My goal here is to explain the difference between preference points and bonus points, how each works, and how to use drawing and harvest statistics to put your bonus and/or preference points to work for you. Finally, we'll discuss some of the pitfalls to avoid when using statistics.
Bonus Points:
Bonus points generally increase the number of times your name "goes into the hat" for a big game drawing. These points are usually accrued when an applicant fails to draw their first choice permit for a given species in a given year. True bonus point systems, like the one used in Nevada, do not guarantee (
nor do they set aside tags for) applicants with the most bonus points. We can see this in the table, by looking at unit group 011-013, fourteen people drew tags with zero preference points while one applicant with seven points didn't draw.How do Bonus Points work?
Let's stick with Nevada as an example. When entering the big game drawing in Nevada, bonus points are "squared" and this determines how many times your name is entered into the drawing. In other words, if you have 5 bonus points for elk, the system squares your points and your name goes into the drawing 25 times (5x5 = 25). The system then applies a random number to each of your 25 entries with the lowest number putting you closer to the top of the drawing list. Once each applicant has been entered into the system, and random numbers have been assigned, the computer does the rest. All you can do is wait, hope and chew your finger nails.
It's important to maintain bonus points on a year over year basis because, as discussed above, the more points you have the more chances you get in the drawing. Look at it this way, with five points this year your name is entered 25 times. Three years from now, with seven points, your name is in the drawing 49 times! That's nearly double the number of chances just because you maintained your points for another two years! In Nevada this is especially important because some tags can take up to ten years to draw!
Preference Points
Preference points work differently than bonus points in that applicants with the most points generally draw the tags. Preference points are usually accrued when applicants fail to draw their first choice permit for a given species in a given year.
How do Preference Points Work?
Colorado is probably the best example of a true preference point system, so I'll use information from the Colorado DOW website to explain their system based on a specific hunt.
In the first table, on the far left under Hunt Cde it says - EE076O1A. This means either sex, elk, unit 76, 1st season, archery. Under Quotas, it has Reg (regular, resident license), LOwn (landowners), NRes (non-residents), Yth (youth). You'll notice that a total of 125 licenses were issued under this hunt code. Under No. Apps (# of applicants), these are the number of people who applied for this license as their 1st choice and 2nd choice - 684 had it as 1st choice, 148 had it as 2nd choice. The next 2 columns are Public/Land Owner - that is the number of people who applied broken down by category - 315 residents applied, 362 non-residents, no youth, 4 resident landowners, and 3 non-resident landowners.
In the bottom table, the top 2 columns, 0-11+ is the number of Preference Points. The columns wrap which is confusing. The bottom 2 columns are the numbers of hunters with those preference points that applied. So, in this example, 193 hunters applied with 0 preference points, 138 applied with 1 preference point...(next column), 3 hunters applied with 6 points (bottom row, far left column), 2 with 7 points, and no one applied with 8 or more points. To see how many preference points it took to actually get the license - look at the Quota (from table above), which was 125 total licenses issued, then count backwards under Preference Points (bottom row, far right side 1st, last number listed) until you reach 125. You count starting from the hunter who applied with the most points to see how many points you needed to get the license that year. Thus, you would add 2 + 3 + 6 + 19 + 134 = 164. So hunters with 7,6,5,4 and some who had 3 points all drew that license. The hunters with 2,1, and 0 points did not draw. These are only tallied for the 1st choice, in this case.
It's pretty clear from the above example that preference points do favor applicants with the most points and that is why it is critical to maintain points year over year. Look again at the number of applicants with three points (134) vs. those with 4 points (19). All things being equal, that one extra point increases your chances by three times and (for this hunt) would have guaranteed you a tag.
Maintaining both preference points and bonus points is accomplished by applying for tags each year or, in some states, purchasing a point each year if you are unable to apply for a tag.
Drawing Statistics
Most big game hunters have heard the term "drawing statistics" at one point or another. But, what are all these fancy reports telling us and how can we use them to our advantage? The purpose of this section is to introduce you to some different report types and explain why they are useful. We'll again use Nevada as our guinea pig.
The first report shows detailed bonus point statistics for a handful of 2007 pronghorn hunts.
Reports like this are a good tool for determining potential success in 
drawing a tag based on your bonus point group because they break down the number of successful applicants in each point group. For example, look at unit 011. In the 4 point category, 12 out of 24 people drew tags for odds of 1 in 2 (or 50%). Those are pretty good draw odds in that point category. Some additional information this report lacks, however is information, such as harvest statistics, which will further help determine which tags to apply for.
The harvest report shown here can be used to compare drawing odds (from the report above) with the success rates of the people who hunted. We can see from thi
s report that 40 out of 54 hunters in unit 015 were successful on their hunts (74% success rate). One word of caution: Do not use harvest reports to determine drawing odds. We'll discuss below why that is a mistake.
The most common mistake people make when using drawing reports is to make their hunt selections based on a single report. To avoid this, be sure review as many reports as you can. Looking only at point statistics is a mistake because it opens you up for the potential of drawing a unit with historically low harvest. Compare point reports with harvest reports!
Another mistake to avoid is using harvest reports to determine draw odds. For example, look back at unit 015 in the pronghorn harvest report above. Based on this report one is led to believe they have 1 in 7 chance of drawing a tag in that unit. That's because this report only tells us the total applicants vs. the total number who drew tags. If you were to apply for unit 015 with zero points thinking you had a 1 in 7 chance of drawing a tag, I'm afraid you'd have made a mistake. Going back to the detailed bonus point report we can see that only one person out of 110 drew a tag for this unit with zero points. Odds of 1 in 11 are much different than 1 in 7.
Use these reports wisely and study more than one report. Connect the dots with as much information as possible on a single unit and you're likely to make a sound decision.
Recap
By now you should have a good understanding of the difference between bonus points and preference points. Bonus points give you more chances at drawing a tag but do not guarantee tags for those with the most points. Preference point systems do not guarantee tags either but, tags generally go to the folks with the most points.
Drawing statistics and harvest reports are invaluable tools when applying for big game hunts as long as they are used correctly. Be diligent, use every report you can find and you'll likely avoid some of the mistakes we've talked about. Avoiding mistakes will help paint a clear picture of your chances before you apply for that tag of a lifetime.
Good luck and, as always, drop us a line if you have any questions.
Good hunting!
Steve
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