59 Responses

  1. Tanner Bell
    Tanner Bell October 12, 2013 at 2:10 PM | | Reply

    Please post your questions or suggestions to improve the rankings system in the comments here.

    1. John czajkowski
      John czajkowski January 22, 2014 at 7:54 AM | | Reply

      How would you calculate era and whip? And say a specific ratio like k/bb? Thanks for the great work.

      1. Tanner Bell
        Tanner Bell January 22, 2014 at 11:56 PM | | Reply

        The calculations for ERA and WHIP are documented at the very end of the article under the section “* Note About Pitching Rate Calculations”.

        K/BB is interesting. Remember there are two things you will need to calculate:

        1. The increase in K/BB required to move up one spot in the standings. To calculate that, take the average ratio of the category winner for the last several years and subtract the average ratio of the last place team in the K/BB ratio category for the same period. Then divide that difference by 11 (assuming a 12 team league).

        2. You need to weight each player’s K/BB performance and figure out their effect on an average team. I’m wildly speculating because I don’t have data to draw from, but assume the average team in your league had 1,300 Ks and 400 BBs, or a ratio of 3.25 K/BB.

        For a 9 pitcher staff that’s 144 K per pitcher and 44 BB. So an 8 pitcher staff would have had 1,152 K (144 * 8) and 352 BB (44 * 8). If the pitcher you are evaluating has 200 K and 60 BB, he would bump the ratio from 3.25 up to 3.28 (1,152 + 200)/(352 + 60).

        Then divide this increase by the answer from the first bullet in this comment. (.03 / XX)

    2. john czajkowski
      john czajkowski January 25, 2014 at 2:51 PM | | Reply

      This may seem like a rather simple question, but how do you add the formulas so that they automatically calculate the SGP for say wins, saves, etc.? I added the formula in the column, but it didn’t do anything, the column is blank still. Please help.

    3. john czajkowski
      john czajkowski January 26, 2014 at 12:25 PM | | Reply

      Tanner,
      Also, looking at the Excel chart posted with this page. I cannot find the SGQ ERA based on your ERA formula. Give me an example please of how you end up with a specific SGP for a P.

  2. Don Mallo
    Don Mallo January 18, 2014 at 11:51 AM | | Reply

    I have been Commissioner and founder of the Rockland County NY, Roto League since 1981 and have to congratulate you on the most clear and precise explanations of the SGP method. Well done. The average seniority in our league is 24 years and no one has come close to explaining SGP. in fact, I am going to translate our historical stats based upon your method. By the way , we are a 6×6 non keeper ultra league rostering 12 hitters, 9 pitchers and 2 reserve spots for $250. Have you compared SGP with PVM? If so, what’s the variation, if any?

    Against, thanks and I look forward to future articles.

    Regards,
    Don Mallo

  3. john czajkowski
    john czajkowski January 22, 2014 at 5:38 AM | | Reply

    How’d you calculate .0024 above for AVG?

  4. Don Mallo
    Don Mallo January 25, 2014 at 9:59 AM | | Reply

    Looking forward to your article on PVM. Will be interesting to compare the rankings. Getting back to SGP for a moment. Have you posted an article on translating the SGP scores into dollar values? I have created a sheet using our 16 team 12 category league but am unsure if my method is correct. Our total pool is $4000 (250 x 16) and I have allocated this pool between hitting and pitchers on a .70/.30 ration for simple math. This leaves $2800 for hitters and $1200 for pitchers.

    I then calculated the total number of points achievable by league members for the 6 hitting and 6 pitching categories in our 16 team league (1644 total points with 822 for hitters and 822 for pitchers) and divided these results into the appropriate dollar allocation to obtain a dollar value per point. (Our league uses an extra point for 1st place in a category so that the leader gets 17 points and the 2nd place team gets 15).

    I then multiplied the dollar value per point by the appropriate SGP number using your methodology to obtain a dollar value.

    Would appreciate your insight.

    Thanks again for a great and well-presented series.

