Early in the season, standings are skewed. If you prorate the category totals over the full season, the totals are out of line with the norm. The top teams in each category have higher totals than expected while the bottom teams have lower totals. Ultimately the separation in the standings will be a reflection of the quality of the teams, but early on, other factors have significant influence: quality of opponent faced, weather conditions, park factors and number of home vs. away games. All it takes is for a couple of teams in your league to have a few extra players who have enjoyed the more favorable conditions to throw your standings out of whack.
So the original question is really asking at what point in the season do all these external factors even out and the quality of your fantasy team is the primary reason for its own fate? To shed light on this matter, I would like to incorporate what has become a favorite tool of mine: average category standings.
Average category standings are based on league history or the histories of leagues with identical scoring formats. The idea is to calculate what it generally takes to finish at a particular point in the standings. Thus the first-place totals for the representative leagues are averaged, then the second-place totals, etc., all the way down the line. This is done across each category and average standings are generated. At your auction or draft, you can use these numbers as targets. Research suggests one needs 75-80 percent of the available rotisserie points to win the league. In leagues with between 12 and 16 teams, this entails averaging about a third-place finish across the board.
While the actual category totals vary from year to year, the percentage of a particular statistic standings place earns stays remarkable consistent, and will be the basis of the ensuing mathematical exercise. The demonstrated calculation will only be applicable for counting stats such as homers, runs, RBI, steals, wins, saves and strikeouts. Stats involving ratios like batting average, on-base percentage, ERA and WHIP cannot be tested in this manner, though the assumption can be made that the ratio stats are real when the counting stats are real.
The prorated standings we will use are different than you might think. Normally, to calculate prorated standings, take the number of games that will be played by season's end (2,430) and divide by the number of games played to date. Then multiply each counting stat by that factor to produce prorated standings. But the problem with doing this likely results in the total amount of each statistic within each category being different.
Recall that studies show the percentage of each stat remains constant from year to year, thus an alternate means of prorating standings will rectify this issue. The principle will be the same but the multiplication factor will be the total number of each stat in average standings divided by the total number of each stat accrued to date. The end result is now a set of standings using the pace of the present standings, but summing up to the totals expected via the average standings.
By means of example, let's carry out the calculation using home runs in a 15-team mixed format. To the right is a table with three columns. The first is the average homers per position using actual 2007 15-team leagues. The middle is the expected total from average category standings. The third column is the prorated total. Summing up the total homers in Column 1 show 232 homers have been scored to date in this style league. By season's end, 4,022 should be included so the multiplication factor is 4,022/232 or 17.33. Multiplying each number in Column 1 by 17.33 renders the prorated amount in Column 3.
Check out the discrepancy with the top two teams. They are on a pace to rack up an incredible number of homers. Obviously, they will regress. The bottom teams will no doubt pick up the pace. While it would be great to be leading the pack, realistically you should be happy with 16 or 17 homers as prorated that puts you right where it should by season's end. This identical process can be carried out with all the counting stats to get you a better picture of where you presently stand.
So let's go back to the original question. When should one get worried about one's place in the standings? My answer is when the prorated standings match up pretty closely with the expected final standings. Since I only thought of the concept recently, I do not have a target date to share, but we can follow our leagues together and come up with an expected date.
What is the practical application of this exercise? Up until the point the pace of the standings are the same, the possibility exists your team can improve or regress just due to luck factors -- both good and bad -- leveling out. This is not to say your team cannot improve or regress on its own after this point. All it means is the above external factors like opponents and weather have evened out. Some players will improve or struggle, but the point at which the two sets of standings match will be my signal to really investigate category management.
Category management will be a topic of future pieces, but in brief it involves the proverbial "managing from strength to improve weakness," but with a necessary twist. Most interpret strength as a category where they are high in the standings and weakness as one where they are struggling. But in reality, you want to improve in categories where there the standings points are most easily attained at the expense of categories where you can lose minimal points. You may be in the top third of a category and still have a couple of points within reach, or near the bottom of a category but be very far way from the next owner. So what will be discussed in ensuing weeks are the manners in which you can realize those potential points while sacrificing as few points as possible.