBA.
The amount of the adjustment is carefully calibrated to be sufficient without being excessive. Since for one thing almost all teams ramp up their defense in the playoffs to one extent or another, you have to be careful here to avoid getting carried away and putting in adjustments that are too large.
5. PACE OVERWEIGHT ADJUSTMENT
The teams are sorted by pace. Pace for each team is the average number of possessions per game for that team's games. Then, using a range from 2.9 to -2.9, points are assigned, in equal increments of .2, to each team in order of how it ranks according to pace. Specifically, the team with the slowest pace (fewest possessions per game) is given 2.9 points, the 2nd slowest pace team gets 2.7 points, the third slowest pace team gets 2.5 points, and so on, until the fastest pace team gets minus 2.9 points.
The reason for the pace adjustment is that there is a relatively small but definite correlation between slower pace and winning playoff series. It is a little more difficult, on average, for fast pace teams to win playoff series than it is for slow pace teams to win them. Therefore, a small adjustment called the pace overweight adjustment is factored in to RTR.
Why exactly do slower paced teams have a slightly easier job winning playoff series? Consider an example. For example, consider the Denver Nuggets. They are one of the fastest paced teams in the NBA during the regular season. If you just look at the efficiency measures, the Nuggets might appear to be almost identical to another, much slower team. But these two teams would be very different when you look at efficiency and pace together. In theory, slower paced teams can more reliably reproduce their nice regular season net efficiency in the playoffs than can faster paced teams, mostly because the playoffs feature a higher defensive intensity and aggressiveness, which automatically slows down the pace.
Suppose that in the playoffs, the fast paced Nuggets and a slow paced team play. Each team had almost exactly the same offensive, defensive, and net efficiency numbers during the regular season. By playing extra hard on defense, the slow pace team can automatically slow down the game to some degree, which will disrupt the offensive (and possibly the defensive) efficiency of the Nuggets, the team that was fast pace in the regular season. In other words, there will be fewer possessions for the fast pace team in the playoff games than it typically had in the regular season. This in turn means that the fast pace team will be disrupted from what they did during the regular season to one extent or another.
This means that for the fast pace team, both the offensive and the defensive efficiency could change in the playoffs from what it was in the regular season, due to all of the changes forced on the fast pace team by the change of pace. Both the offensive and the defensive efficiency might change, and each change could be either for the better or for the worse, but by far the most likely changes would be that the offense would be substantially less efficient, while the defense would not be changed much. A much less efficient offense, but about the same defense, is exactly what we have seen from the Nuggets in their numerous playoff series losses in recent years.
In extreme cases, such as the fastest pace team being slowed down dramatically in the playoffs by an extremely slow team, the pace adjustment may be inadequate, so that there may still be some forecast error even after everything we have done.
The bottom line is that in all known cases, faster paced teams do not do as well in the playoffs as they do in the regular season, all other things equal. If a fast paced team wants to win in the playoffs, it would be wise to do some things better in the playoffs than they did those things in the regular season, in order to compensate for being forced to operate at a slower pace.
CALCULATION OF RTR: THE FORMULA
The easiest way to describe the final calculation of RTR is to give you the formula.
RTR =
Net Efficiency X 3.0
Plus
Winning percentage versus the top 16 and versus the top ten teams combined minus .360) X 90
Plus
The difference between wins and losses in the last 25 games (with the last five games of the regular season ignored)
Plus
The defense overweight adjustment (from +5.8 to -5.8 according to defensive efficiency rank)
Plus
The pace overweight adjustment (from +2.9 to -2.9 according to pace; slower pace is better than faster pace)
BASE STATISTICAL ERROR
Due to a small amount of unavoidable statistical error in RTR, there has to be about a five point difference between teams before you can start to have any confidence at all that the higher team will defeat the lower in a playoff series. The base statistical error for the final, end of season RTRs is about 3 points.
Statistical error is of course greater with less data, which means that the earlier that Real Team Ratings come out during a season, the higher the base statistical error. The first RTR Report is scheduled to come out in the last week of December. The base statistical error at that point is about eight points. Aside from statistical error, of course there is the much larger fact that a lot can change between the end of December and late April that has nothing to do with statistical error.
========== PLAYOFF FACTORS OUTSIDE OF REAL TEAM RATINGS ==========
The RTR system is the best playoff prediction scheme that can be done during the regular season. But there are still some factors that can not be included in RTR itself that will help determine playoff series. To get even better accuracy than base RTR, you have to know exactly what the injury situation is at the time playoff games are played. You need to know who has home court advantage. And you also would want to know how specific coaching tactics in particular playoff series will work out.
We now show you how when playoff time comes to adjust RTR for two out of three of those factors not included in RTR: home court advantage and the injury situation.
TWO MAJOR FACTORS DETERMINING WHO WINS PLAYOFF SERIES NOT BUILT IN TO THE BASIC RTR
1. HOME COURT ADVANTAGE
It is usually impossible to know who will have home court advantage in all of the round one playoff series until after the entire regular season is over.
Home court advantage is estimated to be worth between 5 and 7 points. You should generally add six points to the team that has home court advantage, although you can add as few as five or as many as seven if you know for sure that the home court advantage is much less or much more important than usual.
2. PLAYERS UNAVAILABLE (OR PLAYING POORLY) DUE TO INJURES
This is the most important of the two manual adjustments to RTR that are needed to arrive at an almost perfect prediction of who will win playoff series. In other words, this can easily be a much bigger adjustment than the six points for the home court advantage.
With the advent of the “most recent developments” factor (aka the “last 25 games factor”) manual injury adjustments are now easier, smaller, and more statistically valid than before. As a result, manual injury adjustments can now be highly recommended.
========== MANUAL INJURY ADJUSTMENTS ==========
Use the following instructions to adjust RTR of teams for injuries existing in the playoffs. The best manual injury adjustments can not be done until at least a day or two before a playoff series starts. In fact, due to the big, inherent uncertainty regarding injuries, manual injury adjustments often will need to be updated during or after game one of a series. This is because one or more of the players you thought would not play have played and / or one or more players you thought would play have not played due to injuries.
There are many complications involving the impact of injuries on who is going to win playoff games. I'll mention a few of them. One big complication is that the injury situation changes more rapidly than any of the other factors. Another complication is that early season injuries, even if the player never comes back, are not as bad for the playoffs as are late season injuries. Yet another complication is that there is very often conflicting information out there about just how bad different injuries are. For example, one source may say a player is probable (75-80% chance of playing) while another says the player is questionable (50% chance) while still another says doubtful (20-25% chance).
The overall magnitude of the injury adjustment to the new as of April 2010 RTR will range from zero to 30 points for most NBA playoff teams, but it is theoretically possible for there to be as much as a 60 point downward adjustment for a totally devastated team.
Among the most important variables regarding players who can’t play in the playoffs are:
-How good are the injured players? The Real Player Rating system is a perfect way to find out.
-To what extent are other players able to step up and replace the injured player or players? This depends mostly on how good the replacement(s) is or are and on how good the coaches are.
-For how long was the player injured? For players who never played at all, no adjustment in base RTR at all is necessary. The more the player played during the regular season, the GREATER the adjustment necessary.