  5. KG
    KG January 28, 2014 at 9:15 PM | | Reply

    How do you handle outlier historical data? I’m in a 10 team NL only 4×4 (OBP instead of Avg) and its hard to find reliable values for that setup so this year I’m giving SGPs a shot this time around. Our league has historical data going back to 2001 (the league has actually been around since 1988) so getting the data for the counting stats is very easy. Unfortunately for the rate stats our website has only recorded the final number and not the components (PAs, IP, Hits, etc) that went into those final numbers. As this is not a common league finding a compilation of data like Razzball has on a 12 team 5×5 mixed is a little hard to do.

    I think I have found a decent way around this. On the site I can get the player stats for each season and so I pulled that data and came up with a yearly average OBP from the Top 140 players that the site lists (exactly how their rankings are calculated I’m not sure). I’m looking at data from 2009-2013 and for three of those seasons my average OBP is a perfect median number and one of the years its only off by one (four above, 6 below).

    However 2009 is super funky. When I calculate the average OBP my result would have place between 7th and 8th which isn’t that close. The interesting thing is that this average is the highest average of the five year period I am looking at, the recorded OBPs for that season were apparently insane. Looking at the data I noticed that season’s AB’s and Hits were about 10% less than the 2010-2013 data (which were all remarkably consistent). I’m having a hard time reconciling how my “average” OBP (once again I’m not certain on the actual results each team had) is so much lower than what the median should be. I know data is data but seeing how the odd this is all seeming I’m thinking about just throwing out 2009 all together (and will therefore have to throw out the 2009 counting stats too).

    Also, has anyone given any thoughts to the effect of the Astros moving to the AL is having on historical data in mono leagues? Comparing the 2013 data my regression lines are not as steep but I’m not sure how much that has to do with the Astros based on one year of data. If there is an effect I’m not exactly sure how to quantify and adjust for it.

    1. Tanner Bell
      Tanner Bell January 28, 2014 at 11:55 PM | | Reply

      KG, you ask a number of really good questions. I’ve always played in standard mixed leagues, so I’ve never run into these issues myself before. But these questions have me giving long looks at the other ranking approaches (PVM and z Score), because they’re not so dependent upon league history. They are inherently “forward looking”, whereas SGP is looking at the past and assuming history will repeat itself.

      I hope to eventually write up how to do all three approaches. But I can’t say when I’ll have something like that completed.

      I have been thinking about if it makes sense to include league history from 5-10 years ago in SGP calculations because the offensive environment has changed so much. I don’t have any science to back me up, but I am thinking it would be best to eliminate anything prior to 2009 from your calculations. I think it will just muddy the water too much and possibly give you inaccurate results.

      1. KG
        KG January 30, 2014 at 9:43 AM | | Reply

        Unfortunately when i was working through the pitching data my workaround solution went out the window. When I go and pull player stats from previous years, our site (CBS) didn’t lock/archive what players were actually present. I noticed this while going through last year’s pitcher data and saw Fister show up despite being in the AL last year. I was also noticing that my top 90 pitchers also included several middle relievers who were not rostered during the season which was also throwing off the data.

        Since I don’t have reliable historical data (I’m going to make a better attempt this season to keep track of the rate stats), I’m going to have to move on from SGP even though my gut tells me that for established leagues it might be the better way to go. I’m not convinced on PVM on my limited study of it so far, it seems like you need to do too much adjusting by guesswork to balance the individual stats.

  6. AT
    AT February 3, 2014 at 3:49 PM | | Reply

    Apologies if this was covered somewhere and I missed it…seems like a bit of an obvious question. I’m in a 20 team H2H re-draft league and I can’t seem to find the magic place where it shows past stat totals. Would the SGP for a 12 team league be similar, or do I have to somehow obtain that information (which I’m having trouble finding.)

    Sorry if that’s a dumb question, never really got into the nitty gritty world of spreadsheets before and I’m not really skilled with excel. Thanks for this guide, it’s really helped a huge amount.

    1. Tanner Bell
      Tanner Bell February 3, 2014 at 11:55 PM | | Reply

      I think the fact that there are 20 teams will affect the SGPs. Being a H2H league also complicates things because it is a legitimate strategy to punt one or more categories in H2H leagues. But I don’t suspect it will affect things too much. The players you establish as “replacement level” will be the biggest difference. What site is your league run from?

