Predicted Finish Time
{{ predicted_time_hms }}
{{ pace_km_str }} /km • {{ pace_mi_str }} /mi
Prev: {{ prev_distance_label }} in {{ prev_time_hms }} Target: {{ target_distance_label }} p = {{ exponent_display }} Adj {{ adjust_percent }} %
: :
{{ adjust_percent }} %
Metric Value Copy
{{ row.label }} {{ row.value }}
{{ splitUnitDisplay }}
# Distance Split Cumulative Copy
{{ row.label }} {{ row.distance }} {{ row.split }} {{ row.cumulative }}
Scenario p Adj % Finish Δ vs input Copy
{{ row.label }} {{ row.exponent }} {{ row.adjust }}
{{ row.finish }}
{{ row.pace }}
 {{ row.delta }}
{{ chartDatasetDescription }}
Enter a previous effort and a target distance to render a chart. 

          

        

      


      
    

  

                

                

                    

                        

                            Tags:
                                                            
                                    Cardio Training
                                
                                ,                                                             
                                    Running
                                
                                                                                    

                        

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Race finish times describe how long you are expected to take over a distance based on past efforts. They support planning for future races and structured training sessions. This predictor links your last measured performance with another distance you want to explore.

  
You provide a recent race distance and its official time and then pick a new target distance. The calculator turns those numbers into a predicted finish time with matching pace per kilometer and per mile. It also reveals how that new effort compares with your earlier pace.

  
For example you might enter a five kilometer event completed in twenty five minutes to see what that suggests for a ten kilometer race. You can then judge whether the projected pace feels realistic and adjust your goals before committing to a strategy.

  
Predictions remain estimates rather than guarantees and they assume similar fitness surface and weather. Training cycles fatigue illness or heat can move the real result away from the model. Treat any single run as one data point and look for patterns across several races.

  
Advanced controls let you describe how quickly you tend to slow as distance grows and how course conditions may speed or slow your finishing time. Comparing the scenario presets with your actual results helps you tune those controls and build a more personal picture of your endurance.

  
This predictor provides informational estimates and does not substitute professional coaching or medical advice.






  
Technical Details:

  
Race performance in this calculator follows the Riegel model, which treats finish time as a power function of race distance. A previous race distance and time define a baseline effort, and the target distance scales that effort through an exponent parameter p that captures how quickly performance fades as races get longer.

  
Distances are represented internally in meters, covering events from 400 m to 50 km, while input times are converted into whole seconds from hours, minutes, and seconds. From these quantities the script computes a predicted finish time for the target distance, along with average pace per kilometer and per mile and corresponding speeds in kilometers per hour and miles per hour.

  
A condition adjustment parameter a lets you adjust the prediction for course and environment. Positive values lengthen the predicted time to reflect heat, hills, or trail terrain, while negative values shorten it for faster courses or cooler days. Scenarios apply small shifts to p and a around your baseline to illustrate how sensitive your outcome is to fitness and conditions.

  
The primary prediction combines the baseline effort, the distance ratio, the exponent p, and the condition adjustment into a single equation. The computation is performed in seconds and is then formatted into human readable times in H:MM:SS or M:SS form.


  
The core prediction formula is:

  

    
      
        
          t
          2
        
        =
        
          t
          1
        
        ×
        
          
            
              
                d
                2
              
              
                d
                1
              
            
          
          p
        
        ×
        
          (
          1
          +
          
            a
            100
          
          )
        
      
    
  


  

    

      
      
        

          Symbol
          Meaning
          Unit / Datatype
          Source
        

      
      
        

          t1
          Previous race finish time converted to seconds
          s
          Input
        

        

          d1
          Previous race distance
          m
          Input (predefined options)
        

        

          t2
          Predicted finish time for the target distance
          s
          Derived
        

        

          d2
          Target race distance
          m
          Input (predefined options)
        

        

          p
          Riegel exponent describing performance decay with distance
          dimensionless
          Input (typically near 1.06)
        

        

          a
          Condition adjustment percent applied to the prediction
          percent
          Input (slider or scenario)
        

      
    

  


  

  
From the predicted time the script derives pace per kilometer and per mile by dividing the finish time by the distance in those units. It also computes average speed in kilometers per hour and miles per hour, formatted with two decimal places. Split tables then map the prediction into equal kilometer or mile segments and a final partial segment when the distance is not an exact multiple of the chosen split unit.