Players who were injured the entire season are irrelevant, except of course they are relevant in the hypothetical sense of how the season could have been different. Players who were injured relatively early in the regular season, in November or December, are only slightly relevant, and the loss of them would be a much smaller number of reduced RTR points than when the loss is later. Players who were injured late in the season, from mid-February to mid-April, have the most relevancy to whether playoff series can be won or lost, and the manual injury downward adjustment to RTR for them is much higher.
MECHANICS OF THE INJURY ADJUSTMENT
FIRST FIND OUT WHO IS INJURED AND WHO MIGHT BE INJURED
The first thing to do of course is to find out which players are injured. For best results, use the Quest for the Ring injury page to get the latest information.
MANUAL INJURY ADJUSTMENT BASE
The base or starting point is the quality of the player, as shown by his Real Player Rating (including the hidden defending adjustment.) The base adjustment is the Real Player Rating of the player minus .500 times 20. For example, if the player injured has a RPR of .700, the base manual injury adjustment is (.700 - .500) X 20 = .200 X 20 = 4. As another example, if the player is a superstar and has a Real Player Rating of .950, the base manual injury adjustment is (.950 - .500) X 20 = .450 X 20 = 9.
.500 is subtracted from the ratings because ratings below .500 are virtually worthless in the playoffs.
We now for each injured player take the base and adjust it for variables regarding the injury. The variables are as follows. There are five variables numbered 1, 2, 3A, 3B, a;nd 3C.
1. STATUS (PROBABILITY PLAYER WILL PLAY) ADJUSTMENT
This adjustment is for manual injury adjustments to RTR when it is uncertain whether the player will be able to play in the game or not. Unfortunately uncertainty is the norm, not the exception.
Also unfortunately, sources of injury information sometimes conflict. When they do, you have to use your judgment as to which source is most correct, or else you can average out the designations.
The following tells you what to multiply the base manual injury adjustment base by based on the injury designation being reported.
Probable (There is about a 80% chance the player will play): multiply the base by .3
Game Time Decision (There is about a 60% chance the player will play): multiply the base by .55
Questionable (There is about a 40% chance the player will play): multiply the base by .75
Doubtful (There is about a 20% chance the player will play): multiply the base by .9
Out (There is about a 0% chance the player the player will play): multiply the base by 1.0
The status designations can be used not only as probabilities players will play but as rough but valid approximations of the severity of injuries, which in turn reflects the impact on the playoff series even if the player plays. Players who play slightly injured are seldom if ever going to be as good as they were with no injury at all. Therefore, the above adjustment factors not only reflect the probabilities but also the reality that even if the player plays, the team will be harmed by the injury situation.
2. WHEN IN THE SEASON THE PLAYER WAS LOST
Find out when the player became injured by checking game logs which are part of most statistical data sets for NBA players at most major sites including ESPN.
If the player has been unavailable on an on and off basis, assume the player was not available for the entire range of time, unless he was available at least 75% of the games within the range, in which case use the most recent date he became unavailable.
Use the following factors:
November .10
December .30
January .50
February .70
March .90
April 1.0
3. IMPORTANCE OF PLAYER TO THE TEAM
We actually have three separate adjustments which together show the importance of the player to the team.
3A MINUTES PER GAME OF THE INJURED PLAYER
At ESPN or another good site, find the minutes for the player for the current season. Be careful not to use minutes per game from any other season. Use the following adjustment factors:
30 mpg and more: 1.0
27 to 29.9: .9
24 to 26.9: .8
21 to 23.9: .7
18 to 20.9: .6
15 to 17.9: .5
12 to 14.9: .4
9 to 11.9: .3
6 to 8.9: .2
3 to 5.9: 1
Less than 3: 0
This factor indirectly gets at to what extent other players can make up for the player who is not available due to injury.
3B OVERALL DEPTH OF THE TEAM
Go to the latest Real Player Ratings Report for the team. Such Reports are posted at The Quest for the Ring for most or all playoff teams in late March or early April. Near the very beginning of such Reports you will see all the key players listed by category. Count the number of players according to category as follows, but DO NOT COUNT any players who are not available due to injuries or for any other reason.
Specifically, for purposes of this factor:
-Players listed as out should not be counted
-Players lested as doubtful should not be counted
-Players listed as questionable should be counted at 1/2
-Players listed as game time decision should be counted
-Players listed as probable should be counted
Note that in some cases you will be counting players as available even though you are calculating an injury hit on the team for them. This is paradoxical in the narrow sense but is part of a valid overall calculation.
Here are the team depth count factors:
Major Historical Superstars: Multiply the number of them by 10.
Historical Superstars: Multiply the number of them by 8.5.
Superstars: Multiply the number of them by 7.
Stars: Multiply the number of them by 6.
Very Good / Solid Starters: Multiply the number of them by 5
Major Role Players / Good Enough to start: Multiply the number of them by 4
Add it all up and then apply the following factors to the manual injury adjustment base:
50 and more: 0
49: .1
48: .2
47: .3
46 .4
45: .5
44: .6
43: .7
42: .8
41: .9
40 and less: 1.0
What this means is that if a team is so chock loaded that its remaining, available players add up to 50 or more points then it can completely make up for the injured player. If the sum of the remaining players is 40 or less, the team most likely can not at all make up for the injury.
In practice you will find that this test will often spit out the 1.0 factor since, unfortunately, few teams have enough good and great players to make an injury even partially irrelevant.
3C POSITION SHORTAGES
This factor is unique in that it can result in an increase rather than a decrease in the base manual injury adjustment factor. Find out if you don’t know already which position the injured player plays. Then check the depth chart for the team at ESPN or perhaps CBS Sports or Yahoo Sports. Find out how many available players there are at the injured players’ position.
The minimum reasonable number of players for each position for a completely healthy team is two and the maximum is four. A team impacted by one or more injuries at a position will have between zero and three players at the position following the injury. Use the following factors:
3 Players Still Available at the Position: .8
2 Players Still Available at the Position: 1.0
1 Player Still Available at the Position: 1.2
0 Players Still Available at the Position: 1.5
AN EXAMPLE: THE 2010 UTAH JAZZ
Ok, now lets consider an example to see how all of this manual injury adjustment stuff works.
EXAMPLE STEP ONE
Find out who is and who may be injured.
We have this year Carlos Boozer and Andrei Kirilenko, the second and third best players on the Utah Jazz, who are playing the Denver Nuggets in the first round, affected by injuries. Mehmet Okur may possibly be affected. According to two well regarded sources, here was the situation the day before the playoff series began (April 16, 2009):
-Carlos Boozer power forward, is questionable for Saturday's game against Denver due to a strained right oblique/rib cage.
-Andrei Kirilenko small forward, will miss at least the first round of the playoffs due to a strained left calf.
-Mehmet Okur, center, is probable with a strained left Achilles tendon.
In all of the calculations that follow: we round to the nearest tenth of a point; there is very little need to be more exact than that.
EXAMPLE STEP TWO
Compute the base manual injury adjustments:
Boozer: (1.005 - .500) X 20 = .505 X 20 = 10.1
Kirilenko: (.970 - .500) X 20 = .470 X 20 = 9.4
Okur: (.806 - .500) X 20 = .306 X 20 = 6.1
EXAMPLE STEP THREE
Adjust for the status (probability the player will play) factor:
Boozer is “questionable” so the factor to use is .75:
10.1 X .75 = 7.6
Kirilenko is “out” so the factor to use is 1.0:
9.4 X 1.0 = 9.4
Okur is “probable” so the factor to use is .3:
6.1 X .3 = 1.8
Note that although Okur is actually very likely to play, the Jazz will be at least slightly harmed by his minor injury whether or not he plays, so the small hit they will take on their Real Team Rating due to the minor injury for Okur is justified.
