Data Surgery Analysis Submission Worksheet
Data Surgery Analysis Submission Worksheet
1)Record 5 Q17 if uninsured, all Q17 choices should be zero. 2) If insured. Q16 = zero. Make the corrections and resubmit. | |
Put zeroes in all the blanks in Q16 and Q17. Do this first before you merge your 30 records into the attached 90 records in the 1st sheet. Append your data to this in the bottom to make up records 91-120. Then you can start sorting and copying subsections of the data to their corresponding sheets. Note that you can add more sheets such as vaccinated total, unvaccinated total, involuntarily vaccinated only (A+B), etc. Read the rest of the survey pointers spring 2022 Part 2 of 2 (found in the announcements) and the video on how to do the analysis. Data Surgery Analysis Submission Worksheet |
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SURVEY (NEXT STEPS after data submission is approved)
- After your submission, CANVAS will automatically give it a grade of 10. This does noes not mean that you are ready for the next step. Data Surgery Analysis Submission Worksheet
- I will check all submissions and either tell what is missing, inconsistencies, etc. if any. You will need to make these corrections and resubmit until I give approval. This is sealed by a file of 90 respondents in an excel file that you will use for your analysis. In this file you will add, append or merge your 30 respondents in the bottom to correspondent to respondents 91 – 120 (your respondent 1 should will be assigned 91, resp 2 -> 92, Resp 3 -> 93, etc.)
- Next sort your whole data set (120 total) starting with those choosing A in number 18. Copy all these records and paste in Sheet “A” starting at row 3 (as the 1st 2 rows are dedicated to the header questions and they have already been pasted in these sheets). Next sort on B and do the same, followed by C, D, E, and F. Just copy and paste and do not cut and paste so you will have your master data file intact. You can add more sheets such as the unvaccinated sheet: D+E+F combination. Be careful with the vaccinated sheet. Here A+B seems to be the clear combination. C is involuntarily vaccinated. You can still include it if you want ALL vaccinated but not if you just want voluntarily vaccinated, only A+B. These combinations may help if you are not getting significant relationships with your initial findings.
- After this you can start looking at each response sheet and getting your percentages.
- The main requirement in the analysis are coming up with 4 significant relationships between variables:
- Set up theories between demographic and health variables against Question 18 responses. Example: Higher Education and Choosing A vs. Choosing D in Question 18, High income and choosing not to be vaccinated, Low income and getting vaccinated only because it is required vs. Choosing A, etc. Data Surgery Analysis Submission Worksheet
- Test these theories this way (let us use education vs. Choosing A or B in Q18)
- Get the percentage of those with college degrees and above in Group A (those who chose A in Q18. Then get the percentage of those with college degrees and above in Group D (those who chose D in Q18). Let’s say the percentages you get are 90% in Group A and 30% in Group D. This means you have a significant difference in education.
- However if your percentages are 80% in A and 75% in D, then there is not much significant distinction and you have to go back to the drawing board. The criteria we will use is 15 percentage points. To get a significant and ACCEPTABLE relationship for our purposes, there has to be at least 15 point difference. This exists only in the 90% vs 30% finding and not in the 80% vs. 75%
- Explain your Findings
- Assuming you got the 90% vs 30% result (or as long as the gap is 15% or more) now you can talk about how viewing the pandemic and getting vaccinated as a matter of public health above all is influenced by the level of education. You may also get an opposite result Ex. High ed in Group A is 40% and high ed in Group B in 60%. Enough gap to now say most educated individuals are skeptical of the vaccine.
- So each of the required 4 relationships should include (a) theory, (b) significant percentages from your data proving or opposing your hypothesis (c) explanation of finding. Go through the motion of the explanation even for cases where it seems obvious. So first the percentages should have a gap of at least 15% points or it would not be acceptable meaning you have to choose another relationship. As to part 3 make sure you can explain your finding. If it is counter-intuitive or illogical, see if there are studies or references that find what you found. If not this relationship will not also be acceptable.