  
Scenario rows vary p and a around your current inputs to illustrate how a cooler day, a hilly course, or extra fatigue would change both finish time and pace. Charts plot either split timelines or scenario comparisons, using cumulative time on one axis and distance or condition labels on the other, while tooltips reveal formatted times and paces at each point.


  
Validation and bounds:

  

    

      
      
        

          Field
          Type
          Min
          Max
          Step / Pattern
          Error handling
        

      
      
        

          Previous hours
          Integer
          0
          None
          Whole numbers
          Values below 0 are clamped to 0.
        

        

          Previous minutes
          Integer
          0
          59
          Whole numbers
          Values outside 0 to 59 are clamped into range.
        

        

          Previous seconds
          Integer
          0
          59
          Whole numbers
          Values outside 0 to 59 are clamped into range.
        

        

          Previous distance
          Categorical
          400 m
          50 000 m
          Fixed event list
          Must match one of the predefined race distances.
        

        

          Target distance
          Categorical
          400 m
          50 000 m
          Fixed event list
          Must match one of the predefined race distances.
        

        

          Exponent p
          Number
          0.9
          1.2
          Step 0.01
          Scenarios clamp p in a slightly wider 0.9 to 1.3 band.
        

        

          Condition adjustment a
          Number
          −15
          30
          Step 1
          Scenarios clamp adjustments between −25 and 45 percent.
        

        

          Split unit
          Categorical
          1 km
          1 mi
          km or mi
          Determines pacing splits and chart axes.
        

      
    

  


  
Input and output formats:

  

    

      
      
        

          Input
          Accepted values
          Output
          Encoding / precision
          Rounding policy
        

      
      
        

          Time fields
          Integer hours, minutes, seconds
          Finish time and paces
          Seconds, H:MM:SS and M:SS text
          Seconds rounded to nearest whole second.
        

        

          Distance choices
          Standard track and road race distances
          Predicted time and splits
          Meters, kilometers, miles
          Split distances carry up to two decimal places.
        

        

          Exports
          Summary, splits, scenarios, JSON data
          CSV, DOCX, chart images, JSON file
          UTF-8 text, bitmap chart images
          Exports preserve the same rounding as the on screen values.
        

      
    

  


  
Units, precision, and rounding:

  
All calculations use seconds as the base time unit and meters as the base distance unit. Minutes and seconds are converted to seconds using integer arithmetic, and finish times are rounded to the nearest whole second before being formatted. Average speeds are formatted with two decimal digits, and split distances that do not land on exact kilometers or miles are displayed with up to two decimal places.


  
Assumptions and limitations:

  
    
    
  • Heads-upThe Riegel exponent p is treated as constant across all distances, even though some runners change profile between short and long events.
    • 
    
  • The model assumes similar terrain, surface, and weather between the original race and the predicted event.
    • 
    
  • Input times are assumed to be accurate official results rather than approximate guesses from training runs.
    • 
    
  • Heads-upThe condition adjustment is a simple percentage applied to time and does not capture every factor that affects performance.
    • 
    
  • Scenarios only vary p and a within modest bands and do not account for large lifestyle or training changes.
    • 
    
  • Split pacing assumes even effort throughout the race and may not match preferred negative or positive splits.
    • 
    
  • Speeds and paces are averages and do not describe within race variability such as surges or slow sections.
    • 
    