      1. AT
        AT February 4, 2014 at 8:58 PM | | Reply

        Yahoo. Some guys are using z-scores instead and I’m not sure if that’s a preferable method for H2H. I think I’m going to try running with this and see how it works out and also since it’s easier to understand. Would you be able to take an educated guess at the SGP for K/BB?
        Thanks.

        1. Tanner Bell
          Tanner Bell February 5, 2014 at 9:58 PM | | Reply

          AT, I can’t give an educated guess. But if you have your historic league standings/results available to you in Yahoo, you can perform a calculation yourself using the tool here. You could just fill it out for the one category you need.

          1. Tanner Bell
            Tanner Bell February 5, 2014 at 10:01 PM |

            And while I can’t give the SGP calculation, I do discuss an example of how you would calculate it above in this comment.

  7. Ryan B
    Ryan B February 4, 2014 at 12:24 AM | | Reply

    Tanner,

    Just found your site recently and have been enjoying what I’ve seen so far! Nice writeup on SGP, I’m personally a bigger fan of using z-scores (and using historical stats for std devs), but the concepts seem essentially the same.

    Question time: I’ve been wrestling with an issue lately that I’ve been personally referring to as the “Hanley Ramirez problem” – certain players, especially elite ones with injury histories, tend to be projected for ~550 PA or less while still managing to be well above replacement level. But are these various methods correctly valuing these players? As you point out in another of your articles, winning teams maximize their opportunities to get more PAs. If Hanley manages to put up 550 PA of elite production, that still leaves you ~100 PA of some other bum rep lvl SS to accumulate more counting stats. Meanwhile Elvis Andrus is projected (Steamer 2014) to put up almost as much value as Hanley, but over a full 650+ PA, so there’s no bonus playing time value to be had.

    So, have you come across any methodologies that account for this in some way? Certainly we wouldn’t want to go in the direction of Oliver and try to just normalize every player to the same # of PA’s, but maybe some amount of replacement level performance should be added to a player’s statline, weighted based on something like (650-PA)/650? (Maybe 650 PA would not be the number to go with, but something like avg. PA of above-replacement players at each position)

  8. Tanner Bell
    Tanner Bell February 4, 2014 at 1:05 AM | | Reply

    Hi Ryan, I’ve thought about adding this to my process to see how much it will affect things. I envision it would work similar to how the “Replacement Level” lookup works right now. I think you would have to create some kind of a table that calculates the stat line of the replacement level player ON A PER PLATE APPEARANCE BASIS.

    Hanley’s calculation for runs would be:

    Hanley’s own baseline calculation for Runs + (650 – 550) * Per PA Runs from the table

    Where 650 is the “standard cieling” you adjust everyone to and 550 is Hanley’s actual plate appearances. The difficult part is that i don’t think you can give credit for the full 100 games Hanley misses. Some of those he might not be active, but not on the DL. Some will be normal days of rest, etc. You can’t predict some of that accurately. So maybe multiply the gap by 80% or some other measure.

  9. Fantasy Rankings Prep (2 of 3) | FanGraphs Fantasy Baseball

    […] previous article, here are the pitcher and hitter point equations (for an explanation on SGP read here or […]

  10. direwolfdc
    direwolfdc February 13, 2014 at 5:42 PM | | Reply

    Great stuff here! Thank you. How would the step by step calculations change for calculating a SGP formula/value for OBP instead of AVG? More variables than just hits and at bats.

    1. Tanner Bell
      Tanner Bell February 20, 2014 at 11:24 PM | | Reply
  11. Sean
    Sean February 14, 2014 at 5:24 PM | | Reply

    “I know that it takes about 200 SB to win the category. So I draft players to reach 200 SB. Not 12 SB SGPs”

    I would like to know how to compare the SGP of the players you’ve drafted with the SGPs needed to win the league. I feel this would let me know when I’ve over-drafted a stat category and where my needs are to make trades.

