Assessing (real life) baseball player value

[cuervo72]

Originally Posted by Arles

Not really. Remember, singles are counted fully (from a total base standpoint) three times before being subtracted less than one time. Walks are also counted once in OBP and given another slight bump in the (singles/PA) factor in that if you have more walks, you will lose less here. This is by no means a perfect formula, it just heads towards the path I would like to see for a player's individual value as a hitter.

So you'd like a full team of Darrell Stowers'? Look at his 2014 campaign... .204 avg, .273 OBP, but he had 42 HR. His formula would be:

.450 * 2 + .273 - 58/672

I have that coming out to 1.087. So for a player with a .723 OPS, he'd be just a little less valuable than Manny Ramirez?

Ok, gotcha.

[SackAttack]

Originally Posted by dixieflatline

Let's look at the expected run matrix indeed. From www.baseballprospectus.com for 2004:

           OUTS
RUNNERS       0       1       2
    ---  0.5379  0.2866  0.1135
    1--  0.9259  0.5496  0.2460
    -2-  1.1596  0.7104  0.3359
    12-  1.4669  0.9577  0.4605
    --3  1.4535  0.9722  0.3623
    1-3  1.8540  1.2236  0.5219
    -23  2.1343  1.4717  0.6179
    123  2.2548  1.5946  0.8082

Looking at that matrix, though, you start to get a sense of stolen bases being overrated. A player who steals second after reaching first only increases his team's expected runs by around 0.23, but if he gets caught stealing, he reduces his team's expected runs by 0.64ish.

I guess it comes back down to the idea of if you play for one run, that's what you're going to get.

[QuikSand]

Originally Posted by Arles

Second, I'm trying to value players from a hitting standpoint. I can go up and take a few walks by not swinging. Most players can hit a single from time to time. But, fewer players can consistently hit extra base hits. Therefore, there should be premium put on those that have the ability to do so. Now, batting eye is important and it is a factor here, but if you are going to score runs - the quickest way (and most effective) to get them is extra base hits. So, when valueing players, I am looking for a way that will put a premium on guys that when they decide to swing, they get more extra base hits - while still taking into account walks and singles as they do matter.

I have read this a couple of times. *pause* Okay, now three times. I still don't see how this explanation is anything but reframing the original question/topic to better fit the answer/assertion you offered.


If we are having a discussion about ways to measure a player's effectiveness as a batter in baseball (and until that post, I thought we all were doing exactly that), then it stands to reason that we want to value the things that correlate to the team scoring runs. This really isn't all that hard to do -- and when you invest some time in it, you find that OPS does a very good job. It can be tweaked a bit to good effect (as some have offered, perhaps weighting OBP a little higher makes it a bit more accurate -- essentially the opposite of what you suggest) but on balance, it's a good indicator of a player's value to his team as a batter.



If you now want to start essentially a second debate about "it's hitting, not batting" or whatever else it is you think your "extra base hits are everything" concept supports -- that's okay, but understand that is all you're doing. It doesn't make your world full of Adam Dunns any more valuable to their actual baseball teams just because you're now succesfully correlating to something other than scoring runs, which is what really matters.

[dawgfan]

Originally Posted by Arles

Again, I do not doubt that given OBP takes into account players that reach via walk. And, for an entire team over the course of a season, those walks will end up amounting to a large number of runs which would not be registered by SLG. I am simply trying to determine a single player's "value". Given that goal, OBP (no extra base hits), SLG (no walks) and OPS (premium on singles) leave me a little lacking.

A lot of time and effort has already been expended in the pursuit of quantifying an individual player's contributions towards a team scoring runs. Complex versions of Runs Created per 27 outs give us the best results in this quantification.

[cuervo72]

yy, RC/27!

[dixieflatline]

Originally Posted by SackAttack

Looking at that matrix, though, you start to get a sense of stolen bases being overrated. A player who steals second after reaching first only increases his team's expected runs by around 0.23, but if he gets caught stealing, he reduces his team's expected runs by 0.64ish.