- You do not need to do all the percentages in the analysis sheet. Do only those that you will use for your findings and relationships. Data Surgery Analysis Submission Worksheet
- Analysis submission requirements:
- Excel sheet with the 120 records, broken into Q18 responses and percentages used for analysis
- Written analysis of the 4 relationships. Minimum requirement: 1 page Times new roman font size:12 (strongly enforced). Data Surgery Analysis Submission Worksheet
Respondent Number | (1) City | (2) State | (3) Residential area type: 1 = Urban, 0= Rural | (4) Gender 1 = MALE 2 = Female 3 =other | (5) Race = W(white), B(black), H(hispanic), A(asian), O(others) | (6) Age | (7) Marital Status married = M, Single = S, Divorced = D, Widowed = W | (8) Employment | (9) Household Income | (10) Home Owner ? YES = 1, NO = 0 | (11) No. of household members? | (12) How do you describe your Health Status? YES = 1, NO = 0 | (13) Highest educational level attained: 1 = elementary; 2 = high school; 3 = some college; 4 = college graduate; 5 = post baccalaureate | (14) Health Problems | (15) Do you have Health Insurance? YES = 1, NO = 0. If YES, GO to 17 | (16) NOTE: If the answer in (15) is no, why not? 1 = too expensive; 2 = I am healthy I do not need it; 3 = other reason (please state the reason) GO to Question 18 after answering this question | (17) Insurance Type | (18) Are you vaccinated? Why or why not? (choose all that apply) | ||||||||||||||||||
1 = unemployed looking for work; 2 = retired; 3 = unemployed not looking for work; 4 = employed part time; 5= employed fulltime | Below $35,000? (yes = 1, no = 0) | $35,000 – $69,999 ? (yes = 1, no = 0) | $70,000 – $119,999 ? (yes = 1, no = 0) | $120,000 to $179,999 ? (yes = 1, no = 0) | $180,000 and above ? (yes = 1, no = 0) | BAD = 1, otherwise = 0 | FAIR = 1, otherwise = 0 | GOOD = 1, otherwise = 0 | EXCELLENT = 1, otherwise = 0 | Do you have Heart Problems/ Cancer/diabetes,other debilitating disease? YES = 1, NO = 0 | Do you have a Family History of Heart Problem, Cancer, diabetes, debilitating disease ? YES = 1, NO = 0 | 1=employer based (choose this if you are getting your insurance from your employer or if you are a dependent getting your insurance from your employed parents) 1 = yes 0 = no | 1 = MEDICARE; 0 = no | 1 = MEDICAID; 0 = no | 1 = obamacare or ACA 01 = no | 1 = TriCare or VA 0 = no | 1 = other (state the source); 0 = no | (A) YES, Because an infectious disease is a public health concern: 1 = describes my situation; 0 = does not describe my situation | (B) YES, it is required at work but I will get vaccinated even if it is not required: 1= describes my situation; 0 = does not describe my situation | (C) YES, only because it is required at work otherwise I will not get vaccinated: 1= describes my situation; 0 = does not describe my situation | (D) NO, because I choose not to: 1= describes my situation; 0 = does not describe my situation | (E) NO, only because I do not have time to schedule it because of my work and other obligations: 1= describes my situation; 0 = does not describe my situation | (F), NO, because it is not required at work otherwise I will get vaccinated: 1= describes my situation; 0 = does not describe my situation | |||||||||||||
sample 1 | Okeechobee | FL | 0 | 2 | B | 73 | M | 2 | 1 | 0 | 0 | 0 | 0 | 1 | 4 | 0 | 1 | 0 | 0 | 1 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 |
sample 2 | New York | NY | 1 | 1 | W | 26 | M | 2 | 0 | 0 | 0 | 1 | 0 | 1 | 2 | 1 | 0 | 0 | 0 | 2 | 0 | 1 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 |