    For instance, in my fantasy hockey league I calculated the SGPs of the offensive categories for the season thus far.
    G P HIT BLK +/-
    4.0 11.0 68.7 8.3 5.3

    If I total my teams SGPs up I get 65.3 53.6 16.4 59.3 21.4 in those same categories, respectfully. I know I need 49 126 223 121 14 in each to finish just ahead of the 2nd place team. Basically, I’ve got a feeling that my team has overkill in one stat (Hits) while lagging in another (blocks). How can I verify my hypothesis with SGP math? How can I used SGP mid draft to stop drafting a stat I have accumulated enough of and focus on category holes on my team? MUCH THANKS! Feel free to email me.

    1. Tanner Bell
      Tanner Bell February 15, 2014 at 9:04 PM | | Reply

      Hi Sean, for SGP to work well you must have information about the statistics it takes to win a given category. I don’t play fantasy hockey, but let’s just say you know that over the last 5 seasons in your league it has taken an average of 500 hits to win the category. If your team is projected to exceed 500 hits, then you are overkill in the category. There really is no need to overcomplicate things with SGP math.

      Your sentence “If I total my teams SGPs up I get…” is worrisome to me because this is exactly what I suggest not to do. It’s much safer to simply know the statistics necessary to finish first in a category and see if your projected stats meet those requirements. When you start evaluating on the basis of SGPs there is a greater room for error and noise in the results.

  12. Seth
    Seth February 15, 2014 at 4:07 PM | | Reply

    Maybe I’m just not excel-savvy enough to figure this out, but how could I change things around here to fit the scoring system in my h2h points league? Any help would be great thanks!

  13. Tanner Bell
    Tanner Bell February 15, 2014 at 9:14 PM | | Reply

    Hi Seth. Points leagues do not need to use a system like SGP to rank players. It’s much simpler for a points league. You simply need a set of projections and then multiply those projections by the scoring settings for your league.

    For example, I’m in a points league where doubles are 3 points, HR are 9, SB are 3, H are 5, 3B are 5, BB are 3, and AB are -1.

    So if a player is projected for 40 2B, 30 HR, 10 SB, 200 H, 5 3B, 80 BB, and 600 ABs, their projected points would be 40*3+30*9+10*3+200*5+5*5+80*3+600*-1 = 1,085 points.

    There’s no need to determine SGPs or z Scores or anything like that. You might consider an adjustment for replacement level players though. So if my example player above is an OF and the replacement level OF is projected for 400 points, then I would subtract 400 from every outfielder. The player mentioned above would then have 685 points in my ranking system.

    1. Seth
      Seth February 15, 2014 at 9:37 PM | | Reply

      Thanks for the response! Do I just need to make a separate sheet, and do the formula, for example HR * scoring?

      Also, how would I figure out a replacement level player? Sorry if these are simple questions, just now getting into the depths of all I can do with fantasy statistics!

  14. Tanner Bell
    Tanner Bell February 15, 2014 at 9:54 PM | | Reply

    I do prefer to do my rankings on a separate tab from the projections, but you don’t have to. I do it on a different tab because it makes it easier to download a new set of projections and drop them into the file without having to redo all the formulas again. But it does take a lot longer to set up initially.

    Replacement level is discussed in Part 6, if you haven’t read that yet. But basically you need to know your league size and about how many players will be drafted at each position. If you think 24 SS will be drafted in your league, you can use that 24th SS as replacement level.

  15. Seth
    Seth February 15, 2014 at 10:35 PM | | Reply

    Oh duh, that makes perfect sense for replacement level players. Thanks! Love the excel layout!

  16. help plz
    help plz February 16, 2014 at 3:46 PM | | Reply

    What would the formula be for k/9 if you calculated the average k/9 was 8.0 for your pitcher pool?

  17. mizzoudavis
    mizzoudavis February 16, 2014 at 5:42 PM | | Reply

    Tanner,

    Love the site and your demonstration of SGP. I have a question regarding the example you present in the article. When you mention 14 batter positions, are you counting bench spots? Or just offense position spots?

    Thanks again for your work!