I guess it comes back down to the idea of if you play for one run, that's what you're going to get.

Yes which is exactly why you had better steal bases at a good clip(at least 2 out of 3) or your just hurting your team. Certainly in a close game in the later innings getting a key run is important but early in the game your not helping you team much at all by stealing second.

[SackAttack]

Originally Posted by dawgfan

A lot of time and effort has already been expended in the pursuit of quantifying an individual player's contributions towards a team scoring runs. Complex versions of Runs Created per 27 outs give us the best results in this quantification.

Are there any iterations of RC/27 that make allowances for park factors, though?

[dawgfan]

Originally Posted by Klinglerware

Let's remember that inferential statistics are not facts, they are figures derived from tools of analysis. These tools of analysis are only as good as the analyst--it is up to the analyst to derive meaning from the numbers he or she is seeing. For example, drowning deaths are correlated with ice cream sales--that doesn't mean that ice cream causes drowning or vice versa. What you need to do is to devise a credible causal mechanism to explain the statistical effects you are seeing. The statistics can guide you, but they cannot build theory on their own.

As for the OBP correlation--as you state, there is a strong correlation between team OBP and team runs scored. That in itself is pretty uncontroversial to me. I would be interested in seeing if anybody has run a correlation study on individual OBP to team runs scored. I would suspect that the correlation is much lower (plus I would like to see the theory on exactly why a player with higher OBPs would be more valuable than players with lower OBPs). Since we are looking at the value of individual players here, analyzing that statistic at the team level may not be appropriate to assessing value at the individual level.

True. However let's remember that baseball stats reflect a closed system - unlike most of the real world, we can quantify all offensive results in baseball. And by looking at things like the expected run matrix, you now have a better picture of the causation of why certain offensive events are worth a certain amount of value.

As to comparing individuals vs. the team, your logic of team OBP vs. individual OBP value differing doesn't make sense. Let's say you take 2 players - one rates higher in a measure like RC/27, the other rates higher in Arlie's formula. Clone those players so you have one team of player A (RC/27) and one team of player B (Arlie's formula) - the team full of player A's will score more runs.

Obviously there will be variety in reality in the offensive contributions of your lineup, but each player constitutes a vertical slice of the equation. What's good for the team is what's ideal for the individual.

Originally Posted by Klinglerware

I suspect that there really is no magic bullet statistic that would completely assess all facets of a player's value. Defense and base-running should also be considered (though I believe that SABR-metricians have done studies suggesting that these facets may be overvalued, nevertheless they probably do have some explanatory power), as well as games played (holding other factors constant, a player who plays 162 games is more valuable than a player who only manages to play 100)--none of these facets are captured by hitting statistics. Also, some may argue that return-on-investment calculations might be something to consider in an analysis. The bottom line is that multiple metrics probably should be used in determining a player's value.

Well, there have been attempts to collect all facets of the game and give a numerical value to players that assesses their contributions towards their team winning as pointed out above. The best known one currently is Win Shares devised recently by Bill James - it attempts to quantify all facets of a player's contributions, hitting and fielding and give them the appropriate weighting towards contributing to their team's success, as well as provide a balanced way of comparing pitchers with hitters. I haven't bought the book that details the formula, and since I'm not a math savant it would take me a while to digest it all if I did, so I can't give a personal opinion of the accuracy of Win Shares, but my impression is that it's viewed in a pretty favorable light in the sabermetric community.

If we're talking strictly offensive value, the best one seems to be the more complex versions of runs created per 27 outs - this carries an extremely high correlation with runs scored when you assess a team's stats.

Originally Posted by Klinglerware

That being said, I am quite sympathetic to the SABR-metric views on baseball, and many of the people running these studies are quite bright. My point is that statistics shouldn't be overvalued either--they are tools, not facts...

Very true, and just like any other science it is healthy to view things with skepticism and continue to test the theories with more studies to see if there isn't a better formula or theory. I think there is a fair amount of hubris that has grown around the sabermetric crowd that gets very stubborn in their conviction that they are right and that certain concepts are sacrosanct. This is a dangerous trap that the community needs to be aware of and combat - the temptation to think they've figured things out completely and that existing theories are infallible.