sample 3 | Athens | GA | 0 | 1 | A | 43 | S | 3 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 5 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 1 | 0 | 1 | 0 | 1 |
1 | Miami | Florida | 1 | 1 | W | 36 | M | 5 | 0 | 1 | 0 | 0 | 0 | 0 | 5 | 0 | 0 | 1 | 0 | 4 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | |
2 | New York | NewYork | 1 | 2 | B | 25 | S | 3 | 0 | 0 | 1 | 0 | 0 | 0 | 3 | 0 | 0 | 0 | 1 | 4 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | |
3 | Phoenix | Arizona | 1 | 1 | A | 58 | W | 5 | 0 | 0 | 1 | 0 | 0 | 1 | 4 | 0 | 1 | 0 | 0 | 4 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | |
4 | Phoenix | Arizona | 0 | 1 | W | 27 | S | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 6 | 0 | 0 | 0 | 1 | 3 | 0 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | |
5 | Columbus | Ohio | 1 | 2 | H | 43 | M | 4 | 1 | 0 | 0 | 0 | 0 | 0 | 3 | 0 | 0 | 0 | 1 | 2 | 0 | 0 | 0 | 2 | 0 | 1 | 0 | 0 | 0 | 0 | ||||||
6 | Austin | Texas | 1 | 1 | W | 21 | S | 3 | 0 | 0 | 0 | 1 | 0 | 0 | 4 | 0 | 0 | 0 | 1 | 2 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | |
7 | Dallas | Texas | 0 | 1 | O | 66 | D | 3 | 0 | 0 | 0 | 0 | 1 | 1 | 5 | 0 | 1 | 0 | 0 | 5 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | |
8 | San Diego | California | 0 | 2 | H | 39 | D | 4 | 1 | 0 | 0 | 0 | 0 | 0 | 8 | 0 | 0 | 0 | 1 | 3 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | |
9 | Jacksonville | Florida | 1 | M | B | 79 | W | 2 | 0 | 0 | 0 | 1 | 0 | 1 | 10 | 1 | 0 | 0 | 0 | 5 | 1 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | |
10 | Hialeah | Florida | 1 | M | B | 31 | S | 5 | 0 | 0 | 1 | 0 | 0 | 0 | 3 | 0 | 0 | 0 | 1 | 4 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | |
11 | Miami | Florida | 0 | M | 0 | 40 | M | 5 | 0 | 0 | 1 | 0 | 0 | 1 | 3 | 0 | 0 | 0 | 1 | 4 | 0 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | |
12 | Orlando | Florida | 1 | M | A | 32 | M | 5 | 0 | 0 | 1 | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 1 | 2 | 0 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | |
13 | Tampa | Florida | 0 | F | W | 23 | S | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 6 | 0 | 0 | 0 | 1 | 3 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | |
14 | Scottsdale | Arizona | 1 | F | W | 35 | M | 5 | 0 | 0 | 1 | 0 | 0 | 1 | 4 | 0 | 0 | 0 | 1 | 4 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | |
15 | Tacoma | Washingyon | 0 | F | B | 26 | S | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 7 | 0 | 1 | 0 | 0 | 3 | 1 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | |
16 | madesto | Califronia | 1 | M | B | 37 | M | 5 | 0 | 1 | 0 | 0 | 0 | 0 | 7 | 0 | 0 | 0 | 1 | 4 | 0 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | |
17 | Yonkers | NewYork | 0 | M | B | 29 | M | 3 | 1 | 0 | 0 | 0 | 0 | 0 | 9 | 0 | 0 | 0 | 1 | 2 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
18 | Columbus | Georgia | 1 | F | O | 72 | F | 2 | 0 | 0 | 1 | 0 | 0 | 1 | 15 | 0 | 0 | 1 | 0 | 3 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | |
19 | Frisco | Texas | 1 | F | W | 34 | M | 5 | 0 | 0 | 1 | 0 | 0 | 0 | 3 | 0 | 0 | 0 | 1 | 4 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | |
20 | Mobile | Alabama | 1 | M | W | 41 | M | 5 | 0 | 0 | 0 | 1 | 0 | 1 | 4 | 0 | 0 | 0 | 1 | 4 | 0 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | |
21 | Cape Coral | Florida | 1 | M | B | 35 | M | 5 | 0 | 0 | 1 | 0 | 0 | 0 | 5 | 0 | 0 | 0 | 1 | 4 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | |
22 | Akron | Ohio | 0 | F | W | 52 | M | 3 | 0 | 0 | 0 | 0 | 1 | 1 | 4 | 0 | 0 | 0 | 1 | 4 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | |
23 | Mobile | Alabama | 1 | F | A | 31 | M | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 7 | 0 | 0 | 1 | 0 | 3 | 1 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | |
24 | Mobile | Alabama | 1 | F | B | 24 | S | 1 | I | 0 | 0 | 0 | 0 | 0 | 5 | 0 | 0 | 0 | 1 | 4 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | |
25 | Tempe | Arizona | 1 | F | B | 26 | M | 5 | 0 | 1 | 0 | 0 | 0 | 0 | 3 | 0 | 0 | 0 | 1 | 4 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | |
26 | Clearwater | Florida | 1 | M | W | 43 | M | 5 | 0 | 0 | 0 | 1 | 0 | 1 | 6 | 0 | 0 | 0 | 1 | 5 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | |
27 | Coral Springs | Florida | 1 | F | B | 29 | M | 4 | 1 | 0 | 0 | 0 | 0 | 0 | 5 | 0 | 0 | 0 | 1 | 2 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | |
28 | Surprise | Arizona | 1 | M | H | 25 | S | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 6 | 0 | 1 | 0 | 0 | 2 | 0 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | |
29 | Miramar | Florida | 0 | M | W | 27 | M | 5 | 0 | 0 | 0 | 1 | 0 | 1 | 4 | 0 | 0 | 0 | 1 | 4 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | |
30 | Hollywood | Florida | 1 | F | B | 30 | M | 4 | 0 | 0 | 0 | 1 | 0 | 1 | 3 | 0 | 0 | 0 | 1 | 4 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 |
Data Surgery Analysis Submission Worksheet. Data Surgery Analysis Submission Worksheet
Respondent Number | (1) City | (2) State | (3) Residential area type: 1 = Urban, 0= Rural | (4) Gender 1 = MALE 2 = Female 3 =other | (5) Race = W(white), B(black), H(hispanic), A(asian), O(others) | (6) Age | (7) Marital Status married = M, Single = S, Divorced = D, Widowed = W | (8) Employment | (9) Household Income | (10) Home Owner ? YES = 1, NO = 0 | (11) No. of household members? | (12) How do you describe your Health Status? YES = 1, NO = 0 | (13) Highest educational level attained: 1 = elementary; 2 = high school; 3 = some college; 4 = college graduate; 5 = post baccalaureate | (14) Health Problems | (15) Do you have Health Insurance? YES = 1, NO = 0. If YES, GO to 17 | (16) NOTE: If the answer in (15) is no, why not? 1 = too expensive; 2 = I am healthy I do not need it; 3 = other reason (please state the reason) GO to Question 18 after answering this question | (17) Insurance Type | (18) Are you vaccinated? Why or why not? (choose all that apply) | ||||||||||||||||||
1 = unemployed looking for work; 2 = retired; 3 = unemployed not looking for work; 4 = employed part time; 5= employed fulltime | Below $35,000? (yes = 1, no = 0) | $35,000 – $69,999 ? (yes = 1, no = 0) | $70,000 – $119,999 ? (yes = 1, no = 0) | $120,000 to $179,999 ? (yes = 1, no = 0) | $180,000 and above ? (yes = 1, no = 0) | BAD = 1, otherwise = 0 | FAIR = 1, otherwise = 0 | GOOD = 1, otherwise = 0 | EXCELLENT = 1, otherwise = 0 | Do you have Heart Problems/ Cancer/diabetes,other debilitating disease? YES = 1, NO = 0 | Do you have a Family History of Heart Problem, Cancer, diabetes, debilitating disease ? YES = 1, NO = 0 | 1=employer based (choose this if you are getting your insurance from your employer or if you are a dependent getting your insurance from your employed parents) 1 = yes 0 = no | 1 = MEDICARE; 0 = no | 1 = MEDICAID; 0 = no | 1 = obamacare or ACA 01 = no | 1 = TriCare or VA 0 = no | 1 = other (state the source); 0 = no | (A) YES, Because an infectious disease is a public health concern: 1 = describes my situation; 0 = does not describe my situation | (B) YES, it is required at work but I will get vaccinated even if it is not required: 1= describes my situation; 0 = does not describe my situation | (C) YES, only because it is required at work otherwise I will not get vaccinated: 1= describes my situation; 0 = does not describe my situation | (D) NO, because I choose not to: 1= describes my situation; 0 = does not describe my situation | (E) NO, only because I do not have time to schedule it because of my work and other obligations: 1= describes my situation; 0 = does not describe my situation | (F), NO, because it is not required at work otherwise I will get vaccinated: 1= describes my situation; 0 = does not describe my situation | |||||||||||||
1 | Wellington | FL | 1 | 1 | W | 19 | S | 3 | 0 | 0 | 1 | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 1 | 2 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
2 | PBG | FL | 1 | 1 | W | 31 | D | 5 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 1 | 4 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
3 | Boca Raton | FL | 1 | 1 | W | 37 | D | 5 | 0 | 0 | 1 | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 1 | 4 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 |
4 | Port St. Lucie | FL | 1 | 1 | A | 48 | D | 5 | 0 | 0 | 1 | 0 | 0 | 0 | 3 | 0 | 0 | 0 | 1 | 4 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 |
5 | Miami | FL | 1 | 1 | H | 30 | M | 5 | 0 | 0 | 1 | 0 | 0 | 0 | 2 | 0 | 0 | 1 | 0 | 3 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 |
6 | Miami | FL | 1 | 2 | B | 22 | S | 4 | 0 | 0 | 1 | 0 | 0 | 0 | 3 | 0 | 0 | 0 | 1 | 3 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
7 | Boca Raton | FL | 1 | 1 | w | 17 | S | 3 | 0 | 0 | 1 | 0 | 0 | 0 | 4 | 0 | 0 | 0 | 1 | 3 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 |
8 | Weston | FL | 1 | 1 | w | 52 | M | 5 | 0 | 0 | 0 | 1 | 0 | 1 | 2 | 0 | 0 | 1 | 0 | 5 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 |
9 | Jupiter | FL | 1 | 1 | w | 47 | M | 5 | 0 | 0 | 1 | 0 | 0 | 1 | 3 | 0 | 0 | 0 | 1 | 4 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 |
10 | Boca Raton | FL | 1 | 1 | w | 48 | D | 5 | 0 | 0 | 0 | 1 | 0 | 1 | 3 | 0 | 0 | 0 | 1 | 4 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
11 | Wellinton | FL | 1 | 1 | w | 61 | M | 5 | 0 | 0 | 0 | 0 | 1 | 1 | 2 | 0 | 0 | 1 | 0 | 5 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 |
12 | Fort Lauderdale | FL | 1 | 2 | B | 67 | M | 2 | 0 | 0 | 1 | 0 | 0 | 1 | 2 | 0 | 0 | 1 | 0 | 5 | 0 | 1 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 |
13 | Charlotte | NC | 0 | 2 | H | 48 | S | 5 | 0 | 0 | 1 | 0 | 0 | 1 | 5 | 0 | 0 | 0 | 1 | 3 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
14 | Jupiter | FL | 1 | 2 | W | 34 | M | 5 | 0 | 0 | 0 | 1 | 0 | 0 | 3 | 0 | 0 | 0 | 1 | 3 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 |
15 | PBG | FL | 1 | 1 | W | 35 | M | 5 | 0 | 0 | 0 | 0 | 1 | 0 | 3 | 0 | 0 | 1 | 0 | 3 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
16 | Port St. Lucie | FL | 1 | 1 | W | 57 | D | 5 | 0 | 0 | 1 | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 1 | 5 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 |
17 | Port St. Lucie | FL | 1 | 1 | W | 64 | M | 2 | 0 | 0 | 0 | 1 | 0 | 1 | 2 | 0 | 0 | 1 | 0 | 4 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
18 | Savannah | GA | 0 | 1 | W | 35 | S | 5 | 0 | 0 | 1 | 0 | 0 | 0 | 3 | 0 | 0 | 0 | 1 | 3 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
19 | Savannah | GA | 0 | 1 | W | 38 | S | 5 | 0 | 0 | 0 | 1 | 0 | 1 | 4 | 0 | 0 | 1 | 0 | 4 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 |
20 | Savannah | GA | 0 | 1 | W | 24 | S | 5 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 3 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 |