EXAMPLE STEP FOUR
Using the method described above, find out when in the season the player was lost (or mostly lost).
The Boozer situation just developed in April; the factor for April is 1.0, so the Boozer number remains 7.6.
The Kirilenko situation developed in March and the factor for March is .90. So for Kirilenko:
9.4 X .9 = 8.5
The Okur situation just developed in April and the factor for April is 1.0. So the Okur number remains 1.8.
Step Five: Minutes per game of the player
Boozer’s minutes per game are 34.5 and the factor to use is 1.0 so Boozer’s number remains 7.6.
Kirilenko’s minutes per game are 29 and the factor to use is .9:
8.5 X .9 = 7.7
Okur’s minutes per game are 29.4 and the factor to use is .9:
1.8 X .9 = 1.6
EXAMPLE STEP FIVE
Find the overall depth of the team not counting injured players.
Following the rules described above, Kirilenko is removed from the roster and we are left with:
-Deron Williams: major historical superstar, worth 10 points
-Carlos Boozer: historical superstar, worth 8.5 points
-Kyle Korver: star, worth 6 points
-Paul Milsap: star, worth 6 points
-Mehmet Okur: very good / solid starter, worth 5 points
-Ronnie Price: major role player / good enough to start, worth 4 points
Williams, Korver, Milsap, Okur, and Price are all available and they total 31 points. Boozer is questionable and he is a historical superstar. So he counts as 1/2 X 8.5 = 4.3. So the Jazz depth count is 35.3. So according to the table above, the factor to use (for all three of the Jazz players with injury situations) is 1.0, so the numbers of all three carry forward as what they were in the preceding step: Boozer: 7.6, Kirilenko: 7.7 and Okur: 1.6.
EXAMPLE STEP SIX
Check for position shortages:
Boozer is a power forward and without him the Jazz have just one power forward so the factor to use is 1.2:
7.6 X 1.2 = 9.1
Kirilenko is a small forward and without him the Jazz have just one small forward so the factor to use is 1.2:
7.7 X 1.2 = 9.2
Okur is a center and without him the Jazz have two centers so the factor to use is 1.0:
1.6 X 1.0 = 1.6
EXAMPLE STEP SEVEN
Add up the manual injury adjustments for the three Jazz players:
9.1 + 9.2 +1.6 = 19.9
EXAMPLE STEP EIGHT
Subtract the manual injury adjustment from the Jazz’ Real Team Rating to get the RTR adjusted for injuries:
39.6 – 19.9 = 19.7.
So the Jazz Real Team Rating once injuries are accounted for is 19.7. Then if you do the same thing for the Nuggets, you can compare the two and find out who is probably going to win this series and what the probability is. Then in turn you can evaluate how well the teams do in the series given the situation. You can for example find out how much of an upset it would be if the Jazz beat the Nuggets (assuming their injuries make them underdogs as is apparently the case).
COACHING IN THE PLAYOFFS VERSUS COACHING IN THE REGULAR SEASON
As explained previously, this factor is currently not included in base RTR and nor is there a manual adjustment procedure for it. But regular season coaching is obviously and completely included in base RTR.
Certain coaches deploy offensive and/or defensive strategies in the regular season that do not work as well in the playoffs as they do in the regular season. A team using this kind of strategy makes the playoffs but sooner or later gets bounced in the playoffs by a team using one or more strategies rewarded the most by basketball.
In other words, and more broadly, it is known to us here at Quest that how a team is coached, including what schemes it is using on offense and defense can have a different impact in the playoffs than it and they had in the regular season. This would not be picked up by the RTR.
The negative impact on RTR of coaching that works better in the regular season than in the playoffs is at this time believed to be between small and not so small, up to an absolute maximum of about 20 RTR points. But a 15-20 point hit would be plenty big enough to swing any close series. Coaches who coach well in the regular season but not in the playoffs will cost their teams playoff series they probably could have won, although this will not happen in every series. It will happen mostly in series where the RTR differential is between 5 and 20 points.
This type of coaching will certainly be in the long run ruinous to the objective of going as far as possible in the playoffs, simply because in every playoff run any playoff team will sooner of later face teams with similar base RTR ratings.
One of the primary objectives of the Quest for the Ring is to identify and explain offensive and defensive strategies that work better in the regular season than they do in the playoffs, and vice versa.
Other than lacking the regular versus playoffs coaching differential, coaching is completely reflected in the RTR base system.
Unfortunately, we don’t have any scheme, manual or otherwise, yet for coaching that is better or worse in the playoffs versus the regular season. However, we are working on it and there is a proposal to add a factor for this in RTR itself, and if that is approved no manual adjustment will be necessary.
========== INTERPRETING RTR DIFFERENCES BETWEEN TEAMS / PREDICTING PLAYOFF SERIES ==========
Scoping out playoff series is straightforward. You start with Real Team Ratings (RTR) as reported here at Quest and the first thing you then do is to add six points to the ratings of the teams with home court advantage. Then if you have the time and you want to be more accurate, you do the manual injury adjustments as needed. After you have adjusted the RTRs for home court and for injuries, you then compare them for the two teams playing and find out what the difference is. Finally you can use either the "quick prediction scale" and / or the descriptions in the "detailed guide" that you will see below the quick prediction scale.
QUICK PREDICTION SCALE FOR PLAYOFF SERIES
0 to 5.9 Complete toss-up: flip a coin
6 to 11.9 Roughly 60% chance the higher team will win
12 to 17.9 Roughly 70% chance the higher team will win
18 to 23.9 Roughly 80% chance the higher team will win
24 to 29.9 Roughly 89% chance the higher team will win
30 to 35.9 Roughly 95% chance the higher team will win
36 to 41.9 Roughly 98% chance the higher team will win
42 to 47.9 Roughly 99% chance the higher team will win
48 or more Roughly 100% chance the higher team will win
DETAILED GUIDE TO INTERPRETATION OF DIFFERENCES BETWEEN IN REAL TEAM RATINGS
In the detailed interpretaton guide that follows, the word "roughly" is repeatedly used in front of the probability numbers, as reminders of the small amount of unavoidable statistical error and to emphasize that unknown factors, including injuries, especially injuries for which no manual adjustment has been made, will in some cases result in substantially different actual probabilities.
Whether or not you are doing manual injury adjustments, do not forget to add six points to the RTRs of the teams that have home court advantage. Injury adjustments are highly recommended unless neither of the teams have significant injuries.
The probability percentages in both the quick chart above and in the descriptions below are based on historical results in the NBA.
DIFFERENCE IN RATINGS IS BETWEEN 0 AND 5.9
The series is a complete toss-up when statistical error is considered. There is a strong possibility of a 7 game series. The higher team has a 50% to 55% chance of winning, depending on what exactly the difference is. These probabilities are too low for anyone to have any confidence in using RTR to say who will win. All series of this type are decided quite simply by who plays better, by who coaches better, or both.