[dawgfan]

Originally Posted by SackAttack

Are there any iterations of RC/27 that make allowances for park factors, though?

I'm pretty sure there are - I think what you'd do is evaluate how a park effects all facets of offensive output compared to the league average and then run an individual's output through that filter before calculating RC/27.

[SackAttack]

Originally Posted by dawgfan

I'm pretty sure there are - I think what you'd do is evaluate how a park effects all facets of offensive output compared to the league average and then run an individual's output through that filter before calculating RC/27.

What I'm thinking is that the filter should probably only be applied to the player's home statistics, because he will play an inordinate number of games in his home park as compared to any other park, and thus, his RC/27 will be more greatly influenced by his home performance than by the fluctuations of road ballparks.

[dixieflatline]

Originally Posted by SackAttack

What I'm thinking is that the filter should probably only be applied to the player's home statistics, because he will play an inordinate number of games in his home park as compared to any other park, and thus, his RC/27 will be more greatly influenced by his home performance than by the fluctuations of road ballparks.

Park effects have been a real issue since baseball went to interleague play. Correctly adjust data for park effects when teams aren't playing a balanced schedule is not very easy.

[dawgfan]

Originally Posted by SackAttack

What I'm thinking is that the filter should probably only be applied to the player's home statistics, because he will play an inordinate number of games in his home park as compared to any other park, and thus, his RC/27 will be more greatly influenced by his home performance than by the fluctuations of road ballparks.

I think any sophisticated park effects correction will do this. You also have to make a small adjustment to the road stats though as well, since the road parks won't exactly equal the league average. As dixie points out, making corrections for park effects is rendered more difficult because of interleague play and unbalanced schedules. That said, any moderate effort in this area will go a long way towards correcting imbalances caused by the uniqueness of a player's home park.

[Klinglerware]

Originally Posted by dawgfan

As to comparing individuals vs. the team, your logic of team OBP vs. individual OBP value differing doesn't make sense. Let's say you take 2 players - one rates higher in a measure like RC/27, the other rates higher in Arlie's formula. Clone those players so you have one team of player A (RC/27) and one team of player B (Arlie's formula) - the team full of player A's will score more runs.

My point of contention is that you are using a statistical finding from one level of analysis (team) and attempting to use it to make an inference at a different level (individual). The high correlation score between team OBP and team Runs Scored make sense--I don't disagree with that finding. There certainly could be a correlation between individual OBP and team Runs Scored, but I would rather see an actual correlation study run to find out for sure--I have trouble with concluding anything on the micro individual level, based on analyses done at the macro team level...

[Huckleberry]

Thanks for the 2004 matrix. Been a while since I looked at one.

Here are my quick observations:

Stealing 3rd with 1 out makes the most sense of any steal. To check myself I created a matrix of the breakeven steal percentage for each situation (runner in bold is stealing and someone check my work):

		   OUTS
RUNNERS		0	1	2
	1--  0.7323  0.7306  0.7324
	-2-  0.7481  0.6951  0.9271
	12-  0.7032  0.7280  0.8947
	--3  0.9326  0.7320  0.3254
	1-3  0.7588  0.7764  0.8446
	1-3  0.9478  0.7499  0.4189
	-23  0.9825  0.8263  0.4625
	123  0.8595  0.7575  0.5534

[dawgfan]

Originally Posted by Klinglerware

There certainly could be a correlation between individual OBP and team Runs Scored, but I would rather see an actual correlation study run to find out for sure--I have trouble with concluding anything on the micro individual level, based on analyses done at the macro team level...

That's what the above scenario describes - using the runs created formula (which has an extremely high accuracy in projecting runs vs. actual runs) you can compare lineups of 2 different players and figure out which one would score more runs.

[dixieflatline]

Originally Posted by Huckleberry

Stealing 3rd with 1 out makes the most sense of any steal.

