Fusrodah & Quantify
Fusrodah Fusrodah
I’ve been researching the Battle of Hastings and am thinking of modeling the tactics in a spreadsheet. Do you have any data or a framework that could help us quantify the outcome more precisely?
Quantify Quantify
Quantify Sure thing—here’s a quick template you can paste into Excel or Google Sheets and start filling in: **Sheet 1: Summary** - Date (01-10-1066) - Side (Norman/English) - Commander (William I, Harold II) - Total Troops (Norman, English, French, Irish) - Casualties (total, killed, wounded) - Outcome (victory/defeat) **Sheet 2: Unit Details** - Unit ID - Unit Type (archers, infantry, cavalry, ship‑borne troops) - Strength (initial number) - Strength After (if you want to model attrition) - Morale (scale 1‑10) - Terrain Advantage (flat, hill, marsh) - Weather (clear, rain, fog) **Sheet 3: Timeline (by minute or event)** - Time stamp - Event (e.g., “Norman archers launched”, “English shield wall held”, “Norman cavalry charge”) - Action (attack, defend, retreat) - Result (successful, failed, neutral) - Casualty impact **Sheet 4: Visualization & Analysis** - Pivot tables for casualties by side, unit type - Conditional formatting: red for high casualties, green for low - Bar charts for troop strength over time - Scatter plot: Morale vs. Casualty ratio **Data Sources to Populate** - Primary: *Gesta Normannorum Ducum* (William the Conqueror’s chronicle), *Anglo‑Saxon Chronicle* - Secondary: “The Battle of Hastings” by David Nicolle, “The Making of England” by Frank Stenton - Numbers: Norman army estimated 10,000–15,000, English 8,000–12,000; casualties roughly 4,000‑5,000 total (both sides) **Quick Tips** 1. Keep each unit type in its own row; you can then calculate totals automatically. 2. Use a simple formula like `=SUMIF(UnitType,"Cavalry",Strength)` to get cavalry counts. 3. Color‑code each side—blue for Norman, red for English—to track outcomes visually. 4. Add a column for “Key Decision” and write a short note; that helps correlate tactics with results. Now you have a data framework that’s as clean as a spreadsheet and as precise as a data analyst’s eye. Good luck modeling—just remember: if the numbers start lying, double‑check your source, because that’s the one thing data might actually do.
Fusrodah Fusrodah
Your framework is solid, but a few points to tighten the discipline: define a fixed casualty rate per unit type based on historical averages, use a consistent morale decay formula, and anchor your timeline to key decisions rather than arbitrary minutes. Stick to the numbers, double‑check the sources, and you’ll model the outcome with the same precision as a veteran’s blade.
Quantify Quantify
Thanks for the feedback—here’s a tightened version with the numbers you asked for: **Casualty Rate (average per unit type)** - Archers: 15 % of initial strength per engagement - Infantry: 25 % per engagement - Cavalry: 35 % per engagement - Ship‑borne: 10 % (mostly due to landing) **Morale Decay Formula** - Start at 10 for each unit - After each engagement: `Morale = Morale – (CasualtyRate × 0.3)` - If morale drops below 4, flag the unit as “low morale” and auto‑apply a 10 % combat penalty **Timeline Anchored to Key Decisions** 1. 06:00 – Norman archers open fire (first engagement) 2. 07:15 – English shield wall holds (second engagement) 3. 08:00 – Norman cavalry charge (third engagement) 4. 09:30 – English forces break (fourth engagement) 5. 10:15 – Final retreat/withdrawal (fifth engagement) Each decision point is a row in your timeline sheet; you can drag the casualty rate and morale formulas across the columns for each unit type. Double‑check the casualty rates against the *Anglo‑Saxon Chronicle* and Nicolle’s work; if they’re off, your model will be off, and that’s the only thing data might lie about. Happy modeling—watch the numbers like a guard dog watching the snacks.
Fusrodah Fusrodah
Well done on tightening the parameters; the precision is commendable. I’d suggest running a quick sanity check on the cumulative casualty totals for each side—make sure the sums do not exceed the initial strengths. Also, track morale as a cumulative function rather than resetting each engagement; that will capture the gradual erosion seen in real battles. Once you confirm the numbers line up with the primary sources, the model will reflect the historical outcome with fidelity.