StrategyFebruary 9, 2012


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Drafting to Win in Roto Leagues

By Michael Marinakis

In the time of the year when mocks are running rampant, there is a lot of data being pumped out that isn’t being used to it’s full potential. One of the most important pieces of data we get from mock drafts are MDPs, which are quite important to finding where the best values can be had throughout the draft. Other than those MDPs, however, mock drafts are pretty much just run and then thrown to the wayside. Another useful way to use this mock data, is to calculate a rough idea of the total roto points you’ll need to win your league. By applying the projections you use to the mock draft results, you can get projected team stats which can then be compared to get projected roto standings. This can give you a very general idea of what kind of stats you’ll need to accumulate in order to have a successful fantasy season.

Most people go into their drafts with their rankings and a general idea of where they want to draft their favorite sleepers. However, if we go further than that and create targets for stat totals in each roto category, we can better adapt to our team needs during the draft. It’s a little time consuming, but it’s also an easy way to get a leg up on your competition in the draft. The following table shows projected finishes based on applying my own projections to each of the 14 completed rosters in the mock draft.

In this article, I will be using the results from the first cafe mock draft and my own projections to calculate projected standings based purely on the draft (I also used Baseball Forcaster to fill in for a few players that I did not have projected). Obviously there are a ton more variables as a real season progresses and teams deal with injuries, trade, and add free agent pick-ups, but for this exercise we’re ignoring that to get a very rough idea of what kind of totals our team will need to win our league through the draft alone.

 RHRRBISBAVG WSSOERAWHIPTotal
GiantsFan14141314710 13.51213128116.5
NeatoTorpedo21411.544 10117.581385
ensanimal11111057 3.513114782.5
Urban Cohorts12121329 85106582
TheRock925126 11101251082
Element1056103 714571481
rjforlife86211.52 1231414274.5
saltydog13341311 13.5193171.5
daullaz399313 226111270
ayebatter47.57141 573101169.5
J35J643812 997.51463.5
wrveres77.5865 1629960.5
fast dogs111914 64413659
raiders_umpire5101118 3.5812352.5

It would have been pretty much impossible for me not to finish first in this exercise seeing as how I’m using my own projections. Still, it gives us an idea of how many points we need to score in order to win. This mock was done by some of the Cafe’s best, and as such we can expect that the final scores will be somewhat close together. Leagues with more disparity in owner skill should see higher point totals, and some leagues will see point disparities grow as managers having poor seasons start paying less attention to their teams. This draft would have been won by a score a lot less than what I managed, but based on that knowledge and prior experience, you should aim to get around third or fourth in each roto category to win the league. In this 14 team league, that’d be a total score of around 115.

PtsRHRRBISBAVG WSSOERAWHIP
1411282981078244.289 999013883.301.14
1310732911070217.288 998713463.361.17
1210412821057211.280  96861322 3.37 1.19
1110352801057195.278  94781290 3.441.20
1010272771023182.277 926712893.471.20
910262661007170.277 906612793.491.20
81023262995159.276 886512583.501.20
71013262987144.275 876412583.521.20
61007254977138.273 856211463.541.21
51006251976137.272 825611453.581.25
41005246962122.272 805011403.591.25
3990243957113.270 804511313.601.25
2984241950106.269 764211273.651.26
1967179920101.267 682810843.731.28

The bold stats are around what we should target in order to finish third or fourth in each category. If we can manage that kind success across the board, we have a pretty good shot at winning the league. If you want to try punting a category, like saves, you’ll have to aim for around 12 or 13 points in each category in order to hit the target number of points. Remember, this is a pretty deep league with 14 hitters and nine pitchers being started. As such, counting stats, ERA, and WHIP will be higher than we’d see in shallower leagues while average will be lower. You can use the same method on a mock with the same league settings as your own to get a better idea of what stats you should target int your own leagues.

Looking at the stats required to put up a third or fourth place finish in each category, we see that an overall line of around 1040 runs, 280 homeruns, 1060 RBIs, 200 stolen bases, and a .279 average will get us there in the offensive categories. In pitching, we’ll need to see something along the lines of 95 wins, 80 saves, a 3.40 ERA, 1.19 WHIP, and 1300 strikeouts. Once we have this baseline of performance as a target for our draft, we can track our progress in relation to our target stats in order to find weaknesses and address them as the draft goes on or through trades after the draft completes.

There will of course be times where we can make up for deficiencies in one category by scoring higher in other categories, but it becomes more difficult to make up stats across the board as you do progressively worse in one category. For example, if you were to punt stolen bases, you would need an improvement of around 40 runs, 15 homeruns, 30 RBI, eight points of average, five wins, 10 saves, seven points of ERA, 50 strikeouts, and four points of WHIP in order to make up for the points you lose in stolen bases. If you take into account that drafting guys with less speed will probably cost you runs as well, then you have even more room to make up in the other eight categories. The same can be said about punting saves which in turn likely hurts your ERA and WHIP.

Also keep in mind that getting first in a category isn’t always a good thing. For example, in this mock the stolen base leader had 27 more stolen bases than the manager in second place, but obviously he only needed one of those to get the 14th point. That’s 26 stolen bases that went to waste and could have been used to improve his team elsewhere. We could take it even further and say that he had 60 stolen bases more than what was necessary to get 11 points in the category. Are three points really worth drafting an additional 60 stolen bases? Are there other spots where we can use those additional numbers more efficiently? If he had drafted even 30 less stolen bases and instead drafted 30 more homeruns, he could have gained five points in the standings. Of course it’s not as cut and dry as that, and in most leagues you can trade from a surplus, but this example is a good way to show how important it is to avoid empty stats. By aiming for production in all 10 categories rather than over-drafting in some categories to try and make up for deficiencies in others, we maximize the efficiency of our stat totals and prevent any useless production. In the end, it looks easier to draft a balanced team and aim for lower across the board stats to put up a similar final point total.

Remember, this is a very rough process. Using other projections, different managers, and different sized leagues are all variables which will inevitably effect how the final results turn out. This is only meant to give a very basic idea of the kind of stats you need to draft in order to win a league of this size. By trying the same process on your own mock drafts that closer represent your own leagues, you should get a better idea of what you need to accomplish in the draft to put yourself on the right track to a championship. In the end, it takes a combination of a successful draft, shrewd in-season maneuvering, and of course some luck to bring the trophy home.

Note: If you decide to try this on your own, feel free to use my projections, or whatever projection system you choose. Since mine is in excel format it’s easy to extract the data and total it up for each team. It’d be great if people could post their own results in the comments section including the number of teams and roster sizes so we can get an idea of how the target stats change as the league size changes. If there is enough interest, I may do a similar post using the 12 team cafe mock when it finishes.

 
Michael Marinakis is a 26-year-old Giants' fan who took 2011 off from fantasy baseball to bask in the glory of the World Series victory. He's now back in the game and looking forward to another year of baseball obsession. You can find him on the forums where he posts as GiantsFan14 or on Twitter @FBC_GiantsFan14.
 
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