I agree with this completely. This is the best time to steal. It would be interesting to see a breakdown on when teams try to steal bases and how many of them are situations where it really isn't helping your team all that much.

I wonder how many MLB teams have done this study?

[Arles]

Originally Posted by cuervo72

So you'd like a full team of Darrell Stowers'? Look at his 2014 campaign... .204 avg, .273 OBP, but he had 42 HR. His formula would be:

.450 * 2 + .273 - 58/672

I have that coming out to 1.087. So for a player with a .723 OPS, he'd be just a little less valuable than Manny Ramirez?

Ok, gotcha.

Actually, Manny Ramirez would grade a 1.44 in my formula with an OPS of .963. When using OPS, Manny is 24.9% better than Stowers. Using my formula, he is 24.1% better than Stowers. Not much of a difference there between ratings.

I was simply trying to find some way to measure a player's ability as a hitter outside of OBP and OPS. The formula I chose may need serious modification (and it probably does), but I just do not think OPS or OBP reward extra bases enough. Maybe I am valueing extra base hits too highly - it's all possible. I also was not trying to pull a fast one Quicksand by using the terms "hitter and batter" seperately, I was trying to re-iterate that I was only talking about a player's ability as a hitter (not taking defense into account).

At the macro level, I agree that you would be hardpressed to beat OBP when evaluating a team or group of players. I was just hoping that there would be a better way to evaluate the value of an individual hitter than OBP or OPS. It appears that many here do not feel that this the case, but I will still follow in hopes something emerges. But, in the end, maybe some simple combo of OBP and OPS is the best way for evaluating players. It leaves me somewhat unfulfilled, but I guess it will have to do.

[Arles]

Originally Posted by dawgfan

As to comparing individuals vs. the team, your logic of team OBP vs. individual OBP value differing doesn't make sense. Let's say you take 2 players - one rates higher in a measure like RC/27, the other rates higher in Arlie's formula. Clone those players so you have one team of player A (RC/27) and one team of player B (Arlie's formula) - the team full of player A's will score more runs.

I certainly agree with this. But my point was what if you could NOT have a team full of player "A"s or player "B"s. Let's say you have 8 "average" major leaguers to go with this one player. Is it still a slam dunk to go with a high OBP or OPS guy over one with a high formula similar to what I posted?

Is it better to have a guy that does very well at reaching 1B when he has a group of players behind him not nearly as accomplished at reaching base? Or is it better to have a guy that is better at reaching 2nd, 3rd or scoring on his own (yet a little worse at reaching 1B) when he has a group of players behind him not nearly as good at reaching base? These are the questions I am not sure on.

But, I will certainly agree that if you could have 9 guys with a high OBP, you would maximize your chances for scoring runs. Still, the real world is often a far cry from that and teams will undoubtedly be playing average to below average guys at certain spots.

Obviously there will be variety in reality in the offensive contributions of your lineup, but each player constitutes a vertical slice of the equation. What's good for the team is what's ideal for the individual.

I'm just not sold on this. If you take it to the extreme and say you have 8 guys with an OBP of .300 - is it better to have the ninth guy have an OPB of .450 but a SLG of .390 or an OPB of .350 but a slugging of .490? Practically, it seems like the ability of the .490 SLG player to put himself on 2nd, 3rd or all the way home with no help from his teammates might prove more valuable than a guy that simply gets on base a little more often.

Well, there have been attempts to collect all facets of the game and give a numerical value to players that assesses their contributions towards their team winning as pointed out above. The best known one currently is Win Shares devised recently by Bill James - it attempts to quantify all facets of a player's contributions, hitting and fielding and give them the appropriate weighting towards contributing to their team's success, as well as provide a balanced way of comparing pitchers with hitters. I haven't bought the book that details the formula, and since I'm not a math savant it would take me a while to digest it all if I did, so I can't give a personal opinion of the accuracy of Win Shares, but my impression is that it's viewed in a pretty favorable light in the sabermetric community.

I have heard of this, but haven't really looked into it. I have to admit I do like the way it sounds though.