DIFFERENCE IN RATINGS IS BETWEEN 6.0 AND 11.9
The series can easily go either way, although the higher team has a small edge, and has between a 55% to 65% chance of winning, depending on where in the range the difference is. There is a very substantial chance of a 7-game series. If the lower team wins, it is a small upset. Either slight differences in the quality of coaching, certain players playing a little better or a little worse than they did in the regular season, or both, could be responsible for an upset at this level.
DIFFERENCE IN RATINGS IS BETWEEN 12.0 AND 17.9
The series can go either way and this type of difference gives a significant chance for a 7-game series. But the higher team has a clear edge. The higher team has between a 65% and a 75% probability of winning, depending on where in the range the difference is. If the lower team wins, it is a moderate upset. Either slight differences in the quality of coaching, certain players playing a little better or a little worse than they did in the regular season, or both, could be responsible for an upset at this level.
DIFFERENCE IN RATINGS IS BETWEEN 18.0 AND 23.9
The higher team has roughly between a 75% to 85% probability of winning, depending on where in the range the difference is. There is a chance, but only a small one, for a 7-game series. If the lower team wins, it is a fairly big upset. Either coaches, certain players, or both could be responsible for an upset at this level.
DIFFERENCE IN RATINGS IS BETWEEN 24.0 AND 29.9
The higher team has roughly between an 85% to a 93% probability of winning, depending on where in the range the difference is. In this kind of series, often the only way the lower team can win the series is by extending the series out to 7 games and then somehow winning the 7th game, thus taking the series 4 games to 3. However, it is not uncommon, assuming there is an upset in this type of series, for the lower team to so severly disrupt the favored team that the lower team upsets the higher, favored team 4 games to 2. Whichever way it does it, if the lower team does win coming in down by this amount, it should be considered a major upset. In many such cases, the coaching would have to be very wrong and/or negligent.
DIFFERENCE IN RATINGS IS BETWEEN 30.0 AND 35.9
The higher team has roughly between a 93% and a 97% probability of winning. depending on where in the range the difference is. In this kind of series, often the only way the lower team can win the series is by taking the series 7 games and winning the 7th game, thus taking the series 4 games to 3. However, there have been a tiny number of series where a team with this amount of a RTR deficit has won the series by so severly disrupting the favored team that it is able to win the series 4 games to 2. In the vast majority of such cases, the coaching for the higher team was severely wrong and/or negligent. Whether accomplished in 6 games or 7, the lower team winning despite being this far behind in RTR is extremely rare, and would be considered a very major and very surprising upset.
DIFFERENCE IN RATINGS IS BETWEEN 36.0 AND 41.9
The higher team has roughly between a 97% and a 99% probability of winning, depending on where in the range the difference is. Obviously, an upset would be extremely rare, shocking, and historical. It would in most cases be caused substantially by incompetent and/or severely negligent coaching or by one or more major injuries. With this amount of difference, any upset would almost certainly have to be with the series going all seven games.
DIFFERENCE IN RATINGS IS 42.0 AND 47.9
The higher team has a roughly 99% probability of winning the series. Obviously, an upset would be extremely rare, shocking, and historical. It would in most cases be caused substantially by incompetent and/or severely negligent coaching or by one or more major injuries. With this amount of difference, any upset would almost certainly have to be with the series going all seven games.
DEFFERENCE IN RATINGS IS 48.0 OR MORE
It is close to a 100% certainty that the higher team will win the series. Obviously, an upset would be extremely rare, shocking, and historical. It would in the vast majority of cases be caused substantially by incompetent and/or severely negligent coaching. With this amount of difference, any upset would almost certainly have to be with the series going all seven games.
USER GUIDE FOR REAL TEAM RATINGS REPORTS
UPDATED AS OF APRIL 16 2010
INTRODUCTION
Of all the popular American sports Leagues, the NBA is the one where the better team is most likely to avoid being upset in the playoffs. Therefore, the RTR system can be used to gain knowledge of which team is most likely to win playoff series. It can also be used to determine whether how good various players played led to an upset or not, and to get a general idea of how much better or worse than expected teams played in playoff series.
The Real Team Ratings (RTR) is NOT simply a system that shows how well the teams are doing in the regular season. Instead, it is a rating system designed to reveal the capability of winning playoff games and series of each team.
The original and continuing foundation of RTR is defensive and offensive efficiency. The second most important factor and a big enough factor to be considered part of the foundation is the ability of teams to win games against the better and the best teams.
On top of these most important foundational factors, there are three other factors. First, the Real Team Ratings system was substantially improved in April 2010 with the advent of a new factor that reflects recent performance (in about the last two months). This gets at several previously ignored items that will help determine who will win and lose in the playoffs; see below for details.
The two other, smaller factors are the defense overweight adjustment and the pace over weight adjustment. History has shown that teams with great defenses and teams with slower paces have a little easier time winning Championships than the reverse. Every little bit of easier counts.
In general, factors that sometimes impact winning are NOT included; only factors that always or at least almost always impact winning are included.
RTR can be approximately used to predict who will win playoff series. However, there are of course factors not included in the RTR simply because their impact can not be known until the playoffs are played.
One factor not included can sometimes be huge and can easily flip a series: late regular season and during the playoffs injuries. The new recent games factor partially accounts for injuries that occurred in February and March and injuries occurring before then were already and remain largely covered by RTR. But injuries that occur starting around the 25th of March or later remain mostly unaccounted for by RTR. Among factors not included in RTR that always impact winning playoff games, recent injuries is by far the biggest one.
The ratings are calculated for all teams, even though 14 of the 30 NBA teams do not qualify for the playoffs. Even though they will not be playing any playoff games, the ratings for the lower teams nevertheless give an accurate measure of how well those teams would most likely do if they were in the playoffs. So for those lottery teams, RTR is an interesting hypothetical.
THE NEXT IMPROVEMENT
RTR will be tweaked further in the future as necessary, although we think the new April 2010 version is getting close to “almost perfect”. There is a proposal to include a small adjustment for coaching, based on the annual Real Coach Ratings, which themselves were substantially improved in 2009. Any new coaching adjustment will be small since coaching is already reflected in all of the other factors, but a small adjustment to reflect playoff experience and playoff performance of coaches appears to be warranted and is on the drawing board.
HISTORY OF REAL TEAM RATINGS
Quite honestly this system has had a more rocky development path than most other systems here at Quest for the Ring. There were several major changes to the system historically. For example, in 2009, the RTR rating system was much improved from prior versions. It was improved to make absolutely certain that you can predict the outcome of the playoffs in advance as accurately as possible. All crucial factors except for home court advantage, the injury situation, and coaching in the playoffs versus the regular season were now included and weighted very carefully. See below for how to adjust RTR scores for the first and second of these three items.
The biggest and most important improvement for 2009 and beyond was the introduction of points for wins over and points subtracted for losses to the top sixteen teams (which would be the playoff teams themselves.)
SUMMARY
The RTR system is a combination of net efficiency (net points per 100 possessions), the wins and losses versus playoff bound teams and especially versus the top ten teams, recent performance, the relatively small defensive overweight adjustment, and the very small pace adjustment. Each of these is now described in detail.
THE FIVE FACTORS USED FOR REAL TEAM RATINGS
1. NET EFFICIENCY
Offensive efficiency minus Defensive efficiency equals net efficiency. Offensive efficiency is points scored per 100 possessions. Defensive efficiency is points scored per 100 possessions. A weight of 3.0 is applied to net efficiency in the RTR formula which reflects how crucial this is.
