Using a Formula to look at multiple criteria and return a value

[ALJ716]

I want a formula to look at cell AG2 and return a value based on the score in cell AG2.
Here are my scoring ranges and the value I need to be returned based on the score in the cells in column AG.

Score Return Value
76-100% A
50-75% B
26-49% C
14-25% D
0-13% E

Is there a way to put a formula with all the ranges below to return the values based on the range and score in the call it is looking at?

Job Fit FIle Ongoing.xlsx
	A	B	C	D	E	F	G	H	I	J	K	L	M	N	O	P	Q	R	S	T	U	V	W	X	Y	Z	AA	AB
1	LastName	FirstName	Assembly - Chassis - MAC10/MAD10 (100%)	Assembly - Chassis - MAC20/MAD20 (100%)	Assembly - Doorline - MAA30/MAB30 (100%)	Assembly - Engine Line - MAC30/MAD30 (100%)	Assembly - Final - MAE10/MAF10 (100%)	Assembly - Final - MAE20/MAF20 (100%)	Assembly - Final - MAE30/MAF30 (100%)	Assembly - IP - MAA30/MAB30 (100%)	Assembly - Trim - MAA10/MAB10 (100%)	Assembly - Trim - MAA20/MAB20 (100%)	Body Weld - Quality - MWE10/MWE20 (100%)	Body Weld - Shellbody - MWC10/MWD10 (100%)	Body Weld - Shellbody - MWC20/MWD20 (100%)	Body Weld - Shellbody - MWC30/MWD30 (100%)	Body Weld - Side Member - MWA30/MWB30 (100%)	Body Weld - Underbody - MWA10/MWB10 (100%)	Paint - Applications - MTC10/MTD10 (100%)	Paint - ED - MTA10/MTB10 (100%)	Paint - Finish - MTC30/MTD30 (100%)	Paint - Sealer - MTA20/MTB20 (100%)	Production Control (PC) - Conveyance - BPO10/BRO10 (100%)	Production Control (PC) - Conveyance - BPO30/BRO30 (100%)	Quality - Assembly Inspection (AI) - QE020/QF020 (100%)	Quality - Vehicle Performance (VP) - QE010/QF010 (100%)	Stamping / Press - 1A Press - MWF10/MWF20 (Preferred) (100%)
2	Jones	Miyoshi	No	Yes	Yes	No	No	No	Yes	No	No	Yes	No	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	No	No	Yes	No	60%
3	Thompson	Ashley	No	Yes	Yes	No	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	No	No	Yes	Yes	84%
4	Kuni	Jasmine	No	No	No	No	No	No	No	Yes	No	No	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	No	Yes	No	No	Yes	Yes	52%
5	Croft	Madison	No	Yes	Yes	No	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	No	No	Yes	Yes	84%
6	Torres	Cesar	No	No	Yes	No	No	No	No	No	No	No	No	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	No	Yes	No	No	Yes	No	44%
7	Brown	Destany	No	Yes	Yes	No	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	No	Yes	Yes	88%
8	Beckum	Christopher	Yes	No	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	96%
9	Williams	Zackre	Yes	No	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	96%
10	Bryan	David	No	Yes	Yes	No	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	No	No	Yes	Yes	84%
11	Ferguson	Jeremy	No	No	Yes	No	Yes	Yes	No	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	No	No	Yes	Yes	76%
12	Patterson	Leidra	No	Yes	Yes	No	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	No	No	Yes	Yes	84%
13	Garth	Bryson	No	No	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	92%
14	Luhers	Alfredo	No	No	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	92%
15	Berry	Precious	No	Yes	Yes	No	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	No	No	Yes	Yes	84%
16	Conner	Ira	No	Yes	Yes	No	No	No	Yes	No	No	Yes	No	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	No	No	Yes	No	60%
17	Hatchett	Lavorris	No	Yes	Yes	No	No	No	No	No	No	Yes	No	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	No	Yes	No	60%
18	Allen	Marcie	No	No	Yes	No	No	No	No	No	No	No	No	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	No	Yes	No	No	Yes	No	44%