If we're talking strictly offensive value, the best one seems to be the more complex versions of runs created per 27 outs - this carries an extremely high correlation with runs scored when you assess a team's stats.

This is another stat I have heard of but am not all that familiar with. Is there a definition of it somewhere?

[Crapshoot]

Originally Posted by Arles

I'm just not sold on this. If you take it to the extreme and say you have 8 guys with an OBP of .300 - is it better to have the ninth guy have an OPB of .450 but a SLG of .390 or an OPB of .350 but a slugging of .490? Practically, it seems like the ability of the .490 SLG player to put himself on 2nd, 3rd or all the way home with no help from his teammates might prove more valuable than a guy that simply gets on base a little more often.

And in this statement lies the major flaw Arlie - a 450/390/840 guy is more valuable, by far, than a 350/490/840 guy - because he makes less outs. A single is worth about 1.4 times a walk - basic OPS treats it as twice as much, and that needs to be corrected for - thus the (x*OBP) + (SLG) measure that's generally accepted - with x ranging from 1.4 to 1.8

[NYFAN]

I've read a little bit of this topic, and am only partially knowledgable of these stats (I know how some of them are computed... not all)... anyway, I'm a volleyball coach, and we have a very interesting stat, it's called hitter efficiency, TV Analysts love to compare it to BA, but it's really not... anyway it goes like this...

Kills - a hitter hits, and terminates a rally, thus a point for his team
Error - the opposite of a kill (gives a point to the other team)
Zero - The hitter neither scored, nor committed an error
Attempt - Anything that was attempted to cause a kill, and as a result falls in one of the above categories

(Kills-Errors) / Attempts = Hitter Efficiency

While it doesn't attempt to give credit to other facets of the game that may effect their HE (like quality of passing, setting etc...) it gives you a remarkably accurate picture of what the hitter has done, especially in comparison to teammates at the same position (some positions have certain advantages that allow them to have higher %, much like in basketball where big men are taking easier shots than perimeter players).

Anyway, my point is that it seems like devising a strong system for baseball could easily be derived from this system...

(Singles * 1.5 + Doubles * 2 + Triples * 3 + HRs * 4 + BB + HBP - K's) / Total Attempts

Now a few clarifications... I'm multiplying singles by 1.5 to give it a distinct advantage over a walk because a single theoretically moves a teammate between 1 and 2 bases over. The rest of the multipliers are just to give a bases figure, and subtracting K's because at this point in time a K not only doesn't advance a runner, but it doesn't even force the defense to make a play on the ball, meaning you can't even get the benefit of an error. By not subtracting hit balls that were defended, you are basically saying that a batter made contact with the ball, and the defense was able to stop it, thus it's a void play, or a "zero" in volleyball. Dividing it by Attempts gives you your average.

Any thoughts?

[dawgfan]

Here's the Wikipedia page on runs created for those interested: http://en.wikipedia.org/wiki/Runs_created

[Arles]

Originally Posted by Crapshoot

And in this statement lies the major flaw Arlie - a 450/390/840 guy is more valuable, by far, than a 350/490/840 guy - because he makes less outs. A single is worth about 1.4 times a walk - basic OPS treats it as twice as much, and that needs to be corrected for - thus the (x*OBP) + (SLG) measure that's generally accepted - with x ranging from 1.4 to 1.8

This certainly makes sense, but is Player A worth more simply because he makes fewer outs? Again, if Player A ends up stranded on 1B three straight times with Player B grounding out twice and hitting a HR, wouldn't player B's output be more valuable?

What you are saying is certainly true when viewing an entire time or large collections of players. But, given the team around him, I could see a player with a higher SLG being more valuable than one with a high OBP. Maybe I am making this too hard, but I just don't see how the trend that OBP shows team runs fairly well translates perfectly to the micro level of individual performance.

[dawgfan]

Originally Posted by Arles

This certainly makes sense, but is Player A worth more simply because he makes fewer outs? Again, if Player A ends up stranded on 1B three straight times with Player B grounding out twice and hitting a HR, wouldn't player B's output be more valuable?