    Mike

    1. Tanner Bell
      Tanner Bell February 20, 2014 at 11:30 PM | | Reply

      Hi Mike, thanks for the kind words. Are you referring to the calculation of BA SGP? For this calculation, I think it is important to only use the number of starting batter positions you have. If you start 14 hitters, then 14 hitters need to be included in the calculation. The reason for this is that a single player can have a larger effect on smaller starting lineups. The same hitter will have a smaller effect on a large starting lineup.

      1. mizzoudavisMike Davis
        mizzoudavisMike Davis February 24, 2014 at 12:47 PM | | Reply

        Awesome. Thanks!!

  18. Drew
    Drew February 25, 2014 at 11:33 PM | | Reply

    When calculating the SPG for Batting Average you say “In the Steamer projections, the top 168 major leaguers..” Who are these “top” players? The players with the most ABs? Great site, keep up the good work.

    1. KG
      KG February 27, 2014 at 9:01 AM | | Reply

      Hi Drew,

      This is something I struggled with at first until I figured it out (at least for hitters). Note that I’m using z scores instead of SGPs (I do not have enough historical data for my league setup to do SGPs) I think the method should work just as well.

      1) Bring up your entire projection list for hitters and run the calculations for the counting stats (R, RBI, HR, SB) just the same as Tanner has listed above for all of the hitters you have projected.
      2) When it’s time to do batting average (or OBP or whatever else you might use), just take the first 168 players on that list, it doesn’t matter what order they are in.
      3) Calculate your average ABs and Hits based on those first 168 and apply the calculation to your entire set of players.
      4) Calculate your total SGPs for each player.
      5) Once you have done that, sort your project list by your SGP totals. This should re-sort the list based on your original averages and give you a new set of 168 to work with.
      6) If you setup your formulas so that they update automatically you’ll just need to re-sort your list a few more times until the list stops changing and you should have your 168 (or however many you need with your league setup) hitters. If you’re in a 2 catcher league you may need to add a catcher or two at the bottom of your list.

      I tried to do the same thing for pitchers but it hasn’t come out very well, it keeps trying to put a lot of middle relievers in my pitcher set that have a rare chance of getting drafted. I’m trying to find a method that works there but I haven’t been happy with my results so far.

    2. Tanner Bell
      Tanner Bell March 5, 2014 at 10:12 PM | | Reply

      Drew, great question. I just chose the 168 hitters with the most projected ABs. But you made me second guess myself. And upon further review, that’s probably not the best means to identify the top 168 hitters.

      The method KG describes is probably the best way to identify the top 168. But I also thought it would be helpful to quantify the difference between the two methods.

      Above I mention the formula for BA is “=(([@H]+1768)/([@AB]+6617)-0.267)/0.0024″, where 1,768 represents the average number of hits for a team, and where 6,617 represents the number of at bats the average team hits.

      That is based upon the average hitter having 509 ABs and 136 H (for a .267 average).

      If I look at the top 168 players after I’ve ranked them (and not just the 168 with the most ABs), the average player is projected for 495 ABs (instead of 509).

      A .267 BA on 495 ABs would assume 132.2 H (.267 * 495).

      That means the average team would have 1,851 H (14 * 132.2) and 6,930 AB (14 * 495). Adjusting that to the 13 players necessary to calculate one player’s impact is 1,719 H (13 * 132.2) and 6,435 AB (13 * 495)..

      Running Trout’s 2013 Steamer projection (184 H, 619 AB) through yields the following:

      (184 + 1,719)/(619 + 6,435) = 1,903 / 7,054 = .26977 New Team BA.

      .26977 – .267 = .00277

      .00277 / .0024 = 1.154

      So Trout’s SGP on the top 168 players is 1.154. When I ran it on the 168 with the most ABs, it came out to 1.151. So the difference is negligible. But in a perfect world, you should do an analysis similar to what KG suggests.

  19. Redbird
    Redbird February 28, 2014 at 9:09 AM | | Reply

    Would you adjust the SPG formulas posted above if the league is a 10 person league rather than a 12 person league? I’d imagine it would shift the values some…just not sure if it’s significant enough to need to recalculate. Thanks!