19	Treadaway	Zackary	No	Yes	Yes	No	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	No	Yes	Yes	88%
20	Poole	Jamarrio	No	Yes	Yes	No	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	No	No	Yes	Yes	84%
21	Gillespie	Quentin	No	No	Yes	No	No	No	No	No	No	Yes	No	No	Yes	Yes	Yes	Yes	Yes	Yes	No	Yes	Yes	Yes	No	Yes	No	48%
22	Wheeler	Grant	Yes	No	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	96%
23	Irvin	Charles	Yes	No	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	96%
24	Bishop	Stony	No	Yes	Yes	No	No	No	No	No	No	Yes	No	No	Yes	Yes	Yes	Yes	Yes	Yes	No	Yes	Yes	No	No	Yes	No	48%
25	Pierce	Dakota	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	100%
26	Jumper	Charles	Yes	No	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	96%
27	Taylor	Jordan	No	No	Yes	No	No	No	No	No	No	Yes	No	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	No	No	Yes	No	52%
28	Nabors	Amiracle	No	No	Yes	No	No	No	No	No	No	No	No	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	No	No	No	No	Yes	No	40%
29	Williams	Gerrod	No	No	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	92%
30	Harris	Jocque'tavious	No	No	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	92%
31	Birmingham	Tianna	No	Yes	No	No	Yes	Yes	Yes	No	Yes	Yes	No	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	No	No	Yes	Yes	72%
32	Decanter	Joshua	No	No	No	No	Yes	Yes	Yes	No	No	Yes	No	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	72%
33	Lane	Alyssia	No	No	Yes	No	No	No	No	No	No	No	No	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	No	Yes	No	No	Yes	No	44%
34	Knox	Octaivis	Yes	No	No	Yes	Yes	Yes	Yes	Yes	Yes	Yes	No	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	88%
35	York	Landen	No	Yes	Yes	No	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	No	Yes	Yes	88%
36	Farias	Zachery	No	No	No	No	No	No	No	No	No	No	No	Yes	No	No	No	No	No	Yes	No	No	Yes	No	No	No	No	12%
37	Norris	Anthony	Yes	No	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	96%
38	Harnage	Patrick	No	Yes	Yes	No	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	No	Yes	Yes	88%
39	Gates	Ashley	No	Yes	No	No	No	No	Yes	No	No	Yes	No	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	No	No	Yes	No	56%
40	Brown	Jaylon	No	No	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	92%
41	Williams	Hillary	No	Yes	Yes	No	No	No	Yes	No	No	Yes	No	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	No	No	Yes	No	60%
42	Moustakim	Taib	No	Yes	No	No	No	No	No	No	No	Yes	No	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	No	Yes	No	56%
43	Luhers	Chasity	No	No	Yes	No	No	No	No	No	No	No	No	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	No	No	No	No	Yes	No	40%
44	Moreno	Annette	No	Yes	Yes	No	No	No	No	No	No	Yes	No	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	No	No	Yes	No	56%
Sheet1

Cell Formulas
Range	Formula
AB2:AB44	AB2	=COUNTIF(C2:AA2,"yes")/25

 

[Joe4]

Welcome to the Board!

Here is one way:

=IF(AG2>=0.76,"A",IF(AG2>=0.5,"B",IF(AG2>=0.26,"C",IF(AG2>=0.14,"D","E"))))

 

[Fluff]

Hi & welcome to MrExcel.
How about

=CHAR(XMATCH(AB2,{1,0.75,0.49,0.25,0.13},1)+64)

 

[ALJ716]

Welcome to the Board!

Here is one way:

=IF(AG2>=0.76,"A",IF(AG2>=0.5,"B",IF(AG2>=0.26,"C",IF(AG2>=0.14,"D","E"))))

This worked perfectly! Thank you!

 

[ALJ716]

Hi & welcome to MrExcel.
How about

=CHAR(XMATCH(AB2,{1,0.75,0.49,0.25,0.13},1)+64)

This one worked as well.

 

[Fluff]

Glad we could help & thanks for the feedback.