What you are saying is certainly true when viewing an entire time or large collections of players. But, given the team around him, I could see a player with a higher SLG being more valuable than one with a high OBP. Maybe I am making this too hard, but I just don't see how the trend that OBP shows team runs fairly well translates perfectly to the micro level of individual performance.

If you trust the runs created formula to accurately predict actual run output (and the more sophisticated versions get extremely close in this regard) you can experiment - take a lineup full of guys with a certain batting line and see what they produce as a collective in terms of runs. Then start unplugging guys and replacing them with players that have different batting lines. If you want to test your formula, take guys that get a set value with your formula, then start replacing them with guys with a similar overall value but higher slugging numbers and lower OBP numbers, then see what results you get.

[lynchjm24]

Nothing correlates better to runs scoring then

(OBP*1.8)*SLG

It's been shown many times over to be that equation or quite close to it.

[lynchjm24]

Originally Posted by Arles

This is another stat I have heard of but am not all that familiar with. Is there a definition of it somewhere?

RC/27 is realtively simple. It's just a rate stat of Runs Created per 27 - the offensive equivilent of ERA.

If you create 85 runs and use 540 outs to do it:

85/(540/27)=4.25 runs per 27 outs.

[dawgfan]

Originally Posted by lynchjm24

RC/27 is realtively simple. It's just a rate stat of Runs Created per 27 - the offensive equivilent of ERA.

If you create 85 runs and use 540 outs to do it:

85/(540/27)=4.25 runs per 27 outs.

I'm assuming he was looking for the formula for runs created, which ranges from the simple version (which is very accurate by itself) to the more complex versions that take into account base stealing, grounding into double plays, etc (even more accurate).

[SackAttack]

Originally Posted by Arles

This is another stat I have heard of but am not all that familiar with. Is there a definition of it somewhere?

Simple definition: OBP*TB, but as has been mentioned, there are far more complex iterations of the formula floating around out there as well.

[SackAttack]

Dola,

For runs created, that is; that was sort of in response to dawgfan's comment that Arles was looking for runs created.

[lynchjm24]

Originally Posted by dawgfan

Very true, and just like any other science it is healthy to view things with skepticism and continue to test the theories with more studies to see if there isn't a better formula or theory. I think there is a fair amount of hubris that has grown around the sabermetric crowd that gets very stubborn in their conviction that they are right and that certain concepts are sacrosanct. This is a dangerous trap that the community needs to be aware of and combat - the temptation to think they've figured things out completely and that existing theories are infallible.

True to a degree. There are certain areas that are much more science and less gray.

I have no doubt that as far as quantifing the offensive contribution of a player sabermetrics does a tremendous job. The offensive metrics tell 99% of the story. If an offensive event has already happened, it can be quantified.

There are other areas where there has been great work, but it's still much grayer. For example, defense. I'm a huge stat guy, but I'm still going to weigh the observations of a player on defense very heavily when making decisions about them.

I think that sometimes the people who follow this closely blur the lines between these sorts of things. Just because runs created or VORP is a very solid measure doesn't mean that UZR is. I think that the very brightest though are smart enough to realize this and aren't as dogmatic as they were in the past.

[dawgfan]

Originally Posted by lynchjm24

True to a degree. There are certain areas that are much more science and less gray.

I have no doubt that as far as quantifing the offensive contribution of a player sabermetrics does a tremendous job. The offensive metrics tell 99% of the story. If an offensive event has already happened, it can be quantified.

There are other areas where there has been great work, but it's still much grayer. For example, defense. I'm a huge stat guy, but I'm still going to weigh the observations of a player on defense very heavily when making decisions about them.

I think that sometimes the people who follow this closely blur the lines between these sorts of things. Just because runs created or VORP is a very solid measure doesn't mean that UZR is. I think that the very brightest though are smart enough to realize this and aren't as dogmatic as they were in the past.