  • The script does not classify results into ability categories; interpretation remains up to the user.
    • 
  


  
Edge cases and error sources:

  
    
    
  • Leaving previous time at zero seconds prevents any prediction from being shown.
    • 
    
  • Very large hour values can produce long predicted times that compress chart scales and make trends harder to read.
    • 
    
  • Non numeric inputs are coerced into numbers, which may become zero and distort results.
    • 
    
  • Using extremely low p values within the allowed range can give overly optimistic long distance predictions.
    • 
    
  • Using very high p values can make long distance predictions unrealistically slow for well conditioned runners.
    • 
    
  • Rounding to whole seconds means very small differences in p or a may not appear in the formatted time.
    • 
    
  • Distance conversions rely on fixed constants for miles and standardized race distances and ignore course measurement quirks.
    • 
    
  • Changing split units after inspecting charts can briefly reuse earlier chart state until a redraw completes.
    • 
    
  • Clipboard or file download restrictions in the browser can cause copy and export actions to fail silently.
    • 
    
  • Closing the page or refreshing clears the current configuration unless query parameters are used to share or restore settings.
    • 
  


  
Privacy and compliance:

  
The visible script performs its calculations on the client side and does not include explicit network requests, though shared export utilities may have their own behavior. Avoid entering sensitive personal information, and remember that race predictions are for training and planning rather than medical, legal, or contractual decisions.






  
Step-by-Step Guide:

  
Race time prediction in this calculator turns one recent race into a detailed view of what a similar effort might look like at another distance.

  
    
    
  1. Select your recent race distance using the Previous distance control.
    2. 
    
  2. Enter the official finish time into the hour, minute, and second fields, keeping the same format used on your results sheet.
    3. 
    
  3. Choose the event you want to predict as the Target distance.
    4. 
    
  4. Open the advanced options and adjust the Exponent p or Condition adjustment if you want to reflect personal strengths or course difficulty.
    5. 
    
  5. Select whether you prefer kilometer or mile splits with the Split unit choice.
    6. 
    
  6. Review the predicted finish time, pacing table, scenarios, charts, and optional exports to understand how your performance might translate.
    7. 
  

  
ImportantIf the predicted time looks wildly different from your expectations, double check that the previous result, target distance, and exponent p reflect realistic recent racing conditions.

  
For instance a 25 minute 5 km with default settings predicts roughly a 52 minute 10 km; you can then nudge the adjustment to reflect a windy course or a cool evening race.

  
    
    
  • Use a consistent exponent p across a training block to make predictions comparable between weeks.
    • 
    
  • Save split tables or charts when a race outcome matches the prediction closely and use them as templates for future pacing plans.
    • 
    
  • Experiment with scenarios before race week to decide how much extra time to allow for heat or hills.
    • 
  






  
Features:

  
    
    
  • Riegel model based predictions from one measured race to a wide range of standard distances.
    • 
    
  • Adjustable exponent p and condition percentage to reflect individual endurance and course difficulty.
    • 
    
  • Detailed split tables for kilometers or miles, including a final partial segment where necessary.
    • 
    
  • Scenario presets that show how cooler, hotter, hillier, or more fatigued conditions might shift finish time and pace.
    • 
    
  • Interactive charts for split timelines and scenario comparisons with informative tooltips.
    • 
    
  • Export options for summaries, splits, scenarios, and JSON data to integrate with training logs or reports.
    • 
  






  
FAQ:


  

    How accurate are the predictions?
    
Accuracy depends on how closely your training, course, and conditions match the original race. The Riegel exponent assumes broadly steady endurance and may over or under estimate if your fitness has shifted significantly.Treat close agreement with recent races as a sign that your settings are well tuned.

  


  

    What distances can I model?
    
You can select common track and road races from 400 m through 50 km, including one mile, 5 km, 10 km, 10 miles, half marathon, and marathon. Predictions always use the exact meter values associated with each event option.Custom distances are not supported in this version.