2. WINS OVER AND LOSSES TO PLAYOFF TEAMS AND TO THE BEST TEN TEAMS
Each team's win-loss record is accessed for games it played against the top sixteen teams and, separately, for games it played against the top ten teams. These two records are added together, which has the effect of double weighting wins and losses versus top ten teams while leaving wins and losses versus the 11th through the 16th best teams single weighted.
Next the winning percentage of the wins and losses combined as just explained is calculated to three decimal points (for example, .558). Next the difference between each team’s winning percentage and a base of .360 is calculated and then this difference is multiplied by 90 to achieve the desired correlation with the net efficiency factor or in other words to achieve the desired weight within RTR. As an example, for the team with a winning percentage of .558, the factor added to RTR is (.558-.360) X 90 = 17.82.
The base of .360 is approximately the actual threshold between playoff and non-playoff teams.
The wins and losses versus top teams factor is correlated so that the sixteen playoff teams get from it on average 90% of the RTR points they get from the net efficiency factor.
Note that the use of the winning percentage as opposed to raw wins and losses almost completely corrects for different number of games played by teams against top teams.
This factor, wins over and losses to playoff teams, is the key 2009 improvement over the very early versions of RTR and helped to clearly establish Real Team Ratings as the most accurate playoff predictor possible. By counting in the overall formula actual wins and losses in games between the likely playoff teams, you have gone in a straight line directly to evidence for the question we are out to answer: how good are the teams really going to be in the playoffs, according to everything known now?
3. MOST RECENT DEVELOPMENTS AS SHOWN BY RECENT GAMES
The Real Team Ratings system was substantially improved in April 2010 with the arrival of a new factor that reflects recent performance (in about the last two months). This gets at several previously largely ignored items that help determine who will win and lose in the playoffs.
The key features and attributes of the most recent developments factor are:
-Functionally it over weights the most recent performance, from the most recent 25 games.
-It factors in momentum and morale going into the playoffs.
-It factors in coaching strategies and tactics that have finally produced good (or bad) results just in time for the playoffs. In other words, it substantially though roughly reflects the likelihood that coaching strategies and tactics will work or not in the playoffs
-It factors in the performance of new players acquired for the stretch run of the regular season and for the playoffs.
-It substantially but indirectly and inexactly reflects the current injury situation of teams. It especially factors in injuries that have occurred within the last couple of months or so and that may be carrying over into the playoffs. In other words, this factor is extremely useful for correcting RTR for injuries that occurred in February and March.
-The last five games of the Regular Season are ignored due to playoff coaches resting key players and due to other distortions. So the final Real Team Ratings for a season will cover from the 53rd game of a team through and including the 77th game of a team, while games 78 through 82 are ignored.
LIMITATIONS OF THE MOST RECENT DEVELOPMENTS FACTOR
Injuries that occurred in the last few days of March or in April are not much corrected for by this new factor. Moreover, injuries occurring during the playoffs themselves remain completely outside of the RTR system. Finally, when one or more players were injured and unavailable in February / March but are completely ready to go for the playoffs, the new factor may inadvertently distort the rating of the team downward.
For these and other reasons, the "Manual Injury Adjustment" is being maintained, although it has been completely overhauled. See below for details.
4. DEFENSIVE OVERWEIGHT ADJUSTMENT
The teams are sorted by defensive efficiency. Then, using a range from 5.8 to -5.8, points are assigned, in equal increments of 0.4, to each team in order of how it ranks in defensive efficiency. Specifically, the team with the best defensive efficiency (fewest points allowed per 100 possessions) is given 5.8 points, the second most defensively efficient team gets 5.4 points, the third most defensively efficient team gets 5.0 points, and so on, until the least defensively efficient team gets minus 5.8 points.
It is well known that, for the playoffs, how well a team can defend is generally somewhat more important than during the regular season. This factor answers the need to overweight defending in order to get accurate playoff projections. The adjustment gives an increase or a decrease in every team's rating in accordance with how each team ranks in defensive efficiency in the NBA.
The amount of the adjustment is carefully calibrated to be sufficient without being excessive. Since for one thing almost all teams ramp up their defense in the playoffs to one extent or another, you have to be careful here to avoid getting carried away and putting in adjustments that are too large.
5. PACE OVERWEIGHT ADJUSTMENT
The teams are sorted by pace. Pace for each team is the average number of possessions per game for that team's games. Then, using a range from 2.9 to -2.9, points are assigned, in equal increments of .2, to each team in order of how it ranks according to pace. Specifically, the team with the slowest pace (fewest possessions per game) is given 2.9 points, the 2nd slowest pace team gets 2.7 points, the third slowest pace team gets 2.5 points, and so on, until the fastest pace team gets minus 2.9 points.
The reason for the pace adjustment is that there is a relatively small but definite correlation between slower pace and winning playoff series. It is a little more difficult, on average, for fast pace teams to win playoff series than it is for slow pace teams to win them. Therefore, a small adjustment called the pace overweight adjustment is factored in to RTR.
Why exactly do slower paced teams have a slightly easier job winning playoff series? Consider an example. For example, consider the Denver Nuggets. They are one of the fastest paced teams in the NBA during the regular season. If you just look at the efficiency measures, the Nuggets might appear to be almost identical to another, much slower team. But these two teams would be very different when you look at efficiency and pace together. In theory, slower paced teams can more reliably reproduce their nice regular season net efficiency in the playoffs than can faster paced teams, mostly because the playoffs feature a higher defensive intensity and aggressiveness, which automatically slows down the pace.
Suppose that in the playoffs, the fast paced Nuggets and a slow paced team play. Each team had almost exactly the same offensive, defensive, and net efficiency numbers during the regular season. By playing extra hard on defense, the slow pace team can automatically slow down the game to some degree, which will disrupt the offensive (and possibly the defensive) efficiency of the Nuggets, the team that was fast pace in the regular season. In other words, there will be fewer possessions for the fast pace team in the playoff games than it typically had in the regular season. This in turn means that the fast pace team will be disrupted from what they did during the regular season to one extent or another.
This means that for the fast pace team, both the offensive and the defensive efficiency could change in the playoffs from what it was in the regular season, due to all of the changes forced on the fast pace team by the change of pace. Both the offensive and the defensive efficiency might change, and each change could be either for the better or for the worse, but by far the most likely changes would be that the offense would be substantially less efficient, while the defense would not be changed much. A much less efficient offense, but about the same defense, is exactly what we have seen from the Nuggets in their numerous playoff series losses in recent years.
In extreme cases, such as the fastest pace team being slowed down dramatically in the playoffs by an extremely slow team, the pace adjustment may be inadequate, so that there may still be some forecast error even after everything we have done.
The bottom line is that in all known cases, faster paced teams do not do as well in the playoffs as they do in the regular season, all other things equal. If a fast paced team wants to win in the playoffs, it would be wise to do some things better in the playoffs than they did those things in the regular season, in order to compensate for being forced to operate at a slower pace.
CALCULATION OF RTR: THE FORMULA
The easiest way to describe the final calculation of RTR is to give you the formula.