    1. Sean
      Sean February 28, 2014 at 9:35 AM | | Reply

      There’s only 9 hitters per team in my 12 teamer. Since I don’t have access to past years’ data, would you expect using your/or other public SGP values to be in the realm of correctness?

    2. Tanner Bell
      Tanner Bell March 5, 2014 at 10:18 PM | | Reply

      I think using the SGP method is still sound. But you need to make an important adjustment in the calculations. You need to adjust replacement level for your specific league.

      For example, if you’re in a 10-team league instead of 12-team, you won’t use the 24th catcher as replacement level (assuming a 2 catcher league). It might instead be the 20th catcher.

      Or if it’s a 12-team league with 9 hitters, you might use the 12th catcher.

      You can use the rough SGP calculations, but you HAVE to adjust replacement level for your own league’s roster sizes.

      Once you get some final standings for the league, then you could refine the calculations by calculating the SGP factors.

  20. Matthew Scott Martin
    Matthew Scott Martin March 1, 2014 at 12:34 AM | | Reply

    Tanner, I am in a 10 team, mixed, standard 5×5 league. How can I change the formulas in the SFBB-Rankings-Part-4.xlsx for use with my team in this 10-team league? Thanks. I appreciate how you freely share your information. Love this site. Unfortunately for you, I won’t be sharing this site with my league-mates, but perhaps others who play in different leagues.

  21. Tanner Bell
    Tanner Bell March 5, 2014 at 10:23 PM | | Reply

    Hi Matt. Unfortunately, I don’t have an established history for 10-team leagues to draw from. If you have an established league history where you can access prior season standings, you can calculate these things yourself using the “What It Takes To Win Your League” tool.

    But even if you don’t have past standings to draw from, I think you will still get meaningful results from using the same formulas I have listed on the site here.

    As I mentioned right above here, the very important adjustment you must make is in determining replacement level for the 10-team league. Use your actual roster composition and the fact that you’re a 10-team league to figure out who the replacement level C, 1B, 2B, etc. are in your league.

  22. Jimmy
    Jimmy March 10, 2014 at 10:01 AM | | Reply

    Hey my league is a 10-team mixed league but only in our second year. Added new GMs as two didn’t even pay attention to their teams last year. So don’t trust the differences in points. You know a place to find 10-team league SPG numbers?

  23. Jimmy
    Jimmy March 10, 2014 at 10:19 AM | | Reply

    Ignore my question just saw your reply to March 5 post.
    Thx

  24. Jimmy
    Jimmy March 11, 2014 at 2:46 PM | | Reply

    I’m just wondering if I should use different formulas for Starters and Relievers. I’m in a 10 team league with 5 starters and 3 relievers per team. Our categories are W, L, HR against, ERA, K/9, BB/9, H/9, SV. As you can see there are many ratio stats there, so relievers have more value. After doing this exercise however, the discrepancy is too large (all relievers are worth more than any starter).
    So let’s assume all my numbers are without error (doubtful), I still wouldn’t pick Kimbrel ahead of Kershaw, no one would, but if I separated out the RP and SP, I could wait til people start picking relievers and use my RP list a that point.
    I could use the IP and ER averages for the top 50 starters, and do the same for the top 30 relievers and make separate ranks. Maybe I’m way off track.
    Thoughts?

    1. AT
      AT March 11, 2014 at 2:57 PM | | Reply

      Maybe not my place, but my way of getting around this issue was simply converting ratio stats into counting stats. My excel formula looks like this: =([@ER]*9-([@IP]*AVERAGE($Q$2:$Q$264)))*-1 where Q is ERA. This works for any stat, take the numerator and multiply by the denominator*the league average for that ratio stat. I went with z-scores over SGP in the end (lack of league history plus I think SGP works better for roto leagues, I only play 20 team H2H) so I am not sure how you would calculate SGP from that.

      1. AT
        AT March 11, 2014 at 2:59 PM | | Reply

        *subtract the denominator, not multiply, sorry.