  


  

    How should I choose exponent p?
    
The default value 1.06 suits many road runners. Lower values make long distance predictions faster relative to short races, while higher values slow them down. You can adjust p until predictions roughly match a few of your recent results at different distances.Keep p within realistic bounds to avoid implausible outputs.

  


  

    What does the condition adjustment do?
    
The condition adjustment a applies a simple percentage change to the predicted time. Positive values lengthen the result to represent tougher races, and negative values shorten it for favorable conditions. The scenarios tab shows several presets that combine changes in p and a.It does not replace detailed environmental modeling.

  


  

    Is my data stored anywhere?
    
The visible script uses your inputs to calculate predictions, tables, charts, and exports during the current session. It does not include explicit calls to send data elsewhere, though the hosting site or shared utilities may still log usage.Avoid pasting sensitive personal information into text fields.

  


  

    Can I use this without a connection?
    
Calculations run in the page script once it is loaded. Reloading or opening the tool on a new device still depends on the hosting site being reachable, and caching behavior depends on your browser settings.Keep a local copy of exports if you need access during travel.

  


  

    How do I export split tables?
    
Within the splits view you can copy the table as CSV, download it directly, or export it as a document. Each option uses the same underlying data, so exported figures match what you see on screen.Check your browser download folder if files are hard to find.

  


  

    What does a borderline result mean?
    
When two scenarios differ only slightly in finish time, small changes in weather, sleep, or pacing strategy can decide which one you actually match. In those cases plan using a range and adjust expectations during the race rather than chasing an exact second.Use pacing bands rather than single target times for important events.

  






  
Troubleshooting:

  
If something looks off in your prediction or exports, these quick checks often resolve the issue before you need more detailed debugging.

  
    
    
  • If no prediction appears, confirm that the previous time fields describe a nonzero result and that both distances are selected.
    • 
    
  • If times seem unrealistic, verify that you entered minutes and seconds in the correct fields rather than swapping them.
    • 
    
  • If charts remain blank, switch to a different tab and back to trigger a fresh render once inputs are complete.
    • 
    
  • If copying or downloads fail, check browser permissions for clipboard access and automatic file downloads.
    • 
    
  • If exported tables look empty, ensure that the current tab actually contains rows before running an export action.
    • 
    
  • If scenario names display but values show as zeros, double check that your exponent and adjustment are numeric and not left blank.
    • 
  

  





  
Advanced Tips:

  
    
    
  • 
      
      Calibrate exponent p using two or three recent races at different distances, then keep it fixed while you explore scenarios.
    
    • 
    
  • 
      
      Use kilometer splits for shorter events and mile splits for longer races to match how markers usually appear on course.
    
    • 
    
  • 
      
      Compare baseline and hilly course scenarios to decide how much you should adjust target pace for different profiles.
    
    • 
    
  • 
      
      Export JSON data when you want to integrate predictions into custom dashboards or long term training logs.
    
    • 
    
  • 
      
      Capture chart images after important races so you can visually compare expected and actual pacing patterns across a season.
    
    • 
    
  • 
      
      Periodically revisit your settings after big improvements or breaks in training, since fitness shifts can change how well the model fits you.
    
    • 
  






  
Glossary:

  

    
Finish time

    
Total elapsed time needed to complete a race distance.


    
Riegel model

    
Power law relationship that links race time to distance using an exponent.


    
Exponent p

    
Parameter describing how much additional distance slows predicted finish time.


    
Condition adjustment a

    
Percentage factor that speeds or slows the predicted time for race conditions.


    
Pace

    
Average time needed to cover one kilometer or one mile.


    
Split

    
Segment of a race distance with its own split time and cumulative time.


    
Scenario

    
Preset combination of exponent and condition adjustment used for comparison.


    
Average speed

    
Distance divided by time, expressed in kilometers per hour or miles per hour.