RTR =
Net Efficiency X 3.0
Plus
Winning percentage versus the top 16 and versus the top ten teams combined minus .360) X 90
Plus
The difference between wins and losses in the last 25 games (with the last five games of the regular season ignored)
Plus
The defense overweight adjustment (from +5.8 to -5.8 according to defensive efficiency rank)
Plus
The pace overweight adjustment (from +2.9 to -2.9 according to pace; slower pace is better than faster pace)
BASE STATISTICAL ERROR
Due to a small amount of unavoidable statistical error in RTR, there has to be about a five point difference between teams before you can start to have any confidence at all that the higher team will defeat the lower in a playoff series. The base statistical error for the final, end of season RTRs is about 3 points.
Statistical error is of course greater with less data, which means that the earlier that Real Team Ratings come out during a season, the higher the base statistical error. The first RTR Report is scheduled to come out in the last week of December. The base statistical error at that point is about eight points. Aside from statistical error, of course there is the much larger fact that a lot can change between the end of December and late April that has nothing to do with statistical error.
========== PLAYOFF FACTORS OUTSIDE OF REAL TEAM RATINGS ==========
The RTR system is the best playoff prediction scheme that can be done during the regular season. But there are still some factors that can not be included in RTR itself that will help determine playoff series. To get even better accuracy than base RTR, you have to know exactly what the injury situation is at the time playoff games are played. You need to know who has home court advantage. And you also would want to know how specific coaching tactics in particular playoff series will work out.
We now show you how when playoff time comes to adjust RTR for two out of three of those factors not included in RTR: home court advantage and the injury situation.
TWO MAJOR FACTORS DETERMINING WHO WINS PLAYOFF SERIES NOT BUILT IN TO THE BASIC RTR
1. HOME COURT ADVANTAGE
It is usually impossible to know who will have home court advantage in all of the round one playoff series until after the entire regular season is over.
Home court advantage is estimated to be worth between 5 and 7 points. You should generally add six points to the team that has home court advantage, although you can add as few as five or as many as seven if you know for sure that the home court advantage is much less or much more important than usual.
2. PLAYERS UNAVAILABLE (OR PLAYING POORLY) DUE TO INJURES
This is the most important of the two manual adjustments to RTR that are needed to arrive at an almost perfect prediction of who will win playoff series. In other words, this can easily be a much bigger adjustment than the six points for the home court advantage.
With the advent of the “most recent developments” factor (aka the “last 25 games factor”) manual injury adjustments are now easier, smaller, and more statistically valid than before. As a result, manual injury adjustments can now be highly recommended.
========== MANUAL INJURY ADJUSTMENTS ==========
Use the following instructions to adjust RTR of teams for injuries existing in the playoffs. The best manual injury adjustments can not be done until at least a day or two before a playoff series starts. In fact, due to the big, inherent uncertainty regarding injuries, manual injury adjustments often will need to be updated during or after game one of a series. This is because one or more of the players you thought would not play have played and / or one or more players you thought would play have not played due to injuries.
There are many complications involving the impact of injuries on who is going to win playoff games. I'll mention a few of them. One big complication is that the injury situation changes more rapidly than any of the other factors. Another complication is that early season injuries, even if the player never comes back, are not as bad for the playoffs as are late season injuries. Yet another complication is that there is very often conflicting information out there about just how bad different injuries are. For example, one source may say a player is probable (75-80% chance of playing) while another says the player is questionable (50% chance) while still another says doubtful (20-25% chance).
The overall magnitude of the injury adjustment to the new as of April 2010 RTR will range from zero to 30 points for most NBA playoff teams, but it is theoretically possible for there to be as much as a 60 point downward adjustment for a totally devastated team.
Among the most important variables regarding players who can’t play in the playoffs are:
-How good are the injured players? The Real Player Rating system is a perfect way to find out.
-To what extent are other players able to step up and replace the injured player or players? This depends mostly on how good the replacement(s) is or are and on how good the coaches are.
-For how long was the player injured? For players who never played at all, no adjustment in base RTR at all is necessary. The more the player played during the regular season, the GREATER the adjustment necessary.
Players who were injured the entire season are irrelevant, except of course they are relevant in the hypothetical sense of how the season could have been different. Players who were injured relatively early in the regular season, in November or December, are only slightly relevant, and the loss of them would be a much smaller number of reduced RTR points than when the loss is later. Players who were injured late in the season, from mid-February to mid-April, have the most relevancy to whether playoff series can be won or lost, and the manual injury downward adjustment to RTR for them is much higher.
MECHANICS OF THE INJURY ADJUSTMENT
FIRST FIND OUT WHO IS INJURED AND WHO MIGHT BE INJURED
The first thing to do of course is to find out which players are injured. For best results, use the Quest for the Ring injury page to get the latest information.
MANUAL INJURY ADJUSTMENT BASE
The base or starting point is the quality of the player, as shown by his Real Player Rating (including the hidden defending adjustment.) The base adjustment is the Real Player Rating of the player minus .500 times 20. For example, if the player injured has a RPR of .700, the base manual injury adjustment is (.700 - .500) X 20 = .200 X 20 = 4. As another example, if the player is a superstar and has a Real Player Rating of .950, the base manual injury adjustment is (.950 - .500) X 20 = .450 X 20 = 9.
.500 is subtracted from the ratings because ratings below .500 are virtually worthless in the playoffs.
We now for each injured player take the base and adjust it for variables regarding the injury. The variables are as follows. There are five variables numbered 1, 2, 3A, 3B, a;nd 3C.
1. STATUS (PROBABILITY PLAYER WILL PLAY) ADJUSTMENT
This adjustment is for manual injury adjustments to RTR when it is uncertain whether the player will be able to play in the game or not. Unfortunately uncertainty is the norm, not the exception.
Also unfortunately, sources of injury information sometimes conflict. When they do, you have to use your judgment as to which source is most correct, or else you can average out the designations.
The following tells you what to multiply the base manual injury adjustment base by based on the injury designation being reported.
Probable (There is about a 80% chance the player will play): multiply the base by .3
Game Time Decision (There is about a 60% chance the player will play): multiply the base by .55
Questionable (There is about a 40% chance the player will play): multiply the base by .75
Doubtful (There is about a 20% chance the player will play): multiply the base by .9
Out (There is about a 0% chance the player the player will play): multiply the base by 1.0
The status designations can be used not only as probabilities players will play but as rough but valid approximations of the severity of injuries, which in turn reflects the impact on the playoff series even if the player plays. Players who play slightly injured are seldom if ever going to be as good as they were with no injury at all. Therefore, the above adjustment factors not only reflect the probabilities but also the reality that even if the player plays, the team will be harmed by the injury situation.
2. WHEN IN THE SEASON THE PLAYER WAS LOST
Find out when the player became injured by checking game logs which are part of most statistical data sets for NBA players at most major sites including ESPN.
If the player has been unavailable on an on and off basis, assume the player was not available for the entire range of time, unless he was available at least 75% of the games within the range, in which case use the most recent date he became unavailable.
Use the following factors:
November .10
December .30
January .50
February .70
March .90
April 1.0
3. IMPORTANCE OF PLAYER TO THE TEAM
We actually have three separate adjustments which together show the importance of the player to the team.
3A MINUTES PER GAME OF THE INJURED PLAYER
At ESPN or another good site, find the minutes for the player for the current season. Be careful not to use minutes per game from any other season. Use the following adjustment factors:
30 mpg and more: 1.0
27 to 29.9: .9
24 to 26.9: .8
21 to 23.9: .7
18 to 20.9: .6
15 to 17.9: .5
12 to 14.9: .4
9 to 11.9: .3
6 to 8.9: .2
3 to 5.9: 1
Less than 3: 0
This factor indirectly gets at to what extent other players can make up for the player who is not available due to injury.