      2. Drew
        Drew March 11, 2014 at 3:09 PM | | Reply

        You will want to treat those categories like Tanner has treated the other ratio categories. “Does the fact that Trout will hit .297 over nearly 200 more at bats make him more valuable? Or does Tulowitzki’s .300 average make him the better “batting average contributor”?” Think 200+ IP of Kershaws’ K/9 vs 60 IP of a Kimbrel.

    2. Tanner Bell
      Tanner Bell March 16, 2014 at 11:34 PM | | Reply

      Hi Jimmy. If your categories really are W, L, HR against, ERA, K/9, BB/9, H/9, and SV, then I think it makes sense for relievers to have more value than starters. A reliever will have fewer losses, fewer HR against, a lower ERA, better ratio stats, and more saves. The only benefit to having starters is the W category.

      I do not think it’s necessary to treat SP and RP as different groups. But you should calculate replacement level separately for the two groups. The calculations will all be the same, but starters will be compared to replacement level starters and relievers compared to replacement level relievers.

      If you follow the formulas for weighting the stats, you’ll be fine.

  25. Jimmy
    Jimmy March 11, 2014 at 3:46 PM | | Reply

    Hey thanks AT and Drew,
    AT – Where do you find z-scores? I must have missed something.
    Drew – I agree, I’m just thinking from a strategy point of view; with our cats, my numbers say RPs are worth the most, but strategically it doesn’t make sense for me to pick RPs in the 3rd round for e.g. So I’m just looking for relative value between SPs and RPs, I understand the contribution aspect, but I will just use my RP list when guys start drafting RPs.

  26. AT
    AT March 11, 2014 at 3:57 PM | | Reply

    Z-scores are different from SGP and simpler to integrate. You just standardize all the stat columns your league uses and add them together. For example, my z-scores for K/BB: =STANDARDIZE([@XKBB],AVERAGE($T$2:$T$180),STDEV($T$2:$T$180)) Where T is XKBB, which is K/BB converted to a counting stat. Then you just mash them together. My rankings passed the sniff test, so I’m happy with it. It’s just an alternate to SGP.

  27. PEDex
    PEDex March 14, 2014 at 4:09 PM | | Reply

    My league is switching over from AVG to OBP. Any advice on adjusting ranking calculations for OBP without inflating its overall weight?

  28. Matthew Scott Martin
    Matthew Scott Martin March 16, 2014 at 1:07 AM | | Reply

    Tanner, being a neophyte at ;Excel, I do not know how to do this one thing other than manual. I would like to grab the PlayerID, LN, FN, POS, and TTLSGP columns from both the Hitter Ranks and Pitcher Ranks tables and merge them into one worksheet and table so I can compare the pitcher and hitter Totals at a glance w/o having to toggle back and forth between sheets. How do I do this? I will have enough to do on draft day (two draft day software pkgs. [I might buy a 3rd b4 DD], and at least three spreadsheets besides your SGP sheets). So, I don’t want to be toggling any more than necessary. BTW, just bought the entire 10 chapters so I could read up on the impact of keepers; I am in a keeper league.

    Thanks

  29. PAR for the Course « DTBL News
    PAR for the Course « DTBL News June 14, 2014 at 1:13 PM |

    […] Here’s the page I discovered on a site called Smart Fantasy Baseball.  It’s definitely worth checking out because it probably describes the concepts a lot more clearly than I will be able to.  But what I’ve come up with is not exactly the same, so I will describe PAR in all of its gory details in just a bit.  The linked page describes a concept of player valuation called “Standings Gain Points” or SGP.  So I could have called this new stat SGP as well, but I had already picked PAR before I ever saw anything about SGP.  The concept is the same though.  SGP is the number of points in the standings that a particular player earns for his team.  There is a replacement level concept built into it as well, but that is where my formula is a little different.  One thing to keep in mind is that SGP, and probably other stats like it, are primarily designed to assign values to players to assist with draft preparation or to set future performance projections.  Most of the big sites that develop pre-season player rankings probably incorporate these ideas into their rankings and dollar value assignments.  But that’s not what I’m looking to do here.  I don’t intend to use PAR in pre-season projections or rankings, partly because I assume you all have your own methods of draft preparation (or lack thereof) that you do on your own anyway. […]

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