pith. sign in
Pith Number

pith:BCY3PZNT

pith:2026:BCY3PZNTHWQMJCWBXTR3QU7CSM
not attested not anchored not stored refs resolved

Optimising football transfer strategy under budget constraints: A weighted multi-criteria approach

Rishideep Roy, Soudeep Deb, Tathagata Basu

A club's optimal football transfers can be determined by feeding performance and price predictions into a weighted multi-criteria optimization that respects budget limits.

arxiv:2605.13926 v1 · 2026-05-13 · stat.AP

Add to your LaTeX paper
\usepackage{pith}
\pithnumber{BCY3PZNTHWQMJCWBXTR3QU7CSM}

Prints a linked badge after your title and injects PDF metadata. Compiles on arXiv. Learn more · Embed verified badge

Record completeness

1 Bitcoin timestamp
2 Internet Archive
3 Author claim open · sign in to claim
4 Citations open
5 Replications open
Portable graph bundle live · download bundle · merged state
The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

The predicted ratings and estimated transfer prices are integrated into a weighted multi-criteria constrained optimisation framework that determines a club's transfer activities at the end of the season.

C2weakest assumption

That linear mixed-effects models built on player characteristics, recent performance, team context, and league effects will produce reliable enough predictions of future performance and market prices to drive useful optimization decisions.

C3one line summary

A framework combining linear mixed-effects models for player ratings and prices with multi-criteria optimization and auction simulation for football transfers, illustrated on 2018-19 Premier League data.

References

66 extracted · 66 resolved · 0 Pith anchors

[1] Saikia, Hemanta and Bhattacharjee, Dibyojyoti and Mukherjee, Diganta and Saikia, Hemanta and Bhattacharjee, Dibyojyoti and Mukherjee, Diganta , journal=. 2019 , publisher= 2019
[2] IEEE signal processing magazine , volume= 2004
[3] Proceedings of the 2024 9th International Conference on Machine Learning Technologies , pages= 2024
[4] Humanities and Social Sciences , volume=
[5] Depken, Craig A and Globan, Tomislav , journal=. 2021 , publisher= 2021
Receipt and verification
First computed 2026-05-17T23:39:15.514784Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

08b1b7e5b33da0c48ac1bce3b853e293354d134b6e422dd6699d1b9177c69d2a

Aliases

arxiv: 2605.13926 · arxiv_version: 2605.13926v1 · doi: 10.48550/arxiv.2605.13926 · pith_short_12: BCY3PZNTHWQM · pith_short_16: BCY3PZNTHWQMJCWB · pith_short_8: BCY3PZNT
Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/BCY3PZNTHWQMJCWBXTR3QU7CSM \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 08b1b7e5b33da0c48ac1bce3b853e293354d134b6e422dd6699d1b9177c69d2a
Canonical record JSON
{
  "metadata": {
    "abstract_canon_sha256": "eb7a91461709c3c8444d8d97e90f548342816f2baf00f5a34de3e41c980fb086",
    "cross_cats_sorted": [],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "stat.AP",
    "submitted_at": "2026-05-13T15:27:51Z",
    "title_canon_sha256": "1b652a4278fbe9157581202afadc9dac08ab91af1d1d07521ce9f526a492c96c"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.13926",
    "kind": "arxiv",
    "version": 1
  }
}