3B OVERALL DEPTH OF THE TEAM
Go to the latest Real Player Ratings Report for the team. Such Reports are posted at The Quest for the Ring for most or all playoff teams in late March or early April. Near the very beginning of such Reports you will see all the key players listed by category. Count the number of players according to category as follows, but DO NOT COUNT any players who are not available due to injuries or for any other reason.
Specifically, for purposes of this factor:
-Players listed as out should not be counted
-Players lested as doubtful should not be counted
-Players listed as questionable should be counted at 1/2
-Players listed as game time decision should be counted
-Players listed as probable should be counted
Note that in some cases you will be counting players as available even though you are calculating an injury hit on the team for them. This is paradoxical in the narrow sense but is part of a valid overall calculation.
Here are the team depth count factors:
Major Historical Superstars: Multiply the number of them by 10.
Historical Superstars: Multiply the number of them by 8.5.
Superstars: Multiply the number of them by 7.
Stars: Multiply the number of them by 6.
Very Good / Solid Starters: Multiply the number of them by 5
Major Role Players / Good Enough to start: Multiply the number of them by 4
Add it all up and then apply the following factors to the manual injury adjustment base:
50 and more: 0
49: .1
48: .2
47: .3
46 .4
45: .5
44: .6
43: .7
42: .8
41: .9
40 and less: 1.0
What this means is that if a team is so chock loaded that its remaining, available players add up to 50 or more points then it can completely make up for the injured player. If the sum of the remaining players is 40 or less, the team most likely can not at all make up for the injury.
In practice you will find that this test will often spit out the 1.0 factor since, unfortunately, few teams have enough good and great players to make an injury even partially irrelevant.
3C POSITION SHORTAGES
This factor is unique in that it can result in an increase rather than a decrease in the base manual injury adjustment factor. Find out if you don’t know already which position the injured player plays. Then check the depth chart for the team at ESPN or perhaps CBS Sports or Yahoo Sports. Find out how many available players there are at the injured players’ position.
The minimum reasonable number of players for each position for a completely healthy team is two and the maximum is four. A team impacted by one or more injuries at a position will have between zero and three players at the position following the injury. Use the following factors:
3 Players Still Available at the Position: .8
2 Players Still Available at the Position: 1.0
1 Player Still Available at the Position: 1.2
0 Players Still Available at the Position: 1.5
AN EXAMPLE: THE 2010 UTAH JAZZ
Ok, now lets consider an example to see how all of this manual injury adjustment stuff works.
EXAMPLE STEP ONE
Find out who is and who may be injured.
We have this year Carlos Boozer and Andrei Kirilenko, the second and third best players on the Utah Jazz, who are playing the Denver Nuggets in the first round, affected by injuries. Mehmet Okur may possibly be affected. According to two well regarded sources, here was the situation the day before the playoff series began (April 16, 2009):
-Carlos Boozer power forward, is questionable for Saturday's game against Denver due to a strained right oblique/rib cage.
-Andrei Kirilenko small forward, will miss at least the first round of the playoffs due to a strained left calf.
-Mehmet Okur, center, is probable with a strained left Achilles tendon.
In all of the calculations that follow: we round to the nearest tenth of a point; there is very little need to be more exact than that.
EXAMPLE STEP TWO
Compute the base manual injury adjustments:
Boozer: (1.005 - .500) X 20 = .505 X 20 = 10.1
Kirilenko: (.970 - .500) X 20 = .470 X 20 = 9.4
Okur: (.806 - .500) X 20 = .306 X 20 = 6.1
EXAMPLE STEP THREE
Adjust for the status (probability the player will play) factor:
Boozer is “questionable” so the factor to use is .75:
10.1 X .75 = 7.6
Kirilenko is “out” so the factor to use is 1.0:
9.4 X 1.0 = 9.4
Okur is “probable” so the factor to use is .3:
6.1 X .3 = 1.8
Note that although Okur is actually very likely to play, the Jazz will be at least slightly harmed by his minor injury whether or not he plays, so the small hit they will take on their Real Team Rating due to the minor injury for Okur is justified.
EXAMPLE STEP FOUR
Using the method described above, find out when in the season the player was lost (or mostly lost).
The Boozer situation just developed in April; the factor for April is 1.0, so the Boozer number remains 7.6.
The Kirilenko situation developed in March and the factor for March is .90. So for Kirilenko:
9.4 X .9 = 8.5
The Okur situation just developed in April and the factor for April is 1.0. So the Okur number remains 1.8.
Step Five: Minutes per game of the player
Boozer’s minutes per game are 34.5 and the factor to use is 1.0 so Boozer’s number remains 7.6.
Kirilenko’s minutes per game are 29 and the factor to use is .9:
8.5 X .9 = 7.7
Okur’s minutes per game are 29.4 and the factor to use is .9:
1.8 X .9 = 1.6
EXAMPLE STEP FIVE
Find the overall depth of the team not counting injured players.
Following the rules described above, Kirilenko is removed from the roster and we are left with:
-Deron Williams: major historical superstar, worth 10 points
-Carlos Boozer: historical superstar, worth 8.5 points
-Kyle Korver: star, worth 6 points
-Paul Milsap: star, worth 6 points
-Mehmet Okur: very good / solid starter, worth 5 points
-Ronnie Price: major role player / good enough to start, worth 4 points
Williams, Korver, Milsap, Okur, and Price are all available and they total 31 points. Boozer is questionable and he is a historical superstar. So he counts as 1/2 X 8.5 = 4.3. So the Jazz depth count is 35.3. So according to the table above, the factor to use (for all three of the Jazz players with injury situations) is 1.0, so the numbers of all three carry forward as what they were in the preceding step: Boozer: 7.6, Kirilenko: 7.7 and Okur: 1.6.
EXAMPLE STEP SIX
Check for position shortages:
Boozer is a power forward and without him the Jazz have just one power forward so the factor to use is 1.2:
7.6 X 1.2 = 9.1
Kirilenko is a small forward and without him the Jazz have just one small forward so the factor to use is 1.2:
7.7 X 1.2 = 9.2
Okur is a center and without him the Jazz have two centers so the factor to use is 1.0:
1.6 X 1.0 = 1.6
EXAMPLE STEP SEVEN
Add up the manual injury adjustments for the three Jazz players:
9.1 + 9.2 +1.6 = 19.9
EXAMPLE STEP EIGHT
Subtract the manual injury adjustment from the Jazz’ Real Team Rating to get the RTR adjusted for injuries:
39.6 – 19.9 = 19.7.
So the Jazz Real Team Rating once injuries are accounted for is 19.7. Then if you do the same thing for the Nuggets, you can compare the two and find out who is probably going to win this series and what the probability is. Then in turn you can evaluate how well the teams do in the series given the situation. You can for example find out how much of an upset it would be if the Jazz beat the Nuggets (assuming their injuries make them underdogs as is apparently the case).
COACHING IN THE PLAYOFFS VERSUS COACHING IN THE REGULAR SEASON
As explained previously, this factor is currently not included in base RTR and nor is there a manual adjustment procedure for it. But regular season coaching is obviously and completely included in base RTR.