21 | Weston | FL | 1 | 1 | H | 22 | S | 4 | 0 | 0 | 1 | 0 | 0 | 0 | 2 | 0 | 0 | 1 | 0 | 3 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
22 | Miami | FL | 1 | 2 | H | 41 | D | 5 | 0 | 0 | 1 | 0 | 0 | 1 | 2 | 0 | 0 | 0 | 1 | 4 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 |
23 | Port St. Lucie | FL | 1 | 1 | W | 49 | D | 5 | 0 | 0 | 0 | 1 | 0 | 1 | 2 | 0 | 0 | 1 | 0 | 4 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 |
24 | Wellinton | FL | 1 | 2 | W | 71 | W | 2 | 0 | 0 | 0 | 1 | 0 | 1 | 2 | 0 | 0 | 0 | 1 | 5 | 0 | 1 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
25 | Wellinton | FL | 1 | 1 | W | 76 | M | 2 | 0 | 0 | 0 | 0 | 1 | 1 | 2 | 0 | 0 | 0 | 1 | 5 | 1 | 1 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 |
26 | Wellinton | FL | 1 | 1 | W | 55 | M | 5 | 0 | 0 | 0 | 1 | 0 | 0 | 2 | 0 | 0 | 0 | 1 | 3 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 |
27 | Port St. Lucie | FL | 1 | 1 | B | 63 | M | 5 | 0 | 0 | 1 | 0 | 0 | 1 | 2 | 0 | 0 | 0 | 1 | 4 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
28 | Boca Raton | FL | 1 | 1 | W | 54 | S | 5 | 0 | 0 | 1 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 1 | 3 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 |
29 | Boca Raton | FL | 1 | 1 | H | 66 | M | 4 | 0 | 0 | 1 | 0 | 0 | 1 | 3 | 0 | 0 | 1 | 0 | 3 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 |
30 | Boca Raton | FL | 1 | 2 | H | 19 | S | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 3 | 0 | 0 | 0 | 1 | 2 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
31 | Woodstock | GA | 0 | 2 | W | 54 | M | 5 | 0 | 0 | 0 | 0 | 1 | 1 | 3 | 0 | 0 | 1 | 0 | 3 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
32 | Woodstock | GA | 0 | 1 | W | 62 | M | 5 | 0 | 0 | 0 | 0 | 1 | 1 | 3 | 0 | 0 | 0 | 1 | 5 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 |
33 | Boca Raton | FL | 1 | 2 | W | 27 | M | 4 | 0 | 1 | 0 | 0 | 0 | 1 | 2 | 0 | 0 | 1 | 0 | 5 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 |
34 | Pompano | FL | 1 | 2 | W | 25 | S | 5 | 0 | 1 | 0 | 0 | 0 | 1 | 2 | 0 | 0 | 1 | 0 | 5 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 |
35 | Marrietta | GA | 0 | 2 | W | 18 | S | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 4 | 0 | 1 | 0 | 0 | 3 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
36 | Boca Raton | FL | 1 | 2 | O | 43 | M | 5 | 0 | 0 | 0 | 0 | 1 | 1 | 5 | 0 | 0 | 1 | 0 | 5 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
37 | Boynton Beach | FL | 0 | 2 | H | 21 | S | 4 | 0 | 1 | 0 | 0 | 0 | 0 | 3 | 0 | 0 | 0 | 1 | 3 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
38 | Ft. Lauderdale | FL | 0 | 2 | B | 25 | D | 5 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 5 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 |
39 | North Palm Beach | FL | 1 | 1 | W | 51 | S | 5 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 2 | 0 | 1 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 |
40 | Jupiter | FL | 0 | 2 | W | 35 | D | 5 | 0 | 0 | 1 | 0 | 0 | 1 | 2 | 0 | 0 | 0 | 1 | 5 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 |
41 | Boynton Beach | FL | 0 | 1 | W | 20 | S | 5 | 1 | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 1 | 0 | 0 | 3 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 |
42 | Macon | GA | 0 | 2 | O | 20 | S | 3 | 0 | 1 | 0 | 0 | 0 | 0 | 3 | 0 | 0 | 1 | 0 | 3 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 |
43 | Wellington | FL | 0 | 1 | W | 46 | M | 5 | 0 | 0 | 0 | 1 | 0 | 1 | 4 | 0 | 0 | 1 | 0 | 5 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 |