I agree with the thought that we're much farther along in quantifying hitting contributions in a meaningful way than we are for fielding. Areas I was thinking of though are more along the lines of thoughts on clutch hitting, the extent to which DIPS is true, whether platoon splits are essentially equal among all batters with differences accounted for as just random fluctuation, etc.

On clutch hitting, Bill James was one of (if not the) first people to attempt to prove through data whether such an ability actually existed, and his early attempts found no compelling evidence. Since that time, the concept of clutch hitting has been deemed by stat-heads as a mythical thing, a hoary old concept clung to by old-school baseball types but without merit. More studies have been done since that seem to come to the same conclusion, but pretty much every one I've seen has dealt with the same issues - how do you define clutch hitting (and is it the same thing for every hitter) and small sample sizes. When Bill James in recent years stated he was reconsidering his views on clutch hitting, there was a huge uproar.

On DIPS, when Voros McCracken first published his groundbreaking study on the events pitchers had a great degree of control over and those they didn't, it was a bombshell that quickly converted most of the stat-head community, such that the new gospel was that pitchers have no control over whether a ball put in play against them turns into a hit or an out. This despite a well-researched follow-up study by Tom Tippett showing that, while it's much less of a repeatable skill than strikeouts, some pitchers do have some control over hits allowed. This thought was echoed by Bill James and others (and McCracken himself backed off his initial conclusions somewhat), yet some in the stat-head community haven't gotten the message.

On platoon splits, there was a lot of excitement when James suggested that hitters' platoon splits were all essentially the same if you had enough sample size to look at, and that variations in splits were actually just random fluctuation. I believe he's since backed off from that assertion somewhat, with the current thinking that the concept is more true for left-handed hitters than right-handed hitters, but again this is a recent idea that was embraced by the community and some are having a hard time backing off that initial belief.

What concerns me is that a certain level of arrogance has crept into some members of the stat-head community in thinking that many concepts that have been stated are hard and fast rules, and are very resistant to any reconsiderations of those conclusions by newer studies. Like any science, the theories of sabermetrics should constantly be tested by new theories to see if the existing ones still hold up, or if the newer theories better describe reality. Science and sabermetrics should be as Carl Sagan described a 'Darwinian survival of the fittest theory'.

[cuervo72]

Originally Posted by dawgfan

If you trust the runs created formula to accurately predict actual run output (and the more sophisticated versions get extremely close in this regard) you can experiment - take a lineup full of guys with a certain batting line and see what they produce as a collective in terms of runs.

Off on a little bit of a tangent here, going again from reall baseball to OOTP fake baseball....I actually wrote a program that would:

a) parse through past seasons of stats, and tallying them by stat and rating (so all doubles by guys with 7 ratings against RHP go here, all HR by guys with 4 ratings vs LHP go here, etc). Determine percentage of time per AB that said outcome occurs for that rating occurs (I do this from the Joe/BOSI exporter...accounts for league totals better I think).

b) use these composite components to build a profile for a given guy and his ratings sets (vs RHP and vs LHP)

c) for teams, parse the vLHP/vRHP lineups, adding the components together to find team numbers (vRHP numbers are weighted to account for more RHP)

d) determine how many outs the team will make for the number of PA, then adjust them up or down to match ~ 27 * 162

e) plug numbers into RC formula

f) do the same for pitching

g) place leaguewide numbers in a spreadsheet, balance leagues, and figure out pythag (using 1.83 factor) records

(Step d) is at the heart of what what we're discussing here...obviously with more BB and less outs, the team's overall production goes up. I haven't run numbers with all OBP guys vs all SLG guys, so a mix of both may be the ideal. But in general, OBP = desired just because you keep rolling over the lineup)

Some minor adjustments and steps may be in the process that aren't detailed, but that's the basic approach. Works pretty well too.

http://www.thefobl.com/forums/showth...es+projections
http://www.thefobl.com/forums/showth...es+projections
http://www.thefobl.com/forums/showth...es+predictions
http://www.thefobl.com/forums/showth...es+projections

[/end partially self-promotional tangent]