Certain coaches deploy offensive and/or defensive strategies in the regular season that do not work as well in the playoffs as they do in the regular season. A team using this kind of strategy makes the playoffs but sooner or later gets bounced in the playoffs by a team using one or more strategies rewarded the most by basketball.
In other words, and more broadly, it is known to us here at Quest that how a team is coached, including what schemes it is using on offense and defense can have a different impact in the playoffs than it and they had in the regular season. This would not be picked up by the RTR.
The negative impact on RTR of coaching that works better in the regular season than in the playoffs is at this time believed to be between small and not so small, up to an absolute maximum of about 20 RTR points. But a 15-20 point hit would be plenty big enough to swing any close series. Coaches who coach well in the regular season but not in the playoffs will cost their teams playoff series they probably could have won, although this will not happen in every series. It will happen mostly in series where the RTR differential is between 5 and 20 points.
This type of coaching will certainly be in the long run ruinous to the objective of going as far as possible in the playoffs, simply because in every playoff run any playoff team will sooner of later face teams with similar base RTR ratings.
One of the primary objectives of the Quest for the Ring is to identify and explain offensive and defensive strategies that work better in the regular season than they do in the playoffs, and vice versa.
Other than lacking the regular versus playoffs coaching differential, coaching is completely reflected in the RTR base system.
Unfortunately, we don’t have any scheme, manual or otherwise, yet for coaching that is better or worse in the playoffs versus the regular season. However, we are working on it and there is a proposal to add a factor for this in RTR itself, and if that is approved no manual adjustment will be necessary.
========== INTERPRETING RTR DIFFERENCES BETWEEN TEAMS / PREDICTING PLAYOFF SERIES ==========
Scoping out playoff series is straightforward. You start with Real Team Ratings (RTR) as reported here at Quest and the first thing you then do is to add six points to the ratings of the teams with home court advantage. Then if you have the time and you want to be more accurate, you do the manual injury adjustments as needed. After you have adjusted the RTRs for home court and for injuries, you then compare them for the two teams playing and find out what the difference is. Finally you can use either the "quick prediction scale" and / or the descriptions in the "detailed guide" that you will see below the quick prediction scale.
QUICK PREDICTION SCALE FOR PLAYOFF SERIES
0 to 5.9 Complete toss-up: flip a coin
6 to 11.9 Roughly 60% chance the higher team will win
12 to 17.9 Roughly 70% chance the higher team will win
18 to 23.9 Roughly 80% chance the higher team will win
24 to 29.9 Roughly 89% chance the higher team will win
30 to 35.9 Roughly 95% chance the higher team will win
36 to 41.9 Roughly 98% chance the higher team will win
42 to 47.9 Roughly 99% chance the higher team will win
48 or more Roughly 100% chance the higher team will win
DETAILED GUIDE TO INTERPRETATION OF DIFFERENCES BETWEEN IN REAL TEAM RATINGS
In the detailed interpretaton guide that follows, the word "roughly" is repeatedly used in front of the probability numbers, as reminders of the small amount of unavoidable statistical error and to emphasize that unknown factors, including injuries, especially injuries for which no manual adjustment has been made, will in some cases result in substantially different actual probabilities.
Whether or not you are doing manual injury adjustments, do not forget to add six points to the RTRs of the teams that have home court advantage. Injury adjustments are highly recommended unless neither of the teams have significant injuries.
The probability percentages in both the quick chart above and in the descriptions below are based on historical results in the NBA.
DIFFERENCE IN RATINGS IS BETWEEN 0 AND 5.9
The series is a complete toss-up when statistical error is considered. There is a strong possibility of a 7 game series. The higher team has a 50% to 55% chance of winning, depending on what exactly the difference is. These probabilities are too low for anyone to have any confidence in using RTR to say who will win. All series of this type are decided quite simply by who plays better, by who coaches better, or both.
DIFFERENCE IN RATINGS IS BETWEEN 6.0 AND 11.9
The series can easily go either way, although the higher team has a small edge, and has between a 55% to 65% chance of winning, depending on where in the range the difference is. There is a very substantial chance of a 7-game series. If the lower team wins, it is a small upset. Either slight differences in the quality of coaching, certain players playing a little better or a little worse than they did in the regular season, or both, could be responsible for an upset at this level.
DIFFERENCE IN RATINGS IS BETWEEN 12.0 AND 17.9
The series can go either way and this type of difference gives a significant chance for a 7-game series. But the higher team has a clear edge. The higher team has between a 65% and a 75% probability of winning, depending on where in the range the difference is. If the lower team wins, it is a moderate upset. Either slight differences in the quality of coaching, certain players playing a little better or a little worse than they did in the regular season, or both, could be responsible for an upset at this level.
DIFFERENCE IN RATINGS IS BETWEEN 18.0 AND 23.9
The higher team has roughly between a 75% to 85% probability of winning, depending on where in the range the difference is. There is a chance, but only a small one, for a 7-game series. If the lower team wins, it is a fairly big upset. Either coaches, certain players, or both could be responsible for an upset at this level.
DIFFERENCE IN RATINGS IS BETWEEN 24.0 AND 29.9
The higher team has roughly between an 85% to a 93% probability of winning, depending on where in the range the difference is. In this kind of series, often the only way the lower team can win the series is by extending the series out to 7 games and then somehow winning the 7th game, thus taking the series 4 games to 3. However, it is not uncommon, assuming there is an upset in this type of series, for the lower team to so severly disrupt the favored team that the lower team upsets the higher, favored team 4 games to 2. Whichever way it does it, if the lower team does win coming in down by this amount, it should be considered a major upset. In many such cases, the coaching would have to be very wrong and/or negligent.
DIFFERENCE IN RATINGS IS BETWEEN 30.0 AND 35.9
The higher team has roughly between a 93% and a 97% probability of winning. depending on where in the range the difference is. In this kind of series, often the only way the lower team can win the series is by taking the series 7 games and winning the 7th game, thus taking the series 4 games to 3. However, there have been a tiny number of series where a team with this amount of a RTR deficit has won the series by so severly disrupting the favored team that it is able to win the series 4 games to 2. In the vast majority of such cases, the coaching for the higher team was severely wrong and/or negligent. Whether accomplished in 6 games or 7, the lower team winning despite being this far behind in RTR is extremely rare, and would be considered a very major and very surprising upset.
DIFFERENCE IN RATINGS IS BETWEEN 36.0 AND 41.9
The higher team has roughly between a 97% and a 99% probability of winning, depending on where in the range the difference is. Obviously, an upset would be extremely rare, shocking, and historical. It would in most cases be caused substantially by incompetent and/or severely negligent coaching or by one or more major injuries. With this amount of difference, any upset would almost certainly have to be with the series going all seven games.
DIFFERENCE IN RATINGS IS 42.0 AND 47.9
The higher team has a roughly 99% probability of winning the series. Obviously, an upset would be extremely rare, shocking, and historical. It would in most cases be caused substantially by incompetent and/or severely negligent coaching or by one or more major injuries. With this amount of difference, any upset would almost certainly have to be with the series going all seven games.
DEFFERENCE IN RATINGS IS 48.0 OR MORE
It is close to a 100% certainty that the higher team will win the series. Obviously, an upset would be extremely rare, shocking, and historical. It would in the vast majority of cases be caused substantially by incompetent and/or severely negligent coaching. With this amount of difference, any upset would almost certainly have to be with the series going all seven games.
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