44 | Boca Raton | FL | 1 | 1 | O | 19 | S | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 0 | 1 | 0 | 3 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 |
45 | Boynton Beach | FL | 0 | 1 | W | 22 | S | 5 | 1 | 0 | 0 | 0 | 0 | 0 | 2 | 1 | 0 | 0 | 0 | 4 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
46 | Woodstock | GA | 1 | 2 | W | 22 | S | 5 | 1 | 0 | 0 | 0 | 0 | 0 | 3 | 0 | 0 | 0 | 1 | 2 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 |
47 | Boca Raton | FL | 1 | 2 | W | 20 | S | 5 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 1 | 0 | 3 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
48 | Webster | TX | 1 | 2 | O | 19 | S | 5 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 3 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 |
49 | Palm Bay | FL | 1 | 2 | A | 20 | S | 5 | 1 | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 0 | 1 | 0 | 4 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 |
50 | West Palm Beach | FL | 1 | 1 | W | 51 | M | 5 | 0 | 0 | 0 | 1 | 0 | 1 | 3 | 0 | 1 | 0 | 0 | 2 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 |
51 | West Palm Beach | FL | 1 | 2 | O | 47 | M | 5 | 0 | 0 | 0 | 1 | 0 | 1 | 3 | 0 | 0 | 0 | 1 | 5 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 |
52 | Fayeteville | AR | 0 | 1 | W | 20 | S | 4 | 0 | 0 | 1 | 0 | 0 | 0 | 5 | 0 | 0 | 1 | 0 | 3 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 |
53 | Woodstock | GA | 1 | 2 | W | 28 | S | 4 | 0 | 0 | 0 | 1 | 0 | 0 | 4 | 0 | 0 | 1 | 0 | 2 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 |
54 | Marrietta | GA | 1 | 2 | W | 16 | S | 3 | 0 | 0 | 0 | 1 | 0 | 0 | 3 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
55 | Canton | GA | 0 | 2 | W | 19 | M | 4 | 1 | 0 | 0 | 0 | 0 | 1 | 2 | 0 | 0 | 1 | 0 | 3 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 |
56 | Boca Raton | FL | 1 | 2 | W | 30 | M | 5 | 0 | 0 | 0 | 1 | 0 | 1 | 3 | 0 | 0 | 1 | 0 | 2 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 |
57 | Gainsville | FL | 0 | 1 | W | 62 | D | 2 | 0 | 0 | 1 | 0 | 0 | 1 | 2 | 0 | 1 | 0 | 0 | 4 | 1 | 1 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
58 | Albany | NY | 0 | 2 | W | 42 | M | 5 | 0 | 0 | 1 | 0 | 0 | 1 | 2 | 0 | 0 | 0 | 1 | 5 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 |
59 | West Palm Beach | FL | 1 | 2 | O | 17 | S | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 3 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
60 | Woodstock | GA | 0 | 2 | W | 45 | D | 5 | 0 | 1 | 0 | 0 | 0 | 1 | 2 | 0 | 0 | 1 | 0 | 4 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 |
61 | Jupiter | FL | 1 | 1 | W | 51 | M | 5 | 0 | 0 | 0 | 0 | 1 | 1 | 4 | 0 | 0 | 0 | 1 | 4 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 |
62 | Jupiter | FL | 1 | 2 | W | 50 | M | 3 | 1 | 0 | 0 | 0 | 0 | 1 | 4 | 0 | 0 | 0 | 1 | 4 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
63 | Bonyton Beach | FL | 1 | 2 | W | 22 | S | 4 | 1 | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 1 | 3 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 |
64 | Bonyton Beach | FL | 1 | 1 | W | 23 | S | 5 | 0 | 1 | 0 | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 1 | 4 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 |
65 | State College | PA | 0 | 2 | W | 24 | S | 5 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 5 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
66 | Boalsburg | PA | 0 | 1 | W | 25 | S | 5 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 4 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 |
67 | Kennet Square | PA | 1 | 1 | W | 58 | M | 5 | 0 | 0 | 0 | 1 | 0 | 1 | 3 | 0 | 0 | 1 | 0 | 4 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 |
68 | Kennet Square | PA | 1 | 2 | W | 57 | M | 5 | 0 | 0 | 0 | 0 | 1 | 1 | 3 | 0 | 0 | 0 | 1 | 4 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 |
69 | Kennet Square | PA | 1 | 1 | W | 26 | S | 5 | 0 | 1 | 0 | 0 | 0 | 0 | 3 | 0 | 0 | 0 | 1 | 3 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
70 | Jupiter | FL | 1 | 1 | W | 17 | S | 3 | 1 | 0 | 0 | 0 | 0 | 0 | 3 | 0 | 0 | 0 | 1 | 2 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 |
71 | Boca Raton | FL | 1 | 1 | W | 21 | S | 4 | 1 | 0 | 0 | 0 | 0 | 0 | 3 | 0 | 0 | 1 | 0 | 3 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 |
72 | Boca Raton | FL | 1 | 1 | W | 22 | S | 5 | 0 | 0 | 1 | 0 | 0 | 0 | 3 | 0 | 0 | 0 | 1 | 3 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
73 | Boca Raton | FL | 1 | 2 | W | 22 | S | 4 | 1 | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 1 | 3 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 |
74 | Boca Raton | FL | 1 | 1 | W | 23 | S | 5 | 0 | 0 | 1 | 0 | 0 | 0 | 3 | 0 | 0 | 0 | 1 | 3 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 |
75 | Boca Raton | FL | 1 | 2 | W | 23 | S | 5 | 0 | 1 | 0 | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 1 | 4 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
76 | Waterford | CT | 1 | 2 | W | 81 | W | 2 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 1 | 0 | 4 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
77 | Waterford | CT | 1 | 1 | W | 57 | M | 5 | 0 | 0 | 0 | 0 | 1 | 1 | 2 | 0 | 0 | 1 | 0 | 4 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 |
78 | Waterford | CT | 1 | 2 | W | 55 | M | 5 | 0 | 1 | 0 | 0 | 0 | 1 | 2 | 0 | 0 | 0 | 1 | 4 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 |
79 | Waterford | CT | 1 | 1 | W | 57 | M | 5 | 0 | 0 | 0 | 0 | 1 | 1 | 2 | 0 | 1 | 0 | 0 | 4 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
80 | East Lyme | CT | 1 | 2 | W | 29 | M | 5 | 0 | 1 | 0 | 0 | 0 | 1 | 3 | 0 | 0 | 0 | 1 | 5 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 |
81 | East Lyme | CT | 1 | 1 | W | 30 | M | 5 | 0 | 1 | 0 | 0 | 0 | 1 | 3 | 0 | 0 | 0 | 1 | 4 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 |
82 | Glen Allen | VA | 1 | 1 | W | 80 | M | 2 | 1 | 0 | 0 | 0 | 0 | 1 | 2 | 0 | 0 | 1 | 0 | 4 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
83 | Glen Allen | VA | 1 | 2 | W | 78 | M | 2 | 1 | 0 | 0 | 0 | 0 | 1 | 2 | 0 | 0 | 0 | 1 | 4 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
84 | Richmond | VA | 1 | 1 | W | 50 | M | 5 | 0 | 0 | 0 | 0 | 1 | 1 | 6 | 0 | 0 | 0 | 1 | 5 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
85 | Richmond | VA | 1 | 2 | W | 49 | M | 5 | 0 | 0 | 0 | 0 | 1 | 1 | 6 | 0 | 0 | 1 | 0 | 5 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 |
86 | Richmond | VA | 1 | 2 | W | 18 | S | 3 | 1 | 0 | 0 | 0 | 0 | 0 | 6 | 0 | 0 | 0 | 1 | 2 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
87 | Richmond | VA | 1 | 2 | W | 18 | S | 3 | 1 | 0 | 0 | 0 | 0 | 0 | 6 | 0 | 0 | 0 | 1 | 2 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
88 | Boston | MA | 1 | 2 | W | 22 | S | 4 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 3 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
89 | Boston | MA | 1 | 1 | W | 23 | S | 5 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 4 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 |
90 | Canton | CT | 1 | 1 | W | 21 | S | 5 | 0 | 0 | 1 | 0 | 0 | 0 | 5 | 0 | 0 | 1 | 0 